Presentation skills: Making
gender statistics meaningful
Inter-Regional Workshop on the Production
of Gender Statistics
New Delhi, India 6-10 August 2007
1
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
2
Ways to present data
 Tables
 Graphs
 Charts
 Maps
3
Common Statistical Tables
Table 6-2. Population Aged 65 and Over, by Marital Status, Age, Sex, Race, and Hispanic Origin: 2003
(In percent)
Married, spouse present
Widowed
Age, race, and Hispanic origin
Men
Women
Men
65 and over………………………………….
71.2
41.1
14.3
Non-Hispanic White alone……………….
72.9
42.9
14.0
Black alone………………………………….
56.6
25.4
19.3
Asian alone……………………………….
68.6
42.7
13.6
Hispanic (of any race)……………………………..
68.8
39.9
12.3
65 to 74……………………………………...
74.3
53.5
8.8
Non-Hispanic White alone……………….
76.4
56.5
8.3
Black alone………………………………….
59.2
33.4
14.3
Asian alone……………………………….
70.2
51.8
9.6
Hispanic (of any race)……………………………..
72.5
48.4
7.6
75 to 84………...……………………………..
69.8
33.7
18.4
Non-Hispanic White alone……………….
71.3
35.3
18.1
Black alone………………………………….
54.9
19.3
23.2
Asian alone……………………………….
69.7
35.1
16.6
Hispanic (of any race)……………………………..
65.7
31.4
17.1
85 and over…………………………………
56.1
12.5
34.6
Non-Hispanic White alone……………….
57.8
13.1
33.6
Black alone………………………………….
39.7
4.2
47.7
Asian alone……………………………….
39.2
10.7
48.8
Hispanic (of any race)……………………………..
49.8
17.4
33.2
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
4
General rules for good presentation

Meaningful information

Unambiguous information

Convey message efficiently
5
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
6
General rules for good presentation

Meaningful information

Unambiguous information
 Include
titles and headings
 Include
only relevant labels
 Display
scales
 Include
source
7
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
8
From ‘raw data’ to easily
understood gender statistics

To select tables, graphs and maps
 Identify
gender issue or differences
 Consider
 Identify
underlying causes
analysis needed
 Prepare
raw/basic data
 Determine
appropriate presentation formats
9
Basic table for gender analysis
Title
Women
N
%
Men
N
Sex distribution
%
%W
%M
A
B
C
Total
100
100
Source…
10
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
11
Raw Data
Population ages 10 and over by economic activity status
and reasons for not economically active
Women
Men
Total
Economically Active
5,674,626
5,620,301
11,294,927
Not economically active
2,327,291
1,978,022
4,305,313
366,997
142,350
509,347
Student
1,399,348
1,512,705
2,912,053
Too old
211,826
90,376
302,202
Sick
238,224
139,630
377,854
Disabled
37,317
41,309
78,626
Others
73,579
51,660
125,239
8,001,917
7,598,323
15,600,240
of which Housework
Total
Source: The Labour Force Survey, 1990/91. Tanzania.
12
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
5,675
71
5,620
74
50
50
Not economically active
2,327
29
1,978
26
54
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
13
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
Women
Men
Women
Economically Active
71
74
50
50
Not economically active
29
26
54
46
100
100
51
49
8,002
7,598
Total, per cent
numbers in 1,000's
Men
Source: The Labour Force Survey, 1990/91. Tanzania.
Deleted column with numbers, added totals in 1,000’s
14
Basic Table 2
Population not economically active ages 10 and over by
reasons
Reason
Housework
Women
Men
Sex distribution
Number Percent
Number Percent
Women
Men
367
16
142
7
72
28
Student
1,399
60
1,513
76
48
52
Too old
212
9
90
5
70
30
Sick
238
10
140
7
63
37
Disabled
37
2
41
2
48
52
Others
74
3
52
3
59
41
2,327
100
1,978
100
54
46
Total
Source: The Labour Force Survey, 1990/91. Tanzania.
One message: Reasons for not being economically active
Exact numbers rounded to 1,000, percentages to integers
15
Simplified Table 2
Population not economically active ages 10 and over by
reasons
Reason
Percentage distribution
Women
Men
Housework
16
Student
Too old
Sex distribution
Women
Men
7
72
28
60
76
48
52
9
5
70
30
10
7
63
37
Disabled
2
2
48
52
Others
3
3
59
41
100
100
54
46
2,327
1,978
Sick
Total, per cent
numbers in 1,000's
Source: The Labour Force Survey, 1990/91. Tanzania.
Deleted column with numbers, added totals in 1,000’s
16
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
Men
16
Sex distribution
Women
Men
7
72
28
9
5
70
30
10
7
63
37
3
3
59
41
60
76
48
52
2
2
48
52
100
100
54
46
2,327
1,978
Source: The Labour Force Survey, 1990/91. Tanzania.
Reasons sorted after percentage of women in group
17
Chart can help visualize
Population not economically active
ages 10 and over by reasons
Disabled
Others
Too old
Sick
Housew ork
Student
20
0
Men
Women
40
60
80
Per cent
18
Selecting an appropriate format
Tables
 Graphs
 Charts
 Maps
19
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
20
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
M
W
Region
Europe
Asia
Other developed regions
Latin America
Caribbean
Africa
46
34
32
31
26
24
26
16
22
17
20
18
Source: The World's Women 2000: Trends and
Statistics
21
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
22
Example 1:
Good table?
23
Example 2: Good table?
24
Example 2: Good table?
25
Selecting an appropriate format
 Tables
Graphs
 Charts
 Maps
26
When to use graphs

For continuous, interval
variables

Show trends or changes
27
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
28
Example 1: show facts
Literacy rate
A. Literacy rate by age in Vietnam 1989
100
90
Men
80
Women
70
60
50
40
30
10-14
15-19
20-24
25-29
30-34
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.
29
Example 1: show facts
Literacy rate
B. Literacy rate by age in Vietnam 1989
100
90
Men
80
Women
70
60
50
40
30
20
10
0
10-14
15-19
20-24
25-29
30-34
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.
30
Example 2:
Same Scale
31
Selecting an appropriate format
 Tables
 Graphs
Charts
 Maps
32
When to use charts

For categorical variables
 Ordinal
 Nominal
33
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)
34
User-friendly charts
Homemaker
Satisfaction
Necessity
1999
1978
Satisfaction
40
30
20
10
0
Necessity
Percent of
all women
Reasons why women work or stay at home, US
1978-1999
1978
1999
Full-time job
35
User-friendly charts
40
Women are increasingly working out of
necessity, US 1978-1999
(percent of all women)
1978
30
1999
20
10
0
Necessity
Satisfaction
Homemaker
Necessity
Satisfaction
Full-time job
36
Picking the right chart

Makes difference between strong message and
confusion

Choice depends on:
 Kind
 Key
of data used in analysis
point to be emphasized
37
Example: Picking the right chart
38
Example: Picking the right chart
39
Example: Picking the right chart
40
Example: Picking the right chart
41
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
42
Example: Vertical bar chart
43
Example: Vertical bar chart
44
Example: Vertical bar chart
Both charts have a clear message. The choice
depends on the desired emphasis
45
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
46
Example: stacked bar charts
47
Example 2
48
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
49
Example 1: Horizontal bar charts
50
Example 1: Horizontal bar charts
51
Example 1: Horizontal bar charts
52
Example 1: Horizontal bar charts
53
Example 2: Horizontal bar charts
54
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
55
Example:
Pie charts
56
Picking the right chart:
Scatter plots

To show grouping around a trend line

To show outliers

To show many data points
57
Example: Scatter Plots
58
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
59
Example:
Box plots
60
Example: Box plots
61
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
62
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)
63
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
64