Presentation skills: Making gender statistics meaningful Inter-Regional Workshop on the Production of Gender Statistics New Delhi, India 6-10 August 2007

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Presentation of gender statistics

 Goals:  Reach a wide audience  Highlight key gender issues  Facilitate comparisons between women and men  Encourage further analysis  Stimulate demand for more information

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Ways to present data

 Tables  Graphs  Charts  Maps

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Common Statistical Tables

Table 6-2. Population Aged 65 and Over, by Marital Status, Age, Sex, Race, and Hispanic Origin: 2003

(In percent)

Age, race, and Hispanic origin

65 and over………………………………….

Non-Hispanic White alone……………….

Black alone………………………………….

Asian alone……………………………….

Hispanic (of any race)……………………………..

65 to 74……………………………………...

Non-Hispanic White alone……………….

Black alone………………………………….

Asian alone……………………………….

Hispanic (of any race)……………………………..

75 to 84………...……………………………..

Non-Hispanic White alone……………….

Black alone………………………………….

Asian alone……………………………….

Hispanic (of any race)……………………………..

85 and over………………………………… Non-Hispanic White alone……………….

Black alone………………………………….

Asian alone……………………………….

Hispanic (of any race)……………………………..

Married, spouse present

Men Women 71.2

72.9

56.6

68.6

68.8

74.3

76.4

59.2

70.2

72.5

69.8

71.3

54.9

69.7

65.7

56.1

57.8

39.7

39.2

49.8

41.1

42.9

25.4

42.7

39.9

53.5

56.5

33.4

51.8

48.4

33.7

35.3

19.3

35.1

31.4

12.5

13.1

4.2

10.7

17.4

14.3

9.6

7.6

18.4

18.1

23.2

16.6

17.1

34.6

33.6

47.7

48.8

33.2

Widowed

Men 14.3

14.0

19.3

13.6

12.3

8.8

8.3

Reference population: These data refer to the civilian noninstitutionalized population.

Source: U.S. Census Bureau, Current Population Survey, Annual Social and Economic Supplement, 2003.

Women 44.3

44.0

50.8

39.7

39.5

29.4

28.8

36.2

27.1

25.9

53.3

52.3

62.7

53.7

53.5

78.3

77.8

87.2

75.5

74.2

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General rules for good presentation  Meaningful information  Unambiguous information  Convey message efficiently

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General rules for good presentation  Meaningful information  Identify key message  Choose appropriate indicator (counts, percent, rates, ratios)  Highlight key gender issues  Facilitate comparisons between women and men

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General rules for good presentation  Meaningful information  Unambiguous information  Include titles and headings  Include only relevant labels  Display scales  Include source

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General rules for good presentation  Meaningful information  Unambiguous information  Convey message efficiently  Convey one key finding or concept  Use simple display  Sort on most meaningful variable

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From ‘raw data’ to easily understood gender statistics

 To select tables, graphs and maps  Identify gender issue or differences  Consider underlying causes  Identify analysis needed  Prepare raw/basic data  Determine appropriate presentation formats

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Basic table for gender analysis

Title A B C Total

Source…

N Women % 100 N Men % Sex distribution %W %M 100

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Example: Tanzania

 Gender issue: Poverty  Cause: Differential access to means of economic support  Analysis: Economic situation of women and men  Economic activity status  Reasons for not being economically active  Data sources: labour force surveys or population census

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Raw Data Population ages 10 and over by economic activity status and reasons for not economically active

Economically Active Not economically active of which Housework Student Too old Sick Disabled Others Total Women 5,674,626 2,327,291 366,997 1,399,348 211,826 238,224 37,317 73,579 8,001,917 Men 5,620,301 1,978,022 142,350 1,512,705 90,376 139,630 41,309 51,660 7,598,323 Total 11,294,927 4,305,313 509,347 2,912,053 302,202 377,854 78,626 125,239 15,600,240 Source: The Labour Force Survey, 1990/91. Tanzania.

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Basic Table 1 Population ages 10 and over by economic activity status

Numbers in 1,000's, percentage distribution and sex distribution (%)

Status Women Men Sex distribution Number Percent Number Percent Women Men Economically Active Not economically active 5,675 2,327 71 29 5,620 1,978 74 26 50 54 50 46 Total 8,002 100 7,598 100 51 49 Source: The Labour Force Survey, 1990/91. Tanzania.

One message: economic activity Exact numbers rounded to 1,000, percentages to integers

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Simplified Table 1 Population ages 10 and over by economic activity status

Numbers in 1,000's, percentage distribution and sex distribution (%)

Status Percentage Distribution Sex distribution Economically Active Not economically active Total, per cent numbers in 1,000's Women 71 29 100 8,002 Men 74 26 100 7,598 Women 50 54 51 Men 50 46 49 Source: The Labour Force Survey, 1990/91. Tanzania.

Deleted column with numbers, added totals in 1,000’s

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Basic Table 2 Population not economically active ages 10 and over by reasons

Reason Housework Student Too old Sick Disabled Others Total Women Number Percent 367 16 1,399 212 238 37 74 2,327 60 9 10 2 3 100 Men Number Percent 142 7 1,513 90 140 41 52 76 5 7 2 3 1,978 Source: The Labour Force Survey, 1990/91. Tanzania.

100 Sex distribution Women 72 48 70 63 48 59 Men 28 52 30 37 52 41 54 46

One message: Reasons for not being economically active Exact numbers rounded to 1,000, percentages to integers

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Simplified Table 2 Population not economically active ages 10 and over by reasons

Reason Housework Student Too old Sick Disabled Others Total, per cent numbers in 1,000's Percentage distribution Women 16 60 9 10 2 3 100 2,327 Men 7 76 5 7 2 3 100 1,978 Source : The Labour Force Surve y, 1990/91. Tanzania.

Sex distribution Women 72 48 70 63 48 59 54 Men 28 52 30 37 52 41 46

Deleted column with numbers, added totals in 1,000’s

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Simplified Table 2: Highlights gender issue Population not economically active ages 10 and over by reasons

Reason Housework Too old Sick Others Student Disabled Total, per cent numbers in 1,000's Percentage distribution Women 16 9 10 3 60 2 100 2,327 Men 7 5 7 3 76 2 100 1,978 Source : The Labour Force Surve y, 1990/91. Tanzania.

Sex distribution Women 72 70 63 59 48 48 54 Men 28 30 37 41 52 52 46

Reasons sorted after percentage of women in group

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Chart can help visualize

Population not economically active ages 10 and over by reasons Disabled Others Too old Sick Housew ork Student 0

Men Women

20 40 Per cent 60 80 18

Selecting an appropriate format



Tables

 Graphs  Charts  Maps

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When to use tables

 Lists –one variable  Incomplete data  Data that vary greatly in magnitude  Multiple statistics (annex tables)

A significant proportion of women are in polygynous unions in many countries of sub-Saharan Africa

Percentage of currently married women 15-49 who are in polygynous unions, 1992/1998

Sub-Saharan Africa %

Burkina Faso Benin Guinea Senegal Mali Togo Nigeria Chad Liberia Niger Cote d'Ivoire Cameroon Uganda Central African Republic United Republic of Tanzania Ghana Mozambique Comoros 51 50 50 46 44 43 41 39 38 38 37 33 30 29 29 28 27 25

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User-friendly tables

 Round-off numbers  Round-off percentages  Delete counts and total  Sort by most meaningful variable  Highlight key values  Title with clear message

More than one fourth of women heads of household are aged 60 or over

Percentage of household heads aged 60+, 1985/1997

Region

W M

Europe Asia Other developed regions Latin America Caribbean Africa

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32 31 26 24 26

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22 17 20 18

Source: The World's Women 2000: Trends and Statistics

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User-friendly tables: Clear titles

More than one fourth of women heads of household are aged 60 or over

Percentage of household heads aged 60+, 1985/1997

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Example 1: Good table?

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Example 2: Good table?

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Example 2: Good table?

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Selecting an appropriate format

 Tables 

Graphs

 Charts  Maps

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When to use graphs

 For continuous, interval variables  Show trends or changes

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User-friendly graphs

 Accurately show facts  Y axis should start at zero  Use same scale when comparing graphs side by side  Colours or patterns show differences  Title and minimal labels provide clear message

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Example 1: show facts

70 60 50 40 30 Literacy rate 100 90 80 10-14

A. Literacy rate by age in Vietnam 1989

15-19 20-24 25-29 30-34 Women Men 35-39 40-44 45-49 50-54 55-59 60 and above Age Group

Source: Women and Men in Vietnam. Statistical Publishing House, Vietnam 1995.

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Example 1: show facts

Literacy rate 100 90 80 70 60 50 40 30 20 10 0 10-14

B. Literacy rate by age in Vietnam 1989

15-19 20-24 25-29 30-34 Women 35-39 40-44 45-49 Men 50-54 55-59 60 and above Age Group

Source: Women and Men in Vietnam. Statistical Publishing House, Vietnam 1995.

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Example 2: Same Scale

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Selecting an appropriate format

 Tables  Graphs 

Charts

 Maps

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When to use charts

 For categorical variables  Ordinal  Nominal

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User-friendly charts

 Accurately show facts  Avoid unnecessary three dimensional charts that can distort the information  Colours or patterns to show differences  Title and minimal labels  Minimal lines, usually only horizontal grid  Minimal frames (only for scatter charts)

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User-friendly charts

Reasons why women work or stay at home, US 1978-1999

40 30 20 10 0 1999 1978 1978 1999 Homemaker Full-time job

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User-friendly charts

Women are increasingly working out of necessity, US 1978-1999

(percent of all women) 40 30 20 1978 1999 10 0 Necessity Satisfaction Homemaker Necessity Satisfaction Full-time job

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Picking the right chart

 Makes difference between strong message and confusion  Choice depends on:  Kind of data used in analysis  Key point to be emphasized

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Example: Picking the right chart

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Example: Picking the right chart

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Example: Picking the right chart

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Example: Picking the right chart

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Picking the right chart: Vertical bar charts  Data that do not vary in magnitude too greatly  Few data points  Few categories  Often used for:  Rates, percentages, ratios  Regional variations

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Example: Vertical bar chart

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Example: Vertical bar chart

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Example: Vertical bar chart

Both charts have a clear message. The choice depends on the desired emphasis

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Picking the right chart: Stacked bar charts  Most effective for categories adding to 100 percent  Women and men are shown either as:  X-axis with one stacked bar for each  Different colour segments of each bar with multiple values on the x-axis

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Example: stacked bar charts

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Example 2

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Picking the right chart: Horizontal bar charts  For one variable with many categories  When Y-axis labels are long  To plot two variables against each other

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Example 1: Horizontal bar charts

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Example 1: Horizontal bar charts

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Example 1: Horizontal bar charts

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Example 1: Horizontal bar charts

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Example 2: Horizontal bar charts

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Picking the right chart: Pie charts  To show distribution of categorical components of a single variable  Always show shares that total to 100 per cent  Best for showing one segment as percentage of the whole  Men and women can be shown either as:  Two segments of the pie  Separate pies

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Example: Pie charts

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Picking the right chart: Scatter plots  To show grouping around a trend line  To show outliers  To show many data points

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Example: Scatter Plots

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Picking the right chart: Box plots  To plot the median and quartiles  To compare distribution of one variable for two or more groups or time points  To compare single cases to the overall distribution

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Example: Box plots

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Example: Box plots

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Key points to remember

 Presentation of gender statistics involves analysis to highlight key message  Choosing the right presentation format is key for clear and accurate interpretation of data  Format chosen should present meaningful and unambiguous information efficiently

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Exercise

 Using labour market segregation exercise, do the following:  Identify key gender issue(s)  Determine key message(s) to be highlighted  Prepare basic tabulation table(s)  Choose appropriate presentation format(s)  Present the results using the chosen format(s)  Draft title  Include needed headings, labels, scales, sources  Draft a short paragraph explaining key message(s)

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Acknowledgements

 Statistics Sweden

Engendering Statistics: A Tool for Change

 United Nations Statistics Division

Handbook for Producing National Statistical Reports on Women and Men

 UNECE/WBI

Regional Training of Trainers Workshop on Gender Sensitization of NSS

 UNESCO

Gender sensitive education statistics and indicators: A practical guide

 Gary Klass (Illinois State University)

Presenting Data: Tabular and graphic display of social indicators

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