Bba 2001 Statistics

8/12/2019 Bba 2001 Statistics

1/16

Page 0of 16

BBA 2001

STATISTICS

TAN WAH TIONG

940928-14-5531

201565

CHONG KAR YUN

JUNE 2013


2/16

Page 1of 16

NO DETAIL PAGE

1.0 Contents 1

2.0 Introduction 2

3.0 Task 1 3

4.0 Task 2 4

5.0 Task 3 5

6.0 Task 4 6-8

7.0 Task 5 9

8.0 Task 6 10

9.0 References 11

10.0 Coursework 12-15


3/16

Page 2of 16

2.0 Introduction to statistics

By the 18th century, the term "statistics"designated thesystematic collection of

demographic andeconomic data by states. In the early 19th century, the meaning of

"statistics" broadened to include the discipline concerned with the collection, summary, and

analysis of data. Today statistics is widely employed in government, business, and all the

sciences. Electroniccomputers have expeditedstatistical computation,and have allowed

statisticians to develop "computer-intensive" methods.

The term "mathematical statistics" designates the mathematical theories ofprobability and

statistical inference,which are used instatistical practice.The relation between statistics and

probability theory developed rather late, however. In the 19th century, statistics increasingly

usedprobability theory,whose initial results were found in the 17th and 18th centuries,

particularly in the analysis ofgames of chance (gambling). By 1800, astronomy used

probability models and statistical theories, particularly themethod of least squares,which

was invented byLegendre andGauss.Early probability theory and statistics was

systematized and extended byLaplace;following Laplace, probability and statistics have

been in continual development. In the 19th century, statistical reasoning and probability

models were used by social scientists to advance the new sciences ofexperimental

psychology andsociology,and by physical scientists inthermodynamics andstatistical

mechanics.The development of statistical reasoning was closely associated with the

development ofinductive logic and thescientific method.Statistics can be regarded as not a

field ofmathematicsbut an autonomousmathematical science,likecomputer science and

operations research.
http://en.wikipedia.org/wiki/Statisticshttp://en.wikipedia.org/wiki/Official_statisticshttp://en.wikipedia.org/wiki/Demographichttp://en.wikipedia.org/wiki/Economicshttp://en.wikipedia.org/wiki/Computerhttp://en.wikipedia.org/wiki/Computational_statisticshttp://en.wikipedia.org/wiki/Mathematical_statisticshttp://en.wikipedia.org/wiki/Probability_theoryhttp://en.wikipedia.org/wiki/Statistical_inferencehttp://en.wikipedia.org/wiki/Applied_statisticshttp://en.wikipedia.org/wiki/Probability_theoryhttp://en.wikipedia.org/wiki/Games_of_chancehttp://en.wikipedia.org/wiki/Method_of_least_squareshttp://en.wikipedia.org/wiki/Adrien-Marie_Legendrehttp://en.wikipedia.org/wiki/Gausshttp://en.wikipedia.org/wiki/Laplacehttp://en.wikipedia.org/wiki/Experimental_psychologyhttp://en.wikipedia.org/wiki/Experimental_psychologyhttp://en.wikipedia.org/wiki/Sociologyhttp://en.wikipedia.org/wiki/Thermodynamicshttp://en.wikipedia.org/wiki/Statistical_mechanicshttp://en.wikipedia.org/wiki/Statistical_mechanicshttp://en.wikipedia.org/wiki/Inductive_logichttp://en.wikipedia.org/wiki/Scientific_methodhttp://en.wikipedia.org/wiki/Mathematicshttp://en.wikipedia.org/wiki/Mathematical_sciencehttp://en.wikipedia.org/wiki/Computer_sciencehttp://en.wikipedia.org/wiki/Operations_researchhttp://en.wikipedia.org/wiki/Operations_researchhttp://en.wikipedia.org/wiki/Computer_sciencehttp://en.wikipedia.org/wiki/Mathematical_sciencehttp://en.wikipedia.org/wiki/Mathematicshttp://en.wikipedia.org/wiki/Scientific_methodhttp://en.wikipedia.org/wiki/Inductive_logichttp://en.wikipedia.org/wiki/Statistical_mechanicshttp://en.wikipedia.org/wiki/Statistical_mechanicshttp://en.wikipedia.org/wiki/Thermodynamicshttp://en.wikipedia.org/wiki/Sociologyhttp://en.wikipedia.org/wiki/Experimental_psychologyhttp://en.wikipedia.org/wiki/Experimental_psychologyhttp://en.wikipedia.org/wiki/Laplacehttp://en.wikipedia.org/wiki/Gausshttp://en.wikipedia.org/wiki/Adrien-Marie_Legendrehttp://en.wikipedia.org/wiki/Method_of_least_squareshttp://en.wikipedia.org/wiki/Games_of_chancehttp://en.wikipedia.org/wiki/Probability_theoryhttp://en.wikipedia.org/wiki/Applied_statisticshttp://en.wikipedia.org/wiki/Statistical_inferencehttp://en.wikipedia.org/wiki/Probability_theoryhttp://en.wikipedia.org/wiki/Mathematical_statisticshttp://en.wikipedia.org/wiki/Computational_statisticshttp://en.wikipedia.org/wiki/Computerhttp://en.wikipedia.org/wiki/Economicshttp://en.wikipedia.org/wiki/Demographichttp://en.wikipedia.org/wiki/Official_statisticshttp://en.wikipedia.org/wiki/Statistics


4/16

Page 3of 16

3.0 Task 1

3.1 method of payment

Area Pass Cash Total

South 29,000 34,000 63,000

West 51,000 114,000 165,000

East 35,000 43,000 78,000

North 43,000 81,000 124,000

Total 158,000 272,000 430,000

3.2 Plot a component bar chart, with bars for each city area, to represent the data.

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

NumberofPassengers

Area

Cash

Pass


5/16

Page 4of 16

4.0 Task 2

The audience figures for the 26 programmers in a TV series (in millions) are:

4.0 3.8 4.2 2.9 2.5 3.5 2.6 3.6 5.0 3.5 4.9 2.9 3.3

4.8 1.0 3.2 5.1 2.4 3.7 4.2 3.5 3.8 3.6 2.3 3.9 2.1

Produce a stem and leaf display for this set of data.

Stem Leaves

1 0

2 1 3 4 5 6 9 9

3 2 3 5 5 5 6 6 7 8 8 9

4 0 2 2 8 9

5 0 1

Leaf unit = 0.1million


6/16

Page 5of 16

5.0 Task 3

Number of employee of a computer games company over nine years.

Time series chart

0

100

200

300

400

500

600

1992 1993 1994 1995 1996 1997 1998 1999 2000

Number

OfEmployees

Years

Employees

Employees

Year 1992 1993 1994 1995 1996 1997 1998 1999 2000

Employees 7 15 38 112 149 371 371 508 422


7/16

Page 6of 16

6.0 Task 4

Two independent estate agencies each employ 9 people. The number of years experience in

the property sector that employees of these companies have is

Agency A 0 4 4 5 7 8 10 11 15

Agency B 0 0 4 4 7 10 10 14 15

5.1 Range and Histograms for each set of data

Range A = 150

Range B = 150

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

0 4 5 7 8 10 11 14 15

Agency B

Agency A


8/16

Page 7of 16

5.2 Mean and the standard deviation of the data

Agency A

Mean = = 7.11

Experience Mean 20 7.11 - 7.11 50.55

4 7.11 - 3.11 9.67

4 7.11 - 3.11 9.67

5 7.11 - 2.11 4.45

7 7.11 - 0.11 0.01

8 7.11 0.89 0.79

10 7.11 2.89 8.35

11 7.11 3.89 15.13

15 7.11 7.89 62.2521 2 = 160.87Agency B

Mean = = 7.11

Experience Mean 20 7.11 - 7.11 50.55

0 7.11 - 7.11 50.55

4 7.11 - 3.11 9.67

4 7.11 - 3.11 9.67

7 7.11 - 0.11 0.01

10 7.11 2.89 8.35

10 7.11 2.89 8.35

14 7.11 6.89 47.47

15 7.11 7.89 62.2521

2

= 246.87


9/16

Page 8of 16

Standard deviation of Agency A

S=

=

= 4.48 (2 d.p)

Standard deviation of Agency B

S= =

= 5.56 (2 d.p)

The mean of Agency A and Agency B is same, but standard deviation of Agency B (5.56) is

higher than Agency A (4.48).


10/16

Page 9of 16

7.0 Task 5

The kilocalories per portion in 32 different breakfast cereals were recorded and collated into

the following grouped frequency distribution:

Kcal per portion Frequency

80 and under 120 3

120 and under 160 11

160 and under 200 9

200 and under 240 7

240 and under 280 2

Mean and median of the distributions.

Class Midpoint Frequency 80 a.u. 120 100 3 300

120 a.u. 160 140 11 1540

160 a.u. 200 180 9 1620

200 a.u. 240 220 7 1540

240 a.u. 280 260 2 520

Mean = Median = L+(

= = 160 + ( ) 40

= 172.5 = 168.89

The mean and median are close. This distribution is fairly symmetrical.


11/16

Page 10of 16

8.0 Task 6

Use of statistics in everyday life.

Statistics are used in various ways in our everyday life. For instance food packaging uses

statistics. Other functions like weather forecasts also use statistics.

Besides, Statistics also deal with frequency distribution. It is used to compare two or

more frequency distribution taken from different population to see if there are any

differences between them. The statistics uses the following measures for the comparison.

They are mean, median and mode. Mean is the average of all the observations whereas the

median is the middle most value of the observations and mode has the maximum frequencies.

Use of mean in daily life is to see the average mark of the class obtained. This average

helps to see how many students are above average, how many are average students and how

many are below averages. The teacher tries to help the average and below average students

to score more grades in future. In a factory, the mean of the wages helps the authorities

to know if the workers' welfare is maintained. It also helps to compare the salaries of the

employees of the different companies. In sales, the average sales in the district helps the

sales manager to plan for increasing the sales in the future.

The government takes the average income and expense of the citizens to know whether

the citizen rights are maintained. The family finds the average of their expenses to balance

their finance. The average production of agricultural commodities, the industrial goods, the

average exports and imports help the country to see their developments.

As the conclusion, statistics is the basis for almost all the activities of individuals, group,

society, community and country.


12/16

Page 11of 16

9.0 Reference

-www.google.com

-http://wiki.answers.com/Q/The_use_of_statistics_in_daily_life

-http://www.ask.com/question/how-do-we-use-statistics-in-everyday-life

-http://www.studymode.com/essays/Use-Of-Statistics-In-Daily-Life-395475.html

- http://en.wikipedia.org/wiki/History_of_statistics
http://www.google.com/http://wiki.answers.com/Q/The_use_of_statistics_in_daily_lifehttp://www.ask.com/question/how-do-we-use-statistics-in-everyday-lifehttp://www.studymode.com/essays/Use-Of-Statistics-In-Daily-Life-395475.htmlhttp://www.studymode.com/essays/Use-Of-Statistics-In-Daily-Life-395475.htmlhttp://www.ask.com/question/how-do-we-use-statistics-in-everyday-lifehttp://wiki.answers.com/Q/The_use_of_statistics_in_daily_lifehttp://www.google.com/


13/16

Page 12of 16

10.0 Coursework

Step one: Identifying the problem or opportunity

A manager must understand clearly and define correctly the problem at hand. He must be

careful not to confuse the actual problems that the management is trying to solve and the

symptoms. However, sometime one can use symptoms as clues to find the actual problem.

For example, the monthly sales of Proton cars have been declining significantly for

the past 24 months even though the overall auto industry has shown steady growth. The

management is trying to identify the actual causes or factors that had contributed to the

problem of declining local car sales so that corrective action can be taken immediately.

Failing to find the actual causes might result in the local auto industry having to slow

down, and hence, reduced sales and lower profits. The objective is to determine the factors

that contributed to the decline in demand for Proton cars. The actual problem is unknown

while the symptoms are a decline in sales, high cancellation of bookings and slow growth of

new bookings.

Step two: Gathering available facts

Data and information that are related to the actual problem must be gathered.

Internal data can be obtained from the departments within an organisation. For

example, accounting and financial data can be obtained from the financial and accounting

departments, production figures are obtainable from the production department and sales

data can be obtained from the marketing and sales department. The customer service

department and human resource department also provide useful data for analysis.


14/16

Page 13of 16

External data can be obtained from other organisations such as the Ministry of

domestic Trade and Consumer Affairs, Bank Negara, the Ministry of International Trade and

other business organisations. Other Sources include the Journal of Auto industry, the Journal

of Malaysian Business, Newspapers and magazines.

Step three: Gathering new data

If the available data are inadequate to get a clear picture of the problem, the management

may decide to collect new data. Sometimes, data on important variables are not available

from secondary sources or the data obtained from these sources are already outdated or not

suitable for use. As such, the management must obtain data from primary sources.

Appropriate data collection methods must be applied so that the data are gathered

accurately. For example, the management may want to collect data on customers

expectation on certain characteristics of passenger cars such as the safety standard, design,

performance, price, after-sales service, resale value and rate of financing.

At the same times, the management may also require information regarding the

marketing strategy of competitors such as advertisement and promotional strategies, package

offer, incentive for trade-in, or switching incentive. Several data collection methods can be

applied. They are direct observation, personal interview, telephone interview (especially for

long distance respondents), direct questionnaires, mailed questionnaires and focus group

study.

Before primary data is obtained, the manager must determine the representative

sample to be used for the research. In choosing the sample, the researcher must apply

appropriate sampling techniques so that the sample selected represent the population and


15/16

Page 14of 16

results in inaccurate information for decision-making. Any analysis on the based data is not

valid. The sampling technique used depends on the nature of the target population, the

budget available and also the objective of the study. Among the sampling techniques

available are simple random samplings, systematic sampling, stratified sampling, duster

sampling, quote sampling, judgmental sampling and snowball sampling.

Step four: Classifying and organising the data

After the required data have been collected, the next task is to make the data more

meaningful, readable and understandable in the context of the problem being investigated.

Raw data are meaningless. They must be transformed into meaningful form.

Step five: Presenting and analysing data

Data must be presented in useful and meaningful ways so that they are useful for decision-

makers and the people reading the report. Some of the common methods of presenting data

are through frequency tables, bar charts, graphs, histograms, frequency polygons, ogives and

stem-and-leaf plots.

Frequency tables are used to summarise data based on variables of interest. For

example, Proton customers can be grouped according to demographic variables such as

income level, education level, ethnic group and type of job, so that useful information on

demand can be obtained and analysed. Data presentation through charts, graph, scatter plots

and other visualised methods helps in identifying the relationship between variables of

interest

For example, a manager of a local car company may to determine the relationship

between the demand for local cars and demographic variable such as gender, education level,


16/16

Page 15of 16

income level and social classes. At the same time, he may be interested to establish the

relationship of these variables with the choice of models, price, and quality of service and

product performance. If we want to get more thorough information, the data need to be

further analysed. Among the methods of data analyses are cross tabulation, chi-square test,

regression analysis and time series analysis.

Step six: Making a decision

After going through data presentation, data analysis ad interpretation of the results, the

management should have a clear idea of the problem at hand. Certain variables may

influence some other variables. The management can list down the possible alternative

action to take under various economic conditions, and other influential conditions such as

change in interest rate, change in consumers lifestyles and developments in technology.

With appropriate statistical analyses techniques and models, the management can

make the right decision-marking under uncertainty and decision-marking under risk. This is

followed by the implementation of the plan. Appropriate corrective action should be carried

out in cases where deviation from the plan occurs.

Documents

Bba 2001 Statistics