Public Opinion Survey on the Accuracy of Weather Forecasts ...€¦ · Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010 - Report - Prepared for Prepared

Public Opinion Survey on the Accuracy of

Weather Forecasts in Hong Kong 2010

- Report -

Prepared for

Prepared by

May 2010

Table of Contents

1 Executive Summary ............................................................................................................ 1

2 Background ......................................................................................................................... 8

3 Objectives ............................................................................................................................ 9

4 Methodology ...................................................................................................................... 10

4.1 Survey Coverage ....................................................................................................... 10

4.2 Research Design ........................................................................................................ 10

4.3 Questionnaire Design ................................................................................................. 11

4.4 Statistical Analysis and Presentation of Survey Results ............................................. 11

5 Detailed Findings .............................................................................................................. 12

5.1 Demographic Profiles of Respondents ....................................................................... 12

5.2 Degree of Concern about Weather Information .......................................................... 13

5.3 Channels to Access Weather Information .................................................................. 13

5.3.1 Popularity of channels to access weather information ............................................................ 13

5.4 Opinions towards the Accuracy of Weather Forecasts over the Past Several Months 16

5.4.1 Overall accuracy level of weather forecasts.............................................................................. 16

5.4.2 Percentage of accurate weather forecasts ................................................................................ 17

5.4.3 Accuracy level of different aspects of weather forecasts ........................................................ 18

5.5 Overall Satisfaction with the Hong Kong Observatory’s Services over the Past Several

Months ....................................................................................................................... 20

5.6 Accuracy Level when Compared to 3 or 4 Years Ago ................................................. 21

5.6.1 Comparison: Accuracy Level of Current Weather Forecasts .................................................. 21

5.6.2 Comparison: Accuracy Level of Current Tropical Cyclone Warning Services ...................... 22

Appendix I: Questionnaire ....................................................................................................... 23

Appendix II: Charts ................................................................................................................... 30

Appendix III: Frequency Tables of Survey Findings .............................................................. 40

Appendix IV: Survey Data Analysis (Cross Tabulation and Statistical Test Results) .......... 48

Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010

1 May 2010

1 Executive Summary

Introduction

The objective of this survey is to gauge the public’s opinions on the accuracy of weather

forecasts and warnings issued by Hong Kong Observatory (HKO). Specifically, respondents

were invited to express views on the accuracy of weather forecasts based on different

aspects, performance of the HKO over a medium to longer term, and possible channels to

access weather information.

Infogroup|ORC was invited and commissioned by the HKO to conduct two waves of survey

in April and October 2010.

The findings of the first wave of this public opinion survey is summarized in this report; a

total of 1 008 respondents within a systematically selected random sample were

successfully enumerated during the fieldwork period from 16th April to 30th April 2010,

constituting a response rate of 76.29%.

Overview of the Fieldwork Process

Questionnaire Design

In early April, Infogroup|ORC has prepared both the Chinese and English questionnaire

based on the requirements specified by HKO to be pilot tested.

Pilot Survey

The pilot test was conducted on 8 April 2010 to test for the feasibility of the questionnaire

before the commencement of the main fieldwork. Consequently, 30 interviews were

successfully conducted in the pilot test, with interviewing time in the range of 5 to 7 minutes.

No problematic area was identified during the pilot test, and the original questionnaire was

implemented in the main survey as approved by the HKO.

All interviews in the pilot test were not included in the main survey.


2 May 2010

Main Survey

Before the main fieldwork was executed, a thorough briefing session was held on 16 April

2010 with enumerators and field work supervisor, in full consultation with HKO staff, to

address the requirements of the survey, principles of confidentiality, and to clarify any

misconception on common meteorological terminologies.

As detailed in the briefing session, a systematic random sampling method was deployed for

this survey. A random sample of households was systematically selected from the

telephone database maintained by Infogroup|ORC.

Using this method, each household in the population has a known and equal probability of

selection.

Once the household was selected and contacted, Kish Grid selection method was

adopted for the selection of the target respondent. In order to ensure the findings of this

survey are representative, only one interview (whether successful or not) has been

conducted in each sampled household.


3 May 2010

Summary of Survey Findings

Profile of Users

Of the 1 008 respondents interviewed, 54.5% of which were female; 45.5% were males.

The majority of the respondents were of age 40 – 59 (45.2%) and 20 – 39 (39.5%); the

youth (aged 15 – 19) and the elderly (aged 60 – 64) respondents accounted for 10.4% and

4.9%, respectively.

Analyzed by educational attainment, the proportions of respondents with tertiary or above

education level, secondary to matriculation education level, primary of below education

level were 28.5%, 59.7% and 11.4% respectively.

53.0% of respondents are engaged in full-time employment, just over 10% of the

respondents were unemployed (4.1%) or retired (6.5%), whilst more than 30% of the

respondents were homemakers (19.5%) and students (15.7%). 1.2% of respondents

refused to comment on their employment status.

(Ref.: Question 17 – 19)

Degree of concern about Weather information

The majority of respondents (99.8%) indicated that they usually read, watch or listen to

weather reports, suggesting that the general public is well aware of the weather information

available to them.

(Ref.: Question 1)

Channels to Access Weather Information

Of the channels to access weather information, most respondents (70.1%) obtain weather

information through television, as the primary channel, with the radio (25.5%) as the most

popular alternative channel.

In general, there was an increase in the use of the internet as a mean to access weather

information. More and more respondents (7.4%) were using the HKO's web site as the

primary channel to obtain weather information (against 5.9% in the previous wave).



4 May 2010

Opinions towards the Accuracy of Weather Forecasts

For the perceived accuracy of weather forecasts, 76.2% of respondents considered the

weather forecasts over the past several months to be accurate. Yet some 3% of

respondents asserted the contrary, slightly increased from previous waves (1.2% in April

2009, 1.5% in October 2009).

The perceived accuracy of weather forecasts, together with a comparison with the

corresponding figures from previous waves, is detailed below:

Respondents’ Opinions on the Accuracy of Weather Forecasts over the past Several Months

Level of Accuracy APR 2006

(%)

OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

Accurate 83.6 71.1 71.0 68.3 69.1 71.0 77.1 77.5 76.2

Average 15.9 25.0 25.3 27.8 20.8 23.0 21.3 20.4 20.7

Inaccurate 0.6 3.6 2.1 2.1 6.6 2.5 1.2 1.5 3.0

No comment - 0.2 1.7 1.9 3.5 3.5 0.3 0.6 0.1

Sample Size* 980 973 964 971 960 1021 993 1004 1006

* Number of Active Respondents.

(Ref.: Question 8)

On evaluation of the accuracy of weather forecasts over the past several months, 88.9% of

respondents gave a rating of 70% or higher, whereas only 5.2% of respondents rated

50% or lower.

The average percentage of perceived accuracy of weather forecasts was 78.2%, which is

comparable to corresponding figures in previous waves, as shown in the table below:

Mean Percentage of Weather Forecasts over the Past Several Months Considered Accurate by

Respondents

APR 2006

(%)

OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

Mean percentage 79.8 75.9 77.0 76.5 74.7 77.0 79.0 78.3 78.2

Remark: Sample size of each survey was different.

(Ref.: Question 9)


5 May 2010

When the accuracy of weather forecasts were further broken down into four aspects -

temperature forecast, fine/cloudy prediction, rainstorm forecast/warning and typhoon

prediction/warning over the past several months, most respondents (80.1% - 91.7%)

considered that the four aspects of weather forecasts were “accurate” or “somewhat

accurate”. However, the results indicated a slight decrease in the accuracy of weather

forecasts in those four aspects when compared with the figures from previous waves, as

given in the table below:

Respondents’ Opinions on the Accuracy Level of Different Aspects of Weather Forecasts

over the past Several Months


(%)

OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

Temperature forecasts

Accurate/Somewhat

Accurate 95.0 95.1 92.9 92.2 85.9 88.1 94.2 95.1 91.7

Inaccurate/Somewhat

Inaccurate 4.2 3.7 4.2 4.8 7.6 8.2 5.5 4.0 7.9

No comment 0.8 1.2 2.8 3.0 6.5 3.7 0.2 0.9 0.4

Fine / cloudy predictions

Accurate/Somewhat

Accurate 92.9 90.8 86.8 82.4 81.4 82.4 88.9 88.0 85.4

Inaccurate/Somewhat

Inaccurate 5.9 8.0 8.5 13.5 13.9 13.7 10.7 10.4 13.1

No comment 1.2 1.2 4.7 4.1 4.7 3.9 0.4 1.6 1.5

Rain storm forecasts / warning

Accurate/Somewhat

Accurate 88.7 77.6 75.1 72.5 69.2 76.3 85.6 87.8 80.1

Inaccurate/Somewhat

Inaccurate 9.1 20.5 19.0 23.5 24.5 20.4 13.8 11.4 14.8

No comment 2.5 2.0 5.9 4.0 6.4 3.2 0.6 0.8 5.1

Typhoon prediction / warning

Accurate/Somewhat

Accurate 90.1 73.0 65.2 71.7 67.7 80.4 88.9 91.7 82.9

Inaccurate/Somewhat

Inaccurate 3.7 25.6 17.2 24.4 23.7 17.0 9.7 7.7 9.1

No comment 6.2 1.4 17.5 3.9 8.6 2.6 1.3 0.6 8.1

Sample Size* 980 973 964 971 960 1021 993 1004 1006




6 May 2010

For the accuracy of weather forecasts in comparison with the past 3 to 4 years, 65.2% of

respondents considered the current weather forecasts more accurate, 25.4% of

respondents claimed the accuracy remained the same. Among the respondents, 6.3%

considered the accuracy has declined; an increase of 3.1% from previous wave.

Respondents’ Opinions on the Accuracy of Weather Forecasts Nowadays

as Compared with those of 3 to 4 years ago


(%)

OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

More accurate 70.1 50.4 60.5 59.7 54.5 63.2 65.4 67.1 65.2

About the same 26.5 40.1 30.9 30.1 31.4 25.8 29.5 26.9 25.4

Less accurate 1.4 7.5 3.9 5.8 6.8 3.2 3.8 3.2 6.3

Don’t know / No

comment 2.0 2.0 5.6 4.4 7.3 7.8 1.3 2.8 3.1

Sample Size* 980 973 964 971 960 1021 993 1004 1006


(Ref.: Question 14)


7 May 2010

Overall Satisfaction with the HKO’s Services

In terms of the overall satisfaction with the HKO’s services, most of the respondents (87.3%)

gave a rating of 7 or above, with mean score 7.8 which was comparable to corresponding

figures in previous waves:

Overall Satisfaction on the Services provided by the HKO over the Past Several Months (10-point

rating scale)

Level of Satisfaction OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

0 – 3 1.5 0.8 0.5 1.1 0.4 0.1 0.8 0.8

4 – 6 16.3 14.4 17.2 15.9 9.7 11.1 10.8 12.0

7 – 10 82.2 84.7 76.7 81.7 87.9 88.8 88.4 87.3

Don’t know < 0.05 0.1 -- 1.3 2.0 -- -- --

Mean Score 7.4 7.6 7.5 7.5 7.8 7.8 7.8 7.8

Sample Size* 973 964 971 960 1021 993 1004 1006


(Ref.: Question 15)

In terms of the opinions towards the tropical cyclone warning services, as compared with

the past few years, more than 90% of total respondents considered the services better or

about the same as before. Only 3.4% of respondents believed the services are worse than

before.

Respondents’ Opinions on the Tropical Cyclone Warning Services Nowadays



(%)

Better 61.2

About the same 31.3

Worse 3.4

Don’t know / No comment 4.1

Sample Size* 1006


(Ref.: Question 16)


8 May 2010

2 Background

The Hong Kong Observatory (HKO) is a government department to deliver meteorological

services to the public. One of its important roles is to forecast the weather of the coming

days and to issue warning signals during hazardous weather situations.

Since 1989, the department has commissioned independent market research agencies to

conduct public opinion survey on the accuracy of weather forecasts and warnings issued by

HKO at half-yearly interval. In 2010, two waves of survey are planned to conduct in April

and October respectively.

Opinion Research Corporation (ORC) is pleased to submit this report. This document

presents the objectives, research design, methodology, analysis, and survey findings for

HKO’s reference.


9 May 2010

3 Objectives

The objectives of the survey are:

To gauge the public’s opinions on the accuracy of the following aspects：

o Temperature forecast

o Fine / Cloudy prediction

o Rain storm forecasts / warning

o Typhoon prediction / warning

To track HKO’s performance as perceived by the general public; and

To identify the popular channels used by the general public to receive weather

information


10 May 2010

4 Methodology

4.1 Survey Coverage

The survey covered people living in Hong Kong aged between 15 and 64.

4.2 Research Design

The pilot test was conducted on 8 April 2010 to test for the feasibility of the questionnaire

before the commencement of the main fieldwork. Consequently, 30 interviews were

successfully conducted in the pilot test, with interviewing time in the range of 5 to 7 minutes.

No problematic area was identified during the pilot test, and the original questionnaire was

implemented in the main survey as approved by the HKO.

Main Survey

In order to ensure the findings from the survey are representative, systematic random

sampling method was employed. A random sample of household telephone numbers were

selected from the telephone database maintained by ORC. Within the selected household,

a target respondent aged 15 to 64 was randomly picked by means of the “Kish Grid”

random selection method. Only one successful interview was conducted in each sampled

household.

In total, 1 008 individuals were successfully enumerated during the fieldwork period from 16

April to 30 April 2010, constituting an overall response rate of 75.9%. The enumeration

results are presented below:

Count

(a) Total number of telephone numbers selected 1 620

(b) Non contact cases 83

(c) Invalid cases 292

Non-operating numbers, fax numbers, non-residential numbers, etc. 133

Without eligible respondents aged 15-64 159

(d) Refusal 239

(e) Successful interviews 1 008

Overall response rate = (e) / [(b) + (d) + (e)] x 100% 75.9%


11 May 2010

4.3 Questionnaire Design

In order to meet the objectives stated in Section 3 above, the questionnaire (see Appendix I)

comprised the following three major parts:

Channels to access weather information

Perceptions on the services provided by the HKO

Demographic questions on the respondents

4.4 Statistical Analysis and Presentation of Survey Results

The statistical software, SPSS for Windows version 13.0 was used to perform all statistical

analyses. Office Word 2007 was employed to construct charts and graphs. Frequency

tables and cross tabulations were produced for each survey response. Note that for tables

presented in this report, figures may not add up to totals due to rounding. Statistical tests,

including Chi-square test and Fisher's exact test, were performed to test the relationship

between two categorical variables. Kruskal Wallis test and Mann-Whitney U test were

applied to check for significant differences between groups. To examine the association

among any two ordinal/interval measurements, Spearman's rho test was used.

Respondents who did not usually read, watch or listen to weather reports were excluded

from all statistical analyses. In addition, respondents who refused to answer a particular

question were excluded from all significant tests on that question.


12 May 2010

5 Detailed Findings

5.1 Demographic Profiles of Respondents

Of the 1 008 respondents interviewed during the fieldwork period, females accounted for a

higher proportion as compared to males (54.5% vs. 45.5%). While about two-fifth or more of

the respondents were of age 40 – 59 (45.2%) and 20 – 39 (39.5%), the youth (aged 15 – 19)

and the elderly (aged 60 – 64) respondents accounted for a lower proportion of 10.4% and

4.9% respectively.

Regarding the educational attainment, about three-fifths (58.6%) of the respondents had

secondary/matriculation education level, 32.0% of the respondents had attained tertiary or

above education level and 18.7% had primary or below education level.

45.8% of the respondents were non-working, with closed to one-fifth (19.5%) being

homemakers and 15.7 % being students; 4.1% were jobseekers and 6.5% has retired.

Among those who were economically active, 27.7% of the respondents were clerical staff

and 20.1% were associate professionals. The proportion of respondent who worked as

service or sales staff, managers or administrators, self-employed, technical staff, or

non-technical staff were 13.7%, 10.6%, 10.3%, 10.1% and 5.1%, respectively.

When further asked about their working industry, 29.1% of the respondents were working in

the industry of Community, Social and Personal service; 21.1% of them were working in the

industry of Wholesales, Retail and Import / Export trades, Restaurants and Hotels and

17.8% were in the Financing, Insurance, Real Estate and Business Service sector. About

equal proportions of the working respondents were in the Transport, Storage and

Communication and Construction sectors (10.1% and 9.2% respectively).

Regarding the monthly personal income, more than 15% of the respondents indicated that

they had an income level of $4,000 - $9,999 (18.1%), $1 - $3,999 (17.4%) and $10,000 -

$14,999 (17%). About equal proportions of the respondent claimed that they belonged to

the monthly household income group of $20,000 - $29,999 (18.0%) and $12,500 - $19,999

(17.0%). 13.6% of them had a monthly household income of $30,000 - $39,999 and 10.3%

had $1 - $12,499.

(Ref.: Appendix III, Tables 17 - 23)


13 May 2010

5.2 Degree of Concern about Weather Information

The majority of respondents (99.8%) indicated that they usually read, watch or listen to

weather reports, suggesting that the general public is well aware of the weather information

available to them.

The degree of concern about weather information has never dropped below 94% for the

past decade, and stayed around 99% for the past three waves of public opinion survey.

(Ref.: Appendix II, Chart 3)

5.3 Channels to Access Weather Information

5.3.1 Popularity of channels to access weather information

The majority of the respondents obtain weather information through traditional media

channels, such as television (96.8%), radio (47.1%) and newspaper (25.5%).

Not surprisingly, more and more members of the general public were searching for weather

information on the web. Specifically, 23.1% of the respondents regularly obtain weather

information via the HKO’s website, 1.9% seek information on other weather websites,

while 27.3% look for the relevant details on web portal such as MSN, Yahoo! and Google.

Approximately half (49.1%) of the respondents indicated that they frequently make use of 3

channels to access weather information, with more than one-third (38.3%) making use of 2

channels. Only 12.6% of the respondents merely obtain information from a single channel.


14 May 2010

Chart 1: Channels used by the respondents to access weather information

7%

8%

12%

70%

12%

9%

26%

24%

16%

10%

3%

1%

<2%

<2%

11%

<5%

<8%

7%

5%

Friends/Relatives

Mobile Phones

PCCW's 18501/18503/18508

HK Observatory's Dial-a Weather

hotlines 1878200

Other weather websites

Observatory's website

Other websites' weather

information section

Newspaper

Radio

Television

1st channel 2nd channel 3rd channel

Sample size = 1 006

Television remained as the most popular first channel (70.1%), followed by radio and web

portal (11.5% and 7.8% respectively). Radio was the most popular secondary channel

(25.5%), closely followed by television (23.9%).

PCs were still the most common (85.6%) devices used when accessing weather

information on the internet, a decrease of 6.3% from previous wave, possibly due to the

increasing utilization of WAP phones, PDAs and other handheld devices in recent years.

The corresponding figures for WAP phones and PDAs are 4% and 1%, respectively, with

6.1% used both the PCs and WAP phones, 1.1% used both the PCs and PDAs, and 2.3%

used all three devices.

(Ref.: Chart 1 & Appendix II, Chart 4)


15 May 2010

Cross Tabulation Analysis

Although respondents with low education attainment were less likely to seek

information from the internet, there weren’t trends across the respondent groups based

on the gender, occupation or age demographic variables.

The awareness of weather information is higher for the working classes, who were also

more likely to utilize alternative channels to obtain weather information. For instance

technical people on average used 2.47 channels, against 2.12 channels for those who

have retired.


16 May 2010

5.4 Opinions towards the Accuracy of Weather Forecasts over the

Past Several Months

5.4.1 Overall accuracy level of weather forecasts

The general public was asked for their opinion whether the weather forecasts issued by

HKO over the period of 3 - 6 months immediately before this survey were accurate.

Although there was strong agreement among the respondents (76.2%) that the weather

forecasts were accurate, yet some 3% of respondents expressed an opposite opinion, a

slight increase from previous waves (1.2% in April 2009, 1.5% in October 2009). Just over

twenty percentages of respondents perceived the accuracy as average.

(Ref.: Table 1 & Appendix III, Table 11)

Table 1: Respondents’ Opinions on the Accuracy of Weather Forecasts over the past Several Months


(%)

OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

Accurate 83.6 71.1 71.0 68.3 69.1 71.0 77.1 77.5 76.2

Average 15.9 25.0 25.3 27.8 20.8 23.0 21.3 20.4 20.7

Inaccurate 0.6 3.6 2.1 2.1 6.6 2.5 1.2 1.5 3.0

No comment - 0.2 1.7 1.9 3.5 3.5 0.3 0.6 0.1

Sample Size* 980 973 964 971 960 1021 993 1004 1006



Respondents working in the Electricity, Gas and Water or Construction industries were

more likely to agree with the predictions of HKO.

Based on the Spearman’s rho correlation test, a positive correlation was observed between

age groups and the accuracy levels (p-value =0.000, r =0.217). However, a negative

correlation was observed between education attainments and the accuracy levels (p-value

=0.009, r = -0.083)


17 May 2010

5.4.2 Percentage of accurate weather forecasts

The general public was also asked to comment on the proportion of accurate weather

forecasts, expressed in percentage, issued by HKO over the same time period.

Close to ninety percent (88.9%) of the respondents reckoned that 70% or more of the

weather forecast were accurate. Only a low proportion of the respondents (5.2%) rated

50% or less of the forecast were correct.

The modal percentage score is 80%, with three hundreds and forty-three respondents

(34.3%) gave this rating; another 21.0% of respondents gave a score of 90%, indicating a

high level of accuracy as perceived by the public.

The mean percentage is effectively unchanged from previous wave (78.2% vs 78.3%).

(Ref.: Table 2, Appendix II, Chart 5 & Appendix III, Table 12)

Table 2: Mean Percentage of Weather Forecasts over the Past Several Months Considered Accurate

APR 2006

(%)

OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

Mean percentage 79.8 75.9 77.0 76.5 74.7 77.0 79.0 78.3 78.2



18 May 2010

5.4.3 Accuracy level of different aspects of weather forecasts

The general public was further asked about the accuracy of weather forecast services on

four aspects, viz. temperature forecast, fine/cloudy prediction, rainstorm forecast/warning

and typhoon prediction/warning.

More than ninety percent (91.7%) of respondents considered the temperature forecasts

were “accurate” or “somewhat accurate”. Eighty-five percent (85.4%) agreed that the

fine/cloudy predictions were “accurate” or “somewhat accurate”. The figures for rainstorm

forecast/warning and typhoon prediction/warning were 80.1% and 82.9%, respectively.

(Ref.: Chart 2 & Appendix III, Table 13)

Chart 2: Perception of accuracy level of four aspects of weather forecasts

46%

39%

39%

38%

37%

42%

46%

54%

14%

12%

7%

8% 8%

5%

2%

1%

Typhone prediction /

warning

Rain storm forecasts /

warning

Fine / Cloudy weather

forecasts

Temperature

Accurate Somewhat accurate Somewhat inaccurate Inaccurate Don't know / No comment

Sample size: All Active Respondents (1 006)


19 May 2010

The percentage of respondents who indicated that the forecasts in these four aspects were

“accurate” or “somewhat accurate” has decreased slightly when compared to previous

waves in 2009.

(Ref.: Table 3)

Table 3: Respondents’ Opinions on the Accuracy Level of Different Aspects of Weather Forecasts

over the past Several Months


(%)

OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

Temperature forecasts

Accurate/Somewhat

Accurate 95.0 95.1 92.9 92.2 85.9 88.1 94.2 95.1 91.7

Inaccurate/Somewhat

Inaccurate 4.2 3.7 4.2 4.8 7.6 8.2 5.5 4.0 7.9

No comment 0.8 1.2 2.8 3.0 6.5 3.7 0.2 0.9 0.4

Fine / cloudy predictions

Accurate/Somewhat

Accurate 92.9 90.8 86.8 82.4 81.4 82.4 88.9 88.0 85.4

Inaccurate/Somewhat

Inaccurate 5.9 8.0 8.5 13.5 13.9 13.7 10.7 10.4 13.1

No comment 1.2 1.2 4.7 4.1 4.7 3.9 0.4 1.6 1.5

Rain storm forecasts / warning

Accurate/Somewhat

Accurate 88.7 77.6 75.1 72.5 69.2 76.3 85.6 87.8 80.1

Inaccurate/Somewhat

Inaccurate 9.1 20.5 19.0 23.5 24.5 20.4 13.8 11.4 14.8

No comment 2.5 2.0 5.9 4.0 6.4 3.2 0.6 0.8 5.1

Typhoon prediction / warning

Accurate/Somewhat

Accurate 90.1 73.0 65.2 71.7 67.7 80.4 88.9 91.7 82.9

Inaccurate/Somewhat

Inaccurate 3.7 25.6 17.2 24.4 23.7 17.0 9.7 7.7 9.1

No comment 6.2 1.4 17.5 3.9 8.6 2.6 1.3 0.6 8.1

Sample Size* 980 973 964 971 960 1021 993 1004 1006



20 May 2010

5.5 Overall Satisfaction with the Hong Kong Observatory’s Services

over the Past Several Months

This measure examines the percentage of the general public who were satisfied with the

services provided by the HKO in the past 3 – 6 months immediately before this survey.

On a 10-point scale, with 0 represents "poor service" and 10 represents "excellent

service" the overall satisfaction level with the HKO’s services remained high over the

years. The mean score was 7.8, representing no deterioration since 2008.

Among the respondents, 87.3% gave a rating of 7 or above. The mode of this measure

was 8, with about two-fifth (38.2%) of respondents who gave this rating. Eighty-two

respondents (8.2%) gave HKO’s services a full mark.


Table 4: Overall Satisfaction on the Services provided by the HKO over the Past Several Months

(10-point rating scale)

Level of Satisfaction OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

0 – 3 1.5 0.8 0.5 1.1 0.4 0.1 0.8 0.8

4 – 6 16.3 14.4 17.2 15.9 9.7 11.1 10.8 12.0

7 – 10 82.2 84.7 76.7 81.7 87.9 88.8 88.4 87.3

Don’t know < 0.05 0.1 -- 1.3 2.0 -- -- --

Mean Score 7.4 7.6 7.5 7.5 7.8 7.8 7.8 7.8

Sample Size* 973 964 971 960 1021 993 1004 1006


(Ref.: Appendix II, Chart 11)


21 May 2010

5.6 Accuracy Level when Compared to 3 or 4 Years Ago

5.6.1 Comparison: Accuracy Level of Current Weather Forecasts

For the accuracy of weather forecasts in comparison with the past 3 to 4 years, 65.2% of

respondents reckoned that the current weather forecasts more accurate, 25.4% of

respondents claimed the accuracy remained the same. The rest (6.3%) considered the

accuracy has declined, slight increase of 3.1% from previous wave.

(Ref.: Table 5, Appendix II, Chart 10 & Appendix III, Table 14)

Table 5: Respondents’ Opinions on the Accuracy of Weather Forecasts Nowadays



(%)

OCT 2006

(%)

APR 2007

(%)

OCT 2007

(%)

APR 2008

(%)

OCT 2008

(%)

APR 2009

(%)

OCT 2009

(%)

APR 2010

(%)

More accurate 70.1 50.4 60.5 59.7 54.5 63.2 65.4 67.1 65.2

About the same 26.5 40.1 30.9 30.1 31.4 25.8 29.5 26.9 25.4

Less accurate 1.4 7.5 3.9 5.8 6.8 3.2 3.8 3.2 6.3

Don’t know / No

comment 2.0 2.0 5.6 4.4 7.3 7.8 1.3 2.8 3.1

Sample Size* 980 973 964 971 960 1021 993 1004 1006


Reviewing the data over the years, the accuracy levels of this measure seems to fluctuate

from one season to another, which reflects the perceived performance of the HKO over a

longer period carries strong seasonal variations.


22 May 2010

5.6.2 Comparison: Accuracy Level of Current Tropical Cyclone Warning Services

In respect of the opinions towards the tropical cyclone warning services, as compared with

the past few years, more than 90% of total respondents considered the services better or

about the same as before. Only 3.4% of respondents claimed the services are worse than

before.

Table 6: Respondents’ Opinions on the Tropical Cyclone Warning Services Nowadays



(%)

Better 61.2

About the same 31.3

Worse 3.4

Don’t know / No comment 4.1

Sample Size* 1006



This is a new question added in this wave, and therefore comparisons to previous years

were not available.


Based on the results of the Spearman’s rho test, there was no significant relationship

between monthly income and the perception of accuracy level of current tropical cyclone

warning services.

Regarding the Kruskal Wallis tests, the results showed that no significant variation of

perceived accuracy among working respondents in different occupation and industry. For

the non-working respondents, homemakers and retired persons were likely to consider the

tropical cyclone warning services to be accurate.

Significant relationships were also observed for age groups and education attainments

against the level of accuracy in this measure. Generally speaking; the higher the age group,

the higher is the perceived accuracy (p-value =0.000, r =0.241); and the higher the

education attainments, the lower is the perceived accuracy (p-value =0.000, r = -0.184)


23 May 2010

Appendix I: Questionnaire


24 May 2010

Public Opinion Survey on the Accuracy of Weather Forecasts 2010

Tel. Code：

Name of Respondent： Contact Tel. Number：

Interviewer ID： Interview Date：

Start Time of Interview： End Time of Interview：

Introduction:

Good morning/afternoon/evening, my name is _____________ and I am calling from ORC International, an

independent research firm. We have been commissioned by Hong Kong Observatory (HKO) to conduct an

opinion survey on the accuracy of weather forecasts in Hong Kong and would like to conduct a short interview

with you. The information you provide will be treated with strict confidence and will be used for aggregate

analysis only. Thank you for your cooperation.

Screening

We wish to invite one of your household members to conduct the interview by a random selection method.

May I know how many household members are aged 15 to 64 in your household? Who is the eldest? Then

who is the next eldest…? (Please exclude the live-in domestic helper)

(Selection of respondent: List all household members aged 15 to 64, from the eldest to the youngest.

Circle the last digit of the Tel. Code. Move along the column right under this digit, and circle the

corresponding figure on the row where the youngest household member belongs to. Then interview the

household member whose code number is same as the figure.)

Household members aged 15 to 64 Last digit of the Tel. Code

Code (from the eldest to the youngest) 1 2 3 4 5 6 7 8 9 0

1. 1 1 1 1 1 1 1 1 1 1

2. 2 1 2 1 2 1 2 1 2 1

3. 2 3 1 2 3 1 2 3 1 2

4. 3 4 1 2 3 4 1 2 3 4

5. 5 1 2 3 4 5 1 2 3 4

6. 5 6 1 2 3 4 5 6 1 2

7. 3 4 5 6 7 1 2 3 4 5

8. 6 7 8 1 2 3 4 5 6 7

9. 8 9 1 2 3 4 5 6 7 8

10. 9 10 1 2 3 4 5 6 7 8

According to the information you provided, we have randomly selected (the selected household member) for

the interview. Can I talk to him/her? (If the selected respondent is not available, arrange the interview for

another date and time.)

(If the selected respondent is not the one you first talked to, repeat the introduction; otherwise start with Q1)

RESTRICTED when entered with data

Accessible to authorized persons only


25 May 2010

Q1. Do you usually read, watch or listen to weather reports?

1. Yes

2. No -> Jump to Q17

Q2. From where do you usually obtain weather information of Hong Kong? Do you obtain from radio,

Television, newspaper, weather hotline, internet, pagers / mobile phones, or other sources? [SA]

[For “weather hotline”, probe: Is it Hong Kong Observatory’s Dial-a-Weather hotlines 1878-200, or

PCCW’s 18-501 and 18-503, 18-508?]

[For “internet”, probe: Is it Hong Kong Observatory’s website or other weather websites or other

websites’ weather information section?]

1. Radio -> Jump to Q4

2. Television -> Jump to Q4

3. Newspaper -> Jump to Q4

4. Hong Kong Observatory’s Dial-a-Weather hotlines 1878 200 -> Jump to Q4

5. PCCW’s 18 501 / 18 503 / 18 508 -> Jump to Q4

6. Observatory’s website

7. Other weather websites

8. Other websites’ weather information section (e.g. yahoo)

9. Mobile Phones -> Jump to Q4

10. Pagers -> Jump to Q4

11. Friends or relatives -> Jump to Q4

12. Other sources, please specify: -> Jump to Q4

Q3. As you mentioned, you obtain weather information from Internet. Did you use PC, WAP Mobile phone

or PDA to access internet for obtaining weather information? [MA]

1. Personal Computer (PC)

2. WAP phone

3. Personal Digital Assistant (PDA)

4. Others, please specify: _______________________

Q4. Any others (any other source for obtaining weather information of Hong Kong)? [SA]


PCCW’s 18-501 and 18-503, 18-508?]







5. PCCW’s 18 501 / 18 503 / 18 508 -> Jump to Q6








13. No more -> Jump to Q8

Main Questionnaire


26 May 2010




2. WAP phone


4. Others, please specify:____________________________

Q6. Any more (any other source for obtaining weather information of Hong Kong )? [SA]


PCCW’s 18-501 and 18-503, 18-508?]







5. PCCW’s 18 501 / 18 503 / 18 508 -> Jump to Q8








13. No more -> Jump to Q8




2. WAP phone


4. Others, please specify: ____________________________

Q8. Do you consider the weather forecasts of the Hong Kong Observatory over the past several months

very accurate, somewhat accurate, average, somewhat inaccurate or very inaccurate?

1. Very accurate

2. Somewhat accurate

3. Average

4. Somewhat inaccurate

5. Very inaccurate

6. Don’t know / No comment (Don’t mention)

Q9. What percentage of weather forecasts of the Hong Kong Observatory over the past several months do

you consider accurate?

1. ____________ per cent



27 May 2010

Do you consider the following aspects of weather forecasts of the Hong Kong Observatory over the past

several months accurate, somewhat accurate, somewhat inaccurate or inaccurate?

Accurate Somewhat

accurate

Somewhat

inaccurate Inaccurate

Don’t know /

No comment

(Don’t mention)

Q10. Temperature 1 2 3 4 5

Q11. Fine / Cloudy 1 2 3 4 5

Q12. Rain storm forecasts /

warning 1 2 3 4 5

Q13. Typhoon prediction /

warning 1 2 3 4 5

Q14. How do you compare weather forecasts nowadays with those 3 to 4 years ago? Is it more accurate,

less accurate or about the same?

1. More accurate

2. About the same

3. Less accurate


Q15. If you rate on a scale of 0 to 10, with “10” being “excellent service”, “5” the passing mark and “0” “poor

service”, how many marks will you give for the satisfaction level of the services provided by the Hong

Kong Observatory? ______________ Mark

Q16. How do you compare the tropical cyclone warning services provided by the Hong Kong Observatory

nowadays with those from the past 3 to 4 years ago? Is it better, worse or about the same?

1. Better

2. About the same

3. Worse


Personal Information

Finally, we would like to ask you some personal information. This information is collected for statistical

analysis only and will be kept confidential.

Q17. Which age group do you belong to?

1. 15-17

2. 18-19

3. 20-29

4. 30-39

5. 40-49

6. 50-59

7. 60-64

8. Refuse to answer


28 May 2010

Q18. What is your educational attainment?

1. No formal schooling/kindergarten

2. Primary

3. Junior secondary (Form 1 to Form 3)

4. Senior secondary (Form 4 to Form 5)/Springboard Project

5. Matriculation (Form 6 to Form 7)/Technical College

6. Tertiary (non-degree or associate degree)

7. Bachelor Degree

8. Master or Doctor Degree

9. Refuse to answer

Q19. What is your occupation? (If answer – no occupation, ask whether it belongs to 1, 2, 3, or 4)

1. Student -> Jump to Q21

2. Homemaker -> Jump to Q21

3. Job seeker / unemployed -> Jump to Q21

4. Retired -> Jump to Q21

5. Professionals or associate professionals

6. Managers or administrators

7. Clerical staff

8. Technical staff

9. Non-technical staff

10. Service or sales staff

11. Self-employed

12 Others, please specify: ____________________

13. Refuse to answer

Q20. Which of the industry are you engaged in?

1. Agriculture and Fishing

2. Mining and Quarrying

3. Manufacturing

4. Electricity, Gas and Water

5. Construction

6. Wholesale, Retail and Import/Export Trades, Restaurants and Hotels

7. Transport, Storage and Communication

8. Financing, Insurance, Real Estate and Business Services

9. Community, Social and Personal Services

10. Other, please specify:_____________________



29 May 2010

Q21. Which personal monthly income group do you belong to? (including salary, housekeeping money,

government subsidy, old age allowance, CSSA, etc)

1. No income

2. $1-3,999

3. $4,000-9,999

4. $10,000-14,999

5. $15,000-19,999

6. $20,000-29,999

7. $30,000-39,999

8. $40,000 or above

9. Refuse to answer

Q22. Which household monthly income group do you belong to? (including salary, housekeeping

money, government subsidy, old age allowance, CSSA, etc)

1. No income

2. $1-12,499

3. $12,500-19,999

4. $20,000-29,999

5. $30,000-39,999

6. $40,000-49,999

7. $50,000-59,999

8. $60,000-69,999

9. $70,000 or above


Q23. Gender

1. Male

2. Female

3. Refuse to answer

～ Thank you for your co-operation! ～

[Read out] Another staff of our company may contact you later to re-confirm the interview that I have done or

to clarify some other questions. He/she will ask a few questions only and will not disturb you for a long time.

Interviewer declaration

I hereby authenticate the data accuracy and integrity, and the interview was conducted by following the

guidelines maintained by the international standard of market research.

Signature: Date:


30 May 2010

Appendix II: Charts


31 May 2010

Chart 3: Overall Awareness of Weather Forecasts (April 99 – April 10)


Note: * denotes figure less than 0.5%.

100%100%99%96%94%97%96%97%98%97%97%95%96%97%97%97%96%96%96%98%97%98%98%

4%6%3%4%3%2%3%3%5%4%3%3%3%4%4%4%2%3%2%2% * *1%

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99

Aware Not aware


32 May 2010

Chart 4: Popularity of Channels Used to Access Weather Information (April 99 – April 10)


47

3841

44

48

39

47464546

42

4950

43

57

4648

53

49

5351

55

9793

9594939294

9696949494

96959595959595949696

94

26

212118

13

2118

21

25

211918

21

172020

22222020

26

1517

74

65456675

8567

978787677

53

546

4569

57

912

71110

16

11

1613

1612

17

2326

23

5

9111213

11888765444322

53 212122212

5433323111

27.3

12

22

56

1714

1816

5777

35544

1 21210000000000000001101 0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99

Pe

rce

nta

ge

(%

)

Radio TelevisionNewspaper HKO's Dial-a-Weather hotlinesPCCW's hotline HKO's WebsiteOther Weather websites Other Websites' weather information sectionMobile phones


33 May 2010

Chart 5: Mean Percentage of Accurate Weather Forecasts over the Past Several Months (April 99 – April 10)


74.7%

76.5%

77.0%

75.9%

79.8%

77.8%

79.7%

79.3%

77.5%

75.1%

75.7%

76.5%

77.7%

76.7%

77.0%

77.3%

77.4%

80.2%79.8%

77.7%

79.0%

78.3%

78.2%

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99


34 May 2010

Chart 6: Perceived Accuracy of Forecasts on Temperature over the Past Several Months (April 99 – April 10)


Note: * Less than 0.5%.

92%95%94%

88%86%92%93%95%95%

92%95%93%92%94%92%93%94%93%

84%91%

84%

95%93%

4%6%

8%7%

5%4%4%4%

6%4%

3%4%3%7%5%4%5%

11%

5%

7%

4%5%

4%7%

3%3%1%1%2%1%4%4%3%1%2%2%2%

5%4%9%

1%2%8%

* *1%

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99

Accurate Inaccurate Don't know


35 May 2010

Chart 7: Perceived Accuracy of Fine / Cloudy Weather Forecasts over the Past Several Months (April 99 – April 10)


Note: * Less than 0.5%.

85%88%89%82%81%82%

87%91%93%

90%93%

88%86%90%88%87%87%88%81%

84%79%

82%82%

13%10%11%

14%14%14%9%

8%6%8%

6%

7%6%8%11%11%

8%10%

14%10%

11%

16%15%

2%4%5%4%4%1%1%2%1%

5%5%2%1%2%

5%2%

5%6%10%

2%3% * 2%

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99



36 May 2010

Chart 8: Perceived Accuracy of Rainstorm Forecasts / Warning over the Past Several Months (April 99 – April 10)


80%

88%86%

76%69%

73%75%78%

88%86%89%

81%80%84%86%

71%

81%77%

80%81%81%77%75%

15%

11%14%

21%

25%24%19%

20%

9%12%7%

13%14%13%

13%

26%11%

21%14%14%11%

21%19%

1%3%6%4%6%

2%3%2%4%6%6%3%1%3%

9%2%

6%5%9%

2%6% 5%

1%

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99



37 May 2010

Chart 9: Perceived Accuracy of Typhoon Prediction / Warning over the Past Several Months (April 99 – April 10)


83%

92%89%

80%

68%72%

65%

73%

90%93%92%90%

86%

94%90%

86%

77%83%81%

86%80%

83%77%

9%

8%10%

17%

24%

24%

17%

26%

4%5%

3%6%

4%

5%8%

13%

7%

15%

7%

10%

4%

16%

7%

1%3%8%

4%

18%

1%6%

2%5%4%

10%

1%2%1%

16%

2%

12%

4%

16%

1%

16%

8%1%

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99



38 May 2010

Chart 10: Perceived Accuracy of Current Weather Forecasts as Compared with Those of 3 to 4 Years ago (April 99 – April 10)


65%67%65%63%

55%60%61%

50%

70%63%

70%67%

71%69%

59%55%

66%64%68%

71%76%

70%76%

25%27%30%

26%

31%

30%30%

40%

26%34%

27%27%

24%27%

37%

35%

29%29%

25%24%

19%26%

19%

6%4%

3%7%6%4%7%

1%2%2%

1%2%2%3%

6%2%4%4%1%1%

3%2%3%

8%7%4%5%3%3%1%1%5%3%3%1%4%3%3%3%4%4%1%3%

3%

3%1%

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99

More Accurate More or Less the Same Less Accurate No comment


39 May 2010

Chart 11: Satisfaction Level with Overall Services Provided by the HKO over the Past Several Months (April 99 – April 10)


7.67.67.87.87.87.8

7.57.57.67.4

7.97.7

8.08.08.07.97.7

7.57.87.77.87.87.8

0

1

2

3

4

5

6

7

8

9

10

Apr

10

Oct

09

Apr

09

Oct

08

Apr

08

Oct

07

Apr

07

Oct

06

Apr

06

Oct

05

Apr

05

Oct

04

Apr

04

Oct

03

Apr

03

Oct

02

Apr

02

Oct

01

Apr

01

Oct

00

Apr

00

Oct

99

Apr

99


40 May 2010

Appendix III: Frequency Tables of Survey Findings


41 May 2010

Table 7: Respondents’ habit on reading, watching or listening to weather reports (Q1)

Frequency Percent Valid Percent

Cumulative

Percent

Valid Yes 1006 99.8 99.8 99.8

No 2 0.2 0.2 100.0

Total 1008 100.0 100.0

Base: All respondents

Table 8: Channels used to access weather information (Q2, Q4 & Q6)

1st Channel 2nd Channel 3rd Channel Total

Count % Count % Count % Count %

Radio 116 11.5% 257 25.5% 101 10.0% 474 47.1%

Television 705 70.1% 240 23.9% 29 2.9% 974 96.8%

Newspaper 6 0.6% 86 8.5% 165 16.4% 257 25.5%

Hong Kong

Observatory’s

Dial-a-Weather

hotlines 1878 200

17 1.7% 26 2.6% 28 2.8% 71 7.1%

PCCW’s 18 501 / 18

503 / 18 508 5 0.5% 18 1.8% 26 2.6% 49 4.9%

Observatory’s

website 74 7.4% 111 11.0% 47 4.7% 232 23.1%

Other weather

websites 2 0.2% 11 1.1% 6 0.6% 19 1.9%

Other websites’

weather information

section (e.g. yahoo)

78 7.8% 123 12.2% 74 7.4% 275 27.3%

Mobile Phones 2 0.2% 7 0.7% 9 0.9% 18 1.8%

Friends or relatives 1 0.1% -- -- 9 0.9% 10 1.0%

No more -- -- 127 12.6% 512 50.9% -- --

Total 1006 100.0% 1006 100.0% 1006 100.0% 1006 100.0%

Base: All Active Respondents


42 May 2010

Table 9: Channels used to access weather information (Q3, Q5 & Q7)

Frequency Percent

PC 450 85.6

WAP phone 21 4.0

PDA 5 1.0

Both PC and WAP phone 32 6.1

Both PC and PDA 6 1.1

Both PC, WAP phone and PDA 12 2.3

Total 526 100.0%

Base: All respondents who access weather information through the Internet

Table 10: Number of channels used to access weather information (Q3, Q5 & Q7)


Cumulative

Percent

Valid 1 127 12.6 12.6 12.6

2 385 38.2 38.3 50.9

3 494 49.0 49.1 100.0

Total 1006 100.0 100.0


Table 11: Overall accuracy level on weather forecasts over the past several months (Q8)


Cumulative

Percent

Valid Very accurate 166 16.5 16.5 16.5

Somewhat accurate 601 59.7 59.7 76.2

Average 208 20.7 20.7 96.9

Somewhat inaccurate 25 2.5 2.5 99.4

Very inaccurate 5 0.5 0.5 99.9

Don't know / No comment 1 0.1 0.1 100.0

Total 1006 100.0 100.0



43 May 2010

Table 12: Percentage of accurate weather forecasts over the past several months (Q9)


Cumulative

Percent

Valid

10 2 0.2 0.2 0.2

20 1 0.1 0.1 0.3

30 6 0.6 0.6 0.9

35 1 0.1 0.1 1.0

40 10 1.0 1.0 2.0

45 1 0.1 0.1 2.1

50 31 3.1 3.1 5.2

55 2 0.2 0.2 5.4

60 53 5.3 5.3 10.7

65 4 0.4 0.4 11.1

70 177 17.7 17.7 28.8

75 47 4.7 4.7 33.5

76 1 0.1 0.1 33.6

78 1 0.1 0.1 33.7

80 343 34.3 34.3 68.0

85 51 5.1 5.1 73.1

89 2 0.2 0.2 73.3

90 210 21.0 21.0 94.3

93 1 0.1 0.1 94.4

95 30 3.0 3.0 97.4

96 2 0.2 0.2 97.6

97 3 0.3 0.3 97.9

98 8 0.8 0.8 98.7

99 3 0.3 0.3 99.0

100 10 1.0 1.0 100.0

Total 1006 100.0 100.0

Mean 78.2

Median 80.0

Standard deviation 12.4


Table 13: Perception of accurate weather forecasts over the past several months (Q10-Q13)

Temperature Fine / Cloudy Rain storm Typhoon

Count % Count % Count % Count %

Accurate 380 37.8% 392 39.6% 389 38.7% 463 46.0%

Somewhat accurate 543 54.0% 467 48.4% 417 41.5% 371 36.9%

Somewhat inaccurate 73 7.3% 119 9.9% 141 14.0% 83 8.3%

Inaccurate 6 0.6% 13 0.5% 8 0.8% 8 0.8%

Don't know / No

comment 4 0.4% 15 1.6% 51 5.1% 81 8.1.%

Total 1006 100.0% 1006 100.0% 1006 100.0% 1006 100.0%



44 May 2010

Table 14: Comparison between current weather forecasts with those 3 to 4 years ago (Q14)


Cumulative

Percent

Valid More accurate 656 65.2 65.2 65.2

About the same 256 25.4 25.4 90.7

Less accurate 63 6.3 6.3 96.9


Total 1006 100.0 100.0


Table 15: Satisfaction level on weather services provided by the Hong Kong Observatory over the past

several months (Q15)


Cumulative

Percent

Valid 0.00 1 0.1 0.1 0.1

1.00 1 0.1 0.1 0.2

2.00 3 0.3 0.3 0.5

3.00 3 0.3 0.3 0.8

4.00 3 0.3 0.3 1.1

5.00 61 6.1 6.1 7.2

6.00 56 5.6 5.6 12.7

7.00 230 22.9 22.9 35.6

8.00 384 38.2 38.2 73.8

9.00 182 18.2 18.2 91.8

10.00 82 8.1 8.1 100.0

Total 1006 100.0 100.0

Mean 7.76

Median 8.00

Standard deviation 1.34


Table 16: Comparison between current Tropical Cyclone Warning Services

with those 3 to 4 years ago (Q16)


Cumulative

Percent

Valid More accurate 616 61.2 61.2 61.2

About the same 315 31.3 31.3 92.9

Less accurate 34 3.4 3.4 95.9


Total 1006 100.0 100.0



45 May 2010

Table 17: Age group of the respondents (Q17)

Frequency Percent Valid Percent Cumulative Percent

Valid 15-17 67 6.6 6.6 6.8

18-19 38 3.8 3.8 10.4

20-29 176 17.5 17.5 27.9

30-39 222 22.0 22.0 49.9

40-49 264 26.2 26.2 76.1

50-59 192 19.0 19.0 95.1

60-64 49 4.9 4.9 100.0

Total 1008 100.0 100.0


Table 18: Education attainment of the respondents (Q18)


Cumulative

Percent

Valid No formal

schooling/kindergarten 7 0.7 0.7 0.7

Primary 81 8.0 8.0 8.7

Junior secondary (Form 1 to

Form 3) 106 10.5 10.5 19.2

Senior secondary (Form 4 to

Form 5)/Springboard Project 392 38.9 38.9 58.1

Matriculation (Form 6 to Form

7)/Technical College 93 9.2 9.2 67.4

Tertiary (non-degree or

associate degree) 108 10.7 10.7 78.1

Bachelor Degree 185 18.4 18.4 96.4

Master or Doctor Degree 29 2.9 2.9 99.3

Refuse to answer 7 0.7 0.7 100.0

Total 1008 100.0 100.0


Table 19: Occupation of the respondents (Q19)

Frequency Percent

Valid

Percent

Cumulative

Percent

Valid Student 158 15.7 15.7 15.7

Homemaker 197 19.5 19.5 35.2

Job seeker / unemployed 41 4.1 4.1 39.3

Retired 66 6.5 6.5 45.8

Professionals or associate professionals 110 10.9 10.9 56.7

Managers or administrators 58 5.8 5.8 62.5

Clerical staff 151 15.0 15.0 77.5

Technical staff 55 5.5 5.5 82.9

Non-technical staff 28 2.8 2.8 85.7

Service or sales staff 75 7.4 7.4 93.2

Self-employed 56 5.6 5.6 98.7


Total 1008 100.0 100.0



46 May 2010

Table 20: Industry of the respondents (Q20)


Cumulative

Percent

Valid Agriculture and Fishing 1 0.2 0.2 0.2

Manufacturing 39 7.1 7.1 7.3

Electricity, Gas and Water 7 1.3 1.3 8.6

Construction 50 9.2 9.2 17.8

Wholesale, Retail and

Import/Export Trades,

Restaurants and Hotels

115 21.1 21.1 38.8

Transport, Storage and

Communication 55 10.1 10.1 48.9

Financing, Insurance, Real

Estate and Business Services 97 17.8 17.8 66.7

Community, Social and

Personal Services 159 29.1 29.1 95.8


Total 546 100.0 100.0

Base: All working respondents

Table 21: Personal monthly income of the respondents (Q21)


Cumulative

Percent

Valid No income 87 8.6 8.6 8.6

$1-3,999 175 17.4 17.4 26.0

$4,000-9,999 182 18.1 18.1 44.0

$10,000-14,999 171 17.0 17.0 61.0

$15,000-19,999 113 11.2 11.2 72.2

$20,000-29,999 101 10.0 10.0 82.2

$30,000-39,999 42 4.2 4.2 86.4

$40,000 or above 51 5.1 5.1 91.5


Total 1008 100.0 100.0



47 May 2010

Table 22: Household monthly income of the respondents (Q22)


Cumulative

Percent

Valid No income 8 0.8 0.8 0.8

$1-12,499 104 10.3 10.3 11.1

$12,500-19,999 171 17.0 17.0 28.1

$20,000-29,999 181 18.0 18.0 46.0

$30,000-39,999 137 13.6 13.6 59.6

$40,000-49,999 91 9.0 9.0 68.7

$50,000-59,999 62 6.2 6.2 74.8

$60,000-69,999 13 1.3 1.3 76.1

$70,000 or above 60 6.0 6.0 82.0

Refuse to answer 181 18.0 18.0 100.0

Total 1008 100.0 100.0


Table 23: Gender of the respondents (Q23)

Frequency Percent Valid Percent Cumulative Percent

Valid Male 459 45.5 45.5 45.5

Female 549 54.5 54.5 100.0

Total 1008 100.0 100.0



48 May 2010

Appendix IV: Survey Data Analysis (Cross Tabulation

and Statistical Test Results)


49 May 2010

A4.1 Relationship between Respondents’ Demographics and Their Habit of

Reading, Watching or Listening to Weather Reports

Table 24: Relationship between respondents’ age and their habit of reading, watching or listening to

weather reports

Habit of reading, watching or listening to weather reports Total

Yes No

Count Row % Count Row % Count Row %

15-17 67 98.5% -- -- 67 100.0%

18-19 38 100.0% -- -- 38 100.0%

20-29 176 100.0% -- -- 176 100.0%

30-39 221 99.5% 1 0.5% 222 100.0%

40-49 263 99.6% 1 0.4% 264 100.0%

50-59 192 100.0% -- -- 192 100.0%

60-64 49 100.0% -- -- 49 100.0%

Total 1006 99.8.0% 1 0.2% 1005 100.0%

Fisher’s exact test: test statistic = 13.793, p-value = 0.032

Table 25: Relationship between respondents’ education attainment and their habit of reading,

watching or listening to weather reports

Habit of reading, watching or listening to weather

reports Total

Yes No


No formal

schooling/kindergarten 6 85.7% 1 14.3% 7 100.0%

Primary 81 100.0% -- -- 81 100.0%

Junior secondary

(Form 1 to Form 3) 106 100.0% -- -- 106 100.0%

Senior secondary

(Form 4 to Form

5)/Springboard Project

392 100.0% -- -- 392 100.0%

Matriculation (Form 6

to Form 7)/Technical

College

93 100.0% -- -- 93 100.0%

Tertiary (non-degree

or associate degree) 108 100.0% -- -- 108 100.0%

Bachelor Degree 184 99.5% 1 0.5% 185 100.0%

Master or Doctor

Degree 29 100.0% -- -- 29 100.0%

Total 999 99.8% 2 0.2% 1001 100.0%



50 May 2010

Table 26: Relationship between respondents’ employment status and their habit of reading, watching

or listening to weather reports


Yes No


Yes 532 99.8% 1 0.2% 533 100.0%

No 461 99.8% 1 0.2% 462 100.0%

Total 993 99.9% 2 0.2% 995 100.0%


Table 27: Relationship between respondents’ occupation and their habit of reading, watching or

listening to weather reports

Habit of reading, watching or listening to weather

reports Total

Yes No


Student 158 100.0% -- -- 158 100.0%

Homemaker 196 100.0% 1 0.5% 197 100.0%

Job seeker /

unemployed 41 100.0% -- -- 41 100.0%

Retired 66 100.0% -- -- 66 100.0%

Professionals or

associate

professionals

110 100.0% -- -- 110 100.0%

Managers or

administrators 58 100.0% -- -- 58 100.0%

Clerical staff 151 100.0% -- -- 151 100.0%

Technical staff 55 100.0% -- -- 55 100.0%

Non-technical staff 28 100.0% -- -- 28 100.0%

Service or sales staff 74 100.0% 1 1.3% 75 100.0%

Self-employed 56 100.0% -- -- 65 100.0%

Total 993 99.9% 2 0.2% 995 100.0%


Table 28: Relationship between respondents’ gender and their habit of reading, watching or listening

to weather reports


Yes No


Male 459 100.0% -- -- 459 100.0%

Female 547 99.6% 2 0.4% 549 100.0%

Total 1006 99.8% 2 0.2% 1008 100.0%



51 May 2010

A4.2 Relationship between Respondents’ Demographics and the Number of

Channels to access Weather Reports

Table 29: Relationship between respondents’ age and the number of channels used to access weather

reports

No. of Channels used

Age group Correlation Coefficient -.059

Sig. (2-tailed) .060

Count 1006

Spearman's rho test: r = -0.059, p-value = 0.060

Table 30: Relationship between respondents’ education attainment and the number of channels used

to access weather reports


Education attainment Correlation Coefficient .105(**)


Count 999

Spearman's rho test: r = 0.105, p-value = 0.001

** Correlation is significant at the 0.01 level (2-tailed).

Table 31: Relationship between respondents’ employment status and the number of channels used to

access weather reports

Employment status Count Mean Std. Deviation

No 461 2.0317 .73433

Yes 532 1.9442 .74153

Total 993 1.9859 .73903

Mann-Whitney U test: p-value = 0.062

Table 32: Relationship between non-working respondents’ occupation and the number of channels

used to access weather reports

Employment status Count Mean Std. Deviation Minimum Maximum

Student 158 2.3797 .66397 1.00 3.00

Homemaker 196 2.3265 .75482 1.00 3.00

Job seeker / unemployed 41 2.3659 .73335 1.00 3.00

Retired 66 2.1212 .83233 1.00 3.00

Total 461 2.3189 .73740 1.00 3.00

Kruskal Wallis test: test statistics = 11.478, p-value = 0.009


52 May 2010

Table 33: Relationship between working respondents’ occupation and the number of channels used to



Professionals or associate

professionals 110 2.4273 .62749 1.00 3.00

Managers or administrators 58 2.4310 .65191 1.00 3.00

Clerical staff 151 2.4106 .63531 1.00 3.00

Technical staff 55 2.4727 .63405 1.00 3.00

Non-technical staff 28 2.2500 .75154 1.00 3.00

Service or sales staff 74 2.3649 .71336 1.00 3.00

Self-employed 56 2.3929 .67900 1.00 3.00

Total 532 2.4060 .65570 1.00 3.00


Table 34: Relationship between working respondents’ industry and the number of channels used to


Industry Count Mean Std. Deviation Minimum Maximum

Agriculture and Fishing 1 3.0000 . 3.00 3.00

Manufacturing 39 2.3333 .66227 1.00 3.00

Electricity, Gas and Water 7 2.2857 .48795 2.00 3.00

Construction 50 2.5200 .61412 1.00 3.00




114 2.3246 .71017 1.00 3.00


Communication 55 2.4364 .66007 1.00 3.00


Estate and Business Services 97 2.4536 .61272 1.00 3.00


Personal Services 159 2.4088 .66764 1.00 3.00

Total 522 2.4061 .65848 1.00 3.00


Table 35: Relationship between respondents’ personal monthly income and the number of channels



Personal monthly income Correlation Coefficient .056


Count 921



53 May 2010

Table 36: Relationship between respondents’ household monthly income and the number of channels



Household monthly income Correlation Coefficient .102(**)


Count 826



Table 37: Relationship between respondents’ gender and the number of channels used to access

weather reports

Gender Count Mean Std. Deviation Minimum Maximum

Male 459 2.3508 .68440 1.00 3.00

Female 547 2.3766 .70636 1.00 3.00

Total 1006 2.3648 .69620 1.00 3.00



54 May 2010

A4.3 Relationship between Respondents’ Demographics and Their Perception of

Accuracy on Weather Forecasts over the Past Several Months

Table 38: Relationship between respondents’ age and their perception of accuracy on weather

forecasts over the past several months

Perception of accuracy on weather


Age group Correlation Coefficient .217(**)


Count 1005



Table 39: Relationship between respondents’ education attainment and their perception of accuracy

on weather forecasts over the past several months

Perception of accuracy on weather


Education attainment Correlation Coefficient -.083(**)


Count 998



Table 40: Relationship between respondents’ employment status and their perception of accuracy on

weather forecasts over the past several months


No 460 3.8652 .69490 Very inaccurate Very accurate

Yes 532 3.9248 .72225 Very inaccurate Very accurate

Total 992 3.8972 .70996 Very inaccurate Very accurate


Table 41: Relationship between non-working respondents’ occupation and their perception of

accuracy on weather forecasts over the past several months

Occupation Count Mean Std. Deviation Minimum Maximum

Student 157 3.7261 .70358 Very

inaccurate

Very

accurate

Homemaker 196 3.8878 .72157 Very

inaccurate

Very

accurate

Job seeker / unemployed 41 3.9024 .58330 Somewhat

inaccurate

Very

accurate

Retired 66 4.1061 .58517 Somewhat

inaccurate

Very

accurate

Total 460 3.8652 .69490 Very

inaccurate

Very

accurate



55 May 2010

Table 42: Relationship between working respondents’ occupation and their perception of accuracy on




professionals 110 3.9364 .68103

Very

inaccurate

Very

accurate

Managers or administrators 58 3.9310 .83481

Very

inaccurate

Very

accurate

Clerical staff 151 3.8543 .76068

Very

inaccurate

Very

accurate

Technical staff 55 3.9273 .71633

Somewhat

inaccurate

Very

accurate

Non-technical staff 28 3.9286 .60422 Average

Very

accurate

Service or sales staff 74 3.9054 .62305

Somewhat

inaccurate

Very

accurate

Self-employed 56 4.1071 .75507

Somewhat

inaccurate

Very

accurate

Total 532 3.9248 .72225

Very

inaccurate

Very

accurate


Table 43: Relationship between working respondents’ industry and their perception of accuracy on



Agriculture and Fishing 1 3.0000 . Average Average

Manufacturing 39 3.8462 .53991 Average

Very

accurate

Electricity, Gas and Water 7 4.1429 .69007 Average

Very

accurate

Construction 50 4.1000 .61445 Average

Very

accurate



Restaurants and

114 3.9649 .70309 Somewhat

inaccurate

Very

accurate


Communication 55 3.8364 .83364

Very

inaccurate

Very

accurate


Estate and Business Services 97 3.7938 .80284

Very

inaccurate

Very

accurate


Personal Services 159 3.9686 .69739

Somewhat

inaccurate

Very

accurate

Total 522 3.9253 .72000

Very

inaccurate

Very

accurate



56 May 2010

Table 44: Relationship between respondents’ personal monthly income and their perception of


Perception of accuracy on

weather forecasts over the

past several months

Personal monthly income Correlation Coefficient .094(**)


Count 920



Table 45: Relationship between respondents’ household monthly income and their perception of


Perception of accuracy on

weather forecasts over the

past several months

Household monthly income Correlation Coefficient .046(*)


Count 826


* Correlation is significant at the 0.05 level (2-tailed).

Table 46: Relationship between respondents’ gender and their perception of accuracy on weather



Male 458 3.9476 .69500 Very inaccurate Very accurate

Female 547 3.8483 .72173 Very inaccurate Very accurate

Total 1005 3.8935 .71105 Very inaccurate Very accurate



57 May 2010

A4.4 Relationship between Respondents’ Demographics and the Percentage of

Accurate Weather Forecasts over the Past Several Months

Table 47: Relationship between respondents’ age and the percentage of accurate weather forecasts

over the past several months

Percentage of accurate weather




Count 1001



Table 48: Relationship between respondents’ education attainment and the percentage of accurate






Count 994



Table 49: Relationship between respondents’ employment status and the percentage of accurate


Employment status N Mean Std. Deviation Minimum Maximum

No 458 78.0568 12.61642 10.00 100.00

Yes 530 78.3736 12.52929 5.00 100.00

Total 988 78.2267 12.56437 5.00 100.00


Table 50: Relationship between non-working respondents’ occupation and the percentage of accurate


Occupation N Mean Std. Deviation Minimum Maximum

Student 157 75.5605 13.58465 10.00 98.00

Homemaker 194 78.6392 12.68158 20.00 100.00

Job seeker / unemployed 41 79.0244 10.73659 30.00 90.00

Retired 66 81.6818 9.88730 50.00 100.00

Total 458 78.0568 12.61642 10.00 100.00



58 May 2010

Table 51: Relationship between working respondents’ occupation and the percentage of accurate


Occupation N Mean Std. Deviation Minimum Maximum


professionals 110 78.5182 10.42996 40.00 95.00

Managers or administrators 57 79.8596 11.72823 50.00 98.00

Clerical staff 151 77.2384 13.59201 10.00 100.00

Technical staff 55 77.8182 12.42621 40.00 95.00

Non-technical staff 28 81.3571 7.12956 70.00 98.00

Service or sales staff 73 77.7123 14.31926 5.00 100.00

Self-employed 56 79.5536 13.88252 30.00 100.00

Total 530 78.3736 12.52929 5.00 100.00


Table 52: Relationship between working respondents’ industry and the percentage of accurate




Manufacturing 39 79.4872 10.86974 40.00 100.00

Electricity, Gas and Water 7 85.0000 10.34408 70.00 99.00

Construction 50 81.2600 10.02000 50.00 100.00




113 77.9381 13.48695 5.00 99.00


Communication 55 75.6909 13.17809 40.00 98.00


Estate and Business Services 96 77.0833 13.15228 10.00 95.00


Personal Services 159 79.0881 12.03128 40.00 100.00

Total 520 78.3712 12.51907 5.00 100.00


Table 53: Relationship between respondents’ personal monthly income and the percentage of

accurate weather forecasts over the past several months





Count 916



59 May 2010

Table 54: Relationship between respondents’ household monthly income and the percentage of

accurate weather forecasts over the past several months



Household monthly income Correlation Coefficient .007


Count 821


Table 55: Relationship between respondents’ gender and the percentage of accurate weather



Male 458 78.2838 12.86209 5.00 100.00

Female 543 78.0368 12.35045 20.00 100.00

Total 1001 78.1499 12.58140 5.00 100.00



60 May 2010


Accuracy on Different Aspects of Weather Forecasts over the Past Several Months

Table 56: Relationship between respondents’ age and their perception of accuracy on different

aspects of weather forecasts over the past several months

Perception of accuracy on different aspects of weather forecasts



Age group Correlation Coefficient .164(**) .132(**) .118(**) .059

Sig. (2-tailed) .000 .000 .000 .073

Count 1002 991 995 925

Remark: Spearman's rho test


Table 57: Relationship between respondents’ education attainment and their perception of accuracy

on different aspects of weather forecasts over the past several months




Education

attainment

Correlation Coefficient -.049 -.083(**) -.054 -.067(**)

Sig. (2-tailed) .123 .009 .099 .042

Count 996 984 948 918



Table 58: Relationship between respondents’ employment status and their perception of accuracy on

different aspects of weather forecasts over the past several months

Employment status Count Mean Std. Deviation

Temperature No 460 3.2522 .61348

Yes 530 3.3283 .63137

Total 990 3.2929 .62397

Fine / Cloudy No 454 3.2533 .71235

Yes 524 3.2443 .71415

Total 978 3.2485 .71296

Rain storm No 434 3.2120 .74527

Yes 508 3.2717 .71406

Total 942 3.2442 .72882

Typhoon No 421 3.3848 .68602

Yes 491 3.4114 .68645

Total 912 3.3991 .68601


61 May 2010

Table 59: Relationship between non-working respondents’ occupation and their perception of

accuracy on different aspects of weather forecasts over the past several months

Occupation Count Mean Std. Deviation

Temperature Student 158 3.1203 .64203

Homemaker 196 3.3010 .57841

Job seeker / unemployed 41 3.1951 .67895

Retired 65 3.4615 .53259

Total 460 3.2522 .61348

Fine / Cloudy Student 153 3.1895 .76736

Homemaker 195 3.2564 .67036


Retired 66 3.4091 .70115

Total 454 3.2533 .71235

Rain storm Student 148 3.1081 .78363

Homemaker 187 3.1872 .73488


Retired 62 3.4516 .64471

Total 434 3.2120 .74527

Typhoon Student 143 3.3636 .70756

Homemaker 182 3.4011 .68818


Retired 61 3.3934 .58534

Total 421 3.3848 .68602


62 May 2010

Table 60: Relationship between working respondents’ occupation and their perception of accuracy on

different aspects of weather forecasts over the past several months

Occupation Count Mean Std. Deviation

Temperature Professionals or associate professionals 110 3.3273 .63692




Non-technical staff 28 3.2500 .58531



Total 530 3.3283 .63137

Fine / Cloudy

Professionals or associate professionals 108 3.3241 .62396







Total 524 3.2443 .71415

Rain storm Professionals or associate professionals 106 3.2358 .75026







Total 508 3.2717 .71406

Typhoon Professionals or associate professionals 102 3.4216 .63614







Total 491 3.4114 .68645


63 May 2010

Table 61: Relationship between respondents’ personal monthly income and their perception of





Personal

monthly

income

Correlation Coefficient .080(*) .023 .067(*) .033

Sig. (2-tailed) .015 .492 .047 .334

Count 919 922 875 849



Table 62: Relationship between respondents’ household monthly income and their perception of





Household

monthly

income

Correlation Coefficient -.010 -.023 .018 -.017

Sig. (2-tailed) .773 .516 .608 .647

Count 824 813 785 762


Table 63: Relationship between respondents’ gender and their perception of accuracy on different

aspects of weather forecasts over the past several months

Gender Count Mean Std. Deviation

Temperature Male 457 3.3239 .64900

Female 545 3.2697 .60231

Total 1002 3.2944 .62431

Fine / Cloudy Male 451 3.3038 .70771

Female 540 3.2037 .71246

Total 991 3.2492 .71169

Rain storm Male 442 3.2647 .73158

Female 513 3.2242 .72514

Total 955 3.2429 .72803

Typhoon Male 424 3.3868 .70889

Female 501 3.3992 .66657

Total 925 3.3935 .68595


64 May 2010

A4.6 Relationship between Respondents’ Demographics and Their Perception of Accuracy on Current Weather Forecasts as Compared with Those 3 to 4 Years ago

Table 64: Relationship between respondents’ age and Their Perception of Accuracy on Current

Weather Forecasts as Compared with Those 3 to 4 Years ago

Their Perception of Accuracy on Current Weather Forecasts as

Compared with Those 3 to 4 Years ago



Count 975



Table 65: Relationship between respondents’ education attainment and Their Perception of Accuracy

on Current Weather Forecasts as Compared with Those 3 to 4 Years ago

Their Perception of Accuracy on Current Weather

Forecasts as Compared with Those 3 to 4 Years ago



Count 969



Table 66: Relationship between respondents’ employment status and Their Perception of Accuracy on

Current Weather Forecasts as Compared with Those 3 to 4 Years ago


No 442 2.5814 .61273 Less accurate More accurate

Yes 521 2.6296 .60368 Less accurate More accurate

Total 963 2.6075 .60801 Less accurate More accurate


Table 67: Relationship between non-working respondents’ occupation and Their Perception of

Accuracy on Current Weather Forecasts as Compared with Those 3 to 4 Years ago

Occupation Count Mean

Std.

Deviation Minimum Maximum

Student 154 2.3766 .65756 Less accurate More accurate

Homemaker 183 2.6612 .59759 Less accurate More accurate

Job seeker / unemployed 40 2.6750 .57233 Less accurate More accurate

Retired 65 2.7846 .41429 Less accurate More accurate


Kruskal Wallis test: test statistics = 25.895 p-value = 0.000


65 May 2010

Table 68: Relationship between working respondents’ occupation and Their Perception of Accuracy

on Current Weather Forecasts as Compared with Those 3 to 4 Years ago



professionals 109 2.5321 .67452

Less

accurate

More

accurate

Managers or administrators 57 2.5965 .62277 Less

accurate

More

accurate

Clerical staff 145 2.6345 .58706 Less

accurate

More

accurate

Technical staff 53 2.6226 .62716 Less

accurate

More

accurate

Non-technical staff 28 2.8214 .39002 Less

accurate

More

accurate

Service or sales staff 73 2.6027 .63987 Less

accurate

More

accurate

Self-employed 56 2.7857 .45584 Less

accurate

More

accurate

Total 521 2.6296 .60368 Less

accurate

More

accurate


Table 69: Relationship between working respondents’ industry and Their Perception of Accuracy on

Current Weather Forecasts as Compared with Those 3 to 4 Years ago


Manufacturing 39 2.6923 .56911 Less

accurate

More

accurate

Electricity, Gas and Water 7 2.8571 .37796 About the

same

More

accurate

Construction 49 2.6327 .56620 Less

accurate

More

accurate




113 2.6637 .57648 Less

accurate

More

accurate


Communication 53 2.6604 .58650

Less

accurate

More

accurate


Estate and Business Services 94 2.5745 .66380

Less

accurate

More

accurate


Personal Services 156 2.5962 .63020

Less

accurate

More

accurate

Total 511 2.6282 .60610 Less

accurate

More

accurate



66 May 2010

Table 70: Relationship between respondents’ personal monthly income and Their Perception of


Their Perception of Accuracy on Current

Weather Forecasts as Compared with

Those 3 to 4 Years ago

Personal monthly income Correlation Coefficient .084(*)


Count 894



Table 71: Relationship between respondents’ household monthly income and Their Perception of


Their Perception of Accuracy on Current

Weather Forecasts as Compared with Those 3 to

4 Years ago

Household monthly income Correlation Coefficient -.007


Count 805


Table 72: Relationship between respondents’ gender and Their Perception of Accuracy on Current

Weather Forecasts as Compared with Those 3 to 4 Years ago


Male 449 2.6058 .57714 Less accurate More accurate

Female 526 2.6103 .63111 Less accurate More accurate




67 May 2010


Overall Satisfaction on Services provided by Hong Kong Observatory over the Past

Several Months

Table 73: Relationship between respondents’ age and Their Perception of Overall Satisfaction on

Services provided by Hong Kong Observatory over the Past Several Months

Perception of Overall Satisfaction on Services provided by

Hong Kong Observatory over the Past Several Months



Count 1005



Table 74: Relationship between respondents’ education attainment and Their Perception of Overall

Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months

Perception of Overall Satisfaction on Services provided by

Hong Kong Observatory over the Past Several Months



Count 998



Table 75: Relationship between respondents’ employment status and Their Perception of Overall



No 461 7.7440 1.33985 1.00 10.00

Yes 531 7.8079 1.28885 2.00 10.00

Total 992 7.7782 1.31252 1.00 10.00


Table 76: Relationship between non-working respondents’ occupation and Their Perception of Overall



Std.


Student 158 7.4114 1.33130 1.00 10.00

Homemaker 196 7.8673 1.37477 2.00 10.00

Job seeker / unemployed 41 7.7805 1.19399 5.00 10.00

Retired 66 8.1515 1.17986 4.00 10.00

Total 461 7.7440 1.33985 1.00 10.00



68 May 2010

Table 77: Relationship between working respondents’ occupation and Their Perception of Overall




professionals 110 7.8364 1.00938 5.00 10.00

Managers or administrators 58 7.7414 1.23630 4.00 10.00

Clerical staff 151 7.6821 1.27735 5.00 10.00

Technical staff 54 8.0926 1.13717 5.00 10.00

Non-technical staff 28 7.9286 1.46385 5.00 10.00

Service or sales staff 74 7.7297 1.48321 3.00 10.00

Self-employed 56 7.9286 1.60519 2.00 10.00

Total 531 7.8079 1.28885 2.00 10.00


Table 78: Relationship between working respondents’ industry and Their Perception of Overall




Manufacturing 38 7.9737 1.10250 5.00 10.00

Electricity, Gas and Water 7 8.0000 1.00000 7.00 10.00

Construction 50 8.0400 1.33951 5.00 10.00



Restaurants and

114 7.6842 1.41619 3.00 10.00


Communication 55 7.6909 1.21522 5.00 10.00


Estate and Business Services 97 7.7216 1.37494 2.00 10.00


Personal Services 159 7.8868 1.18525 5.00 10.00

Total 521 7.8138 1.28373 2.00 10.00



Overall Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months

Perception of Overall Satisfaction on Services

provided by Hong Kong Observatory over the Past

Several Months



Count 921



69 May 2010


Overall Satisfaction on Services provided by Hong Kong Observatory over the Past Several Months



Several Months

Household monthly income Correlation Coefficient -.009


Count 826

Spearman's rho test: r =- 0.009, p-value = 0.800

Table 81: Relationship between respondents’ gender and Their Perception of Overall Satisfaction on

Services provided by Hong Kong Observatory over the Past Several Months


Male 458 7.7686 1.28061 1.00 10.00

Female 547 7.7715 1.34684 2.00 10.00

Total 1005 7.7701 1.31642 1.00 10.00



70 May 2010


Accuracy on Current Tropical Cyclone Warning Services as Compared with Those 3

to 4 Years ago

Table 82: Relationship between respondents’ age and Their Perception of Accuracy on Current

Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago

Their Perception of Accuracy on Current Tropical Cyclone

Warning Services as Compared with Those 3 to 4 Years ago



Count 965



Table 83: Relationship between respondents’ education attainment and Their Perception of Accuracy

on Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago

Their Perception of Accuracy on Current Tropical Cyclone

Warning Services as Compared with Those 3 to 4 Years ago



Count 959



Table 84: Relationship between respondents’ employment status and Their Perception of Accuracy on

Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago


No 440 2.6182 .53116 Less accurate More accurate

Yes 514 2.5914 .57600 Less accurate More accurate



Table 85: Relationship between non-working respondents’ occupation and Their Perception of

Accuracy on Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago


Std.


Student 153 2.4444 .56065 Less accurate More accurate

Homemaker 182 2.7143 .48822 Less accurate More accurate

Job seeker / unemployed 40 2.5750 .54948 Less accurate More accurate

Retired 65 2.7846 .45043 Less accurate More accurate




71 May 2010

Table 86: Relationship between working respondents’ occupation and Their Perception of Accuracy

on Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago


Std.



professionals 105 2.5524 .60417 Less accurate More accurate

Managers or administrators 56 2.6071 .52841 Less accurate More accurate

Clerical staff 144 2.5347 .59028 Less accurate More accurate

Technical staff 55 2.6364 .58890 Less accurate More accurate

Non-technical staff 26 2.6154 .63730 Less accurate More accurate

Service or sales staff 74 2.6351 .56312 Less accurate More accurate

Self-employed 54 2.6852 .50746 Less accurate More accurate



Table 87: Relationship between working respondents’ industry and Their Perception of Accuracy on

Current Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago

Industry Count Mean

Std.


Manufacturing 38 2.5263 .64669 Less accurate More accurate

Electricity, Gas and Water 7 2.5714 .53452 About the same More accurate

Construction 50 2.6200 .53031 Less accurate More accurate



Restaurants and

109 2.5780 .59774 Less accurate More accurate


Communication 54 2.4815 .63664 Less accurate More accurate


Estate and Business Services 92 2.6087 .51262 Less accurate More accurate


Personal Services 154 2.6364 .56958 Less accurate More accurate







Several Months



Count 888



72 May 2010





Several Months

Household monthly income Correlation Coefficient .004


Count 796


Table 90: Relationship between respondents’ gender and Their Perception of Accuracy on Current

Tropical Cyclone Warning Services as Compared with Those 3 to 4 Years ago


Male 450 2.5778 .56193 Less accurate More accurate

Female 515 2.6252 .55210 Less accurate More accurate



Documents

Public Opinion Survey on the Accuracy of Weather Forecasts ...€¦ · Public Opinion Survey on the Accuracy of Weather Forecasts in Hong Kong 2010 - Report - Prepared for Prepared