Writing the results, discussion & using graphics & visuals in research reports Communication Research Week 7

Writing the results, discussion & using graphics & visuals in research reports

Communication Research

Week 7

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Results

Purpose of this section is to present a summary of the results and comment on the significance of the data

Graphics are used in this section to present the full findings

Text should highlight the most important results and help the reader interpret them

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Results

For each piece of important information, a three (3) step process is useful: A statement which locates the figures or

findings eg as shown in Fig 1, the trend … Statements which present the most important

findings Comments by the author on these findings

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Results/comments

May do the following Generalise from specific results to general trends

in populations Explain the possible reasons or causes of such

results Compare the results with results of other studies

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Discussion section

Makes reference to the main purpose and/or hypothesis Reviews the most significant findings and whether or not

they agree or disagree with the original hypothesis Explains/speculates about findings outlined or described

in “Results” section Compares findings/outcomes with related studies

already cited in literature review Outlines limitations of the study and the extent to which

findings can really be generalised Makes recommendations for further research

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Difficulties with presenting & interpreting probability informationfrom Berry (2004)

“Fifty percent of the public doesn’t actually know what 50% means” (UK Secretary of State for Trade and Industry, 2002)

A German study asked people: What does 40% mean”

1 in 4 4 out of every 10 Every 40th person

Over a third of a sample of 1000 Germans tested did not select the correct answer (Gigerenzer, 2002, 23 cited in Berry, 2004, 5)

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Presenting probabilities as frequencies

Gigerenzer (2002) argues that some of the misinterpretation by even experienced and educated readers can be overcome by using frequencies eg

The probability that a woman of age 40 has breast cancer is about 1 percent. If she has breast cancer, the probability that she tests positive on a screening mammogram is 90 percent. If she does not have breast cancer, the probability that she nevertheless tests positive is 9 percent. What are the chances that a woman who tests positive actually has breast cancer? (Gigerenzer, 2002, 41 cited in Berry, 2004, 32)

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Presenting probabilities as frequencies Most people surveyed found the above problem

confusing and believed the answer is 90 percent. Read the same problem expressed using natural frequencies:

Think of 100 women. One has breast cancer, and she will probably test positive. Of the 99 who do not have breast cancer, 9 will also test positive.Thus a total of 10 women will test positive. How many of those who test positive actually have breast cancer? (Gigerenzer, 2002, 42)

People found it easier to see that only one woman out of every ten tests positive will actually have cancer – that is, the probability is 10% not 90%

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Interpretation can be affected by

Verbal expressions used eg ‘likely’, ‘rare’ Context – knowledge, experience, framing of info Different numerical formats eg

Yamagishi (1997) presented people with two different statements about a certain type of cancer and asked them which they judged to be more risky

Kills 1286 out of 10,000 people Kills 24.14 out of 100 people.

The first statement was judged more risky even though the level of risk described in the second is twice as high

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Why is understanding how visuals communicate important?

Our culture places much emphasis on the visual – seeing is believing

Visual communication is faster and more easily processed

Visuals and graphics add another layer of meaning and another way of communicating

Visuals actively engage the brain in interpretation, making it more likely that readers will rememberthe information

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How do graphics & visuals enhance & supplement a report?

Make points vivid and help readers “see” data Present information more compactly than

words Convey/ simplify complex data Demonstrate contrasts/ comparisons Suggest movements/ trends over time Emphasise physical appearance

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How do graphics & visuals enhance & supplement a report?

Analyse concepts/ processes/ abstract relationships

Should not replace text Should be properly incorporated and

referenced eg ‘ … as shown in figure 1 …’ Different graphics serve different purposes –

choose the right visual for the story and the data

Ensure each visual is accurate and ethical

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All visuals share certain conventions

Identify an analytic perspective for the data with an interpretative title

Clearly describe the type of data (survey or projection)

Label the units (e.g. slices in a pie chart) Label the axes and use a legend List the source of the data or acknowledge the

source of the visual (if copied) Integrate into text with table/ figure numbers

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What’s wrong with this graphic?

Has there been a growth in the number of bananas between 1960 and 1980?

Or have the bananas grown increased in size?

Source: Sadler & Tucker, 1981, 116

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Line graphs Indicate movements over

time, compare frequency, identify correlations

Inappropriate labels and scales can make them difficult to interpret

Q :What is the difference between these two graphs?

Source: Sadler & Tucker, 1981, 116

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Line graphs Put time on the

horizontal axis Avoid more than 3 or 4

lines Use only 2 lines if they

cross a lot Use different colours

and a legend Label the axes Avoid perspective

Extra Staff in East Increased Sales in 3rd Q

0

10

20

30

40

50

60

70

80

90

100

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

Millions

EastWestNorth

Source: Gould www.rpi.edu/~goulde/co_su02/viscom.ppt

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Poor example

0

20

40

60

80

100


EastWest

North

EastWestNorth


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Column or vertical bar graph Compare items, show distributions or

highlight correlations Different bar charts for different

purposes Grouped (compare aspects of

each item across time Segmented, subdivided or stacked

(helps compare totals but cannot compare segments

Deviation (identify opposites) Paired (show correlation between

two items) Difficult for the eye to interpret size

and proportionsSource: Eunson, 1995, 79

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Grouped bar charts allow comparison


0102030405060708090

100

East West North

Millions

1st Qtr2nd Qtr3rd Qtr4th Qtr


20

Segmented, subdivided, stacked bar charts show different relationships


0% 20% 40% 60% 80% 100%

East

West

North

1st Qtr2nd Qtr3rd Qtr4th Qtr


21

Deviation bar charts show exceptions1998 Sales Relative to 1997

-8

-6

-4

-2

0

2

4

6

8

10

12


Percent Increase/ Decrease

EastWestNorth


22

Bar chart design Use a logical order

Chronological By region

Put bars close enough for comparison Label both axes and make increments

consistent Make all bars the same width Use colours for coding (not just “to look good”) Avoid “chart junk” – especially 3D views

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Chart junk


020406080

100

1stQtr

2ndQtr

3rdQtr

4thQtr

East

North

EastWestNorth

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Pie charts Show relative proportions and

the importance of each part to the whole

Label segments and proportions outside the pie

Limit segments to 5-7 Can be difficult to judge area

and size differences therefore should not be used to exactly compare segments

Source: Eunson, 1995, 78

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Good exampleNorth Region Leads 1st Q Sales

45.9million

30. 6 miliion

20.4 million

EastWestNorth

Source: www.rpi.edu/~goulde/co_su02/viscom.ppt]

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Poor exampleNorth Region Leads 1st Q Sales

10.2

12.6

25.3

15.6

20.415.7

EastNortheastNorthCentral

WestIsland


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Tables

Offer clear comprehensive detail Allow comparison between large amounts of

data Make readers focus on the raw data not your

interpretation of the data How you set out the table can affect

interpretation Difficult to read quickly Hard to recognise relationships

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Even tables can tell different stories – compare …

Florida Alaska New York CitySpring 23 m 2 m 10 mSummer 10 m 13 m 12.5 mFall 13.3 m 3 m 12.5 mWinter 49 m 2 m 15.5 mTotal 95.3 m 20 m 50.5 m

Spring Summer Fall WinterFlorida 25% 10% 15% 50%Alaska 10% 65% 15% 10%New York City 20% 25% 25% 30%


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Summary of charts

Use charts to simplify data Pick an appropriate style – bar charts are most

common for business audiences Provide an interpretative title – you want your

readers to understand the data in a way that supports your arguments, not theirs

Avoid “chart junk”

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Visual Ethics in Accident Reporting

(from Dragga & Voss, 2003)

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Bibliography & further readingBerry, D.(2004) Risk, Communication and Health Psychology UK, Open

University Press

Dragga, S. & Voss, D. (2003) Hiding Humanity: Verbal and Visual Ethics in Accident Reports Technical Communication Vol 50, No 1, Feb 2003 pp.61-82

Dragga, S. & Voss, D. (2001) Cruel Pies: The Inhumanity of Technical Illustrations Technical Communication Vol 48, No 3, Aug 2001 pp.265-274

Eunson, B. (1995) Writing and Presenting Reports Melbourne, John Wiley

Gould, E (2002) www.rpi.edu/~goulde/co_su02/viscom.ppt [accessed May 20, 2003]

Mohan, T., McGregor, H., Saunders, S., & Archee, R. (2004) Communicating as Professionals Melbourne, Thomson

Sadler, R.K & Tucker, K (1981) Common Ground: A Course in Communication Melbourne, Macmillan

Documents

Writing the results, discussion & using graphics & visuals in research reports Communication Research Week 7