Read in Order Categorized as Chapter 4 - Analysis and presentation of gender statistics Graphs can be used to great effect in publication. They can summarize trends, patterns and relationships between variables.
They can illustrate and amplify the main messages of the publication and inspire the reader to continue reading. Graphs are generally better understood and interpreted by the average reader, and therefore appeal to a wider audience. If done well, they can give readers a quick and easy understanding of the differences and similarities between women and men. Every graph should make a point, which can be given in the title. Nevertheless, in many publications, titles state the subject and the coverage of data in the graph.
In this case, the title should start with the key word s of the statistics presented. There are many types of charts. The type of chart used depends on the kind of data used in the analysis and the point the authors wish to make.
Choosing the correct chart can make the difference between providing the reader with a strong message and confusing the reader. Time-series data that are often presented in line charts include life expectancies at birth, infant mortality, literacy rates and labour force participation rates. In general, it is expected that advances in human development over time will be reflected in declining infant mortality rates and increasing literacy rates and life expectancies, while labour force participation rates are expected to respond to changes in overall market and trade conditions.
It is generally recommended that charts start from zero at the y-axis of a quantitative variable, so that the differences or similarities between women and men are not distorted. At the same time, however, it is important for the comparison between women and men to be facilitated.
In this case all the values of life expectancy are concentrated above the age of Line charts are also useful in revealing changes from one age cohort to another in labour force participation, employment or literacy, for example. The chart illustrates three main points: One of the axes, usually the x-axis, is formed by a qualitative variable with distinct categories. The other axis can represent absolute frequencies or percentages, sums or averages.
Bar charts can be used to illustrate data that do not vary too greatly in magnitude. It shows the percentage of women in India who have ever experienced physical violence for different categories of wealth, ordered from the poorest quintile poorest 20 per cent of the population to the wealthiest quintile wealthiest 20 per cent of the population.
Grouped or clustered bar charts present the same characteristic for two or more categories of population at the same time, thereby facilitating comparisons.
Often, the values of a characteristic for women and men are shown as two sets of differently colored or shaded bars side by side for each category. For example, in chart IV. It is shown that girls have lower school participation rates than boys in both wealth groups; however, the gender gap is much more substantial in the poorest group of population.
Yemen, Ministry of Health and Population and others, If more categories or data points need to be illustrated, the bars can become too thin and difficult to interpret. In such cases it is recommended that some dot charts be used instead of grouped bar charts. For example, in comparison to chart IV. Stacked bar charts can be used for most kinds of data, but they are most effective for categories that add up to per cent.
A common problem with stacked bar charts is that one or more segments are too short to be visible on the scale. Another problem is that using more than three segments of the bar can make it difficult to compare one bar to another.
Some stacked charts illustrate the percentage distribution by sex within various categories of variables, such as the share of women and men among categories of occupations. Other stacked charts, however, can illustrate the distribution of variables within the female and male population, such as the distribution of female and male deaths by cause of death or the distribution of female and male employment by sector of employment.
They are often used when many categories need to be presented, or when the categories presented have long labels. Men and women can be presented side by side for each category, as in chart IV. Similar to vertical bar charts, when a graph needs to display the sex distribution within a category and the values for women and men add up to per cent, a stacked bar chart should be considered.
El-Zanaty and Way, Horizontal bar charts are also ideal for showing time-use data, because the left-to-right motion in Western cultures on the x-axis generally implies the passage of time. Bar charts are often used to present gender statistics for different regions of a country. When there are many regions to be presented, a horizontal bar chart may be preferred.
It is important that the regions considered are presented in such a way that they facilitate comparisons between women and men within and between the regions. Presenting the regions alphabetically is seldom a good solution.
When no other dimension is the focus of analysis such as the level of economic or human development of the region, for example , it is important that the regions are presented in the graph according to the rank of values observed for women or, less frequently, for men. Ranking of the regions by gender gap may also be considered if it would not make the graph too confusing. Another way to use a horizontal bar chart is to plot against each other extending left and right from the y-axis two variables that are visibly correlated.
The two variables considered for this type of plot do not need to have the same scale. Traditionally, age and sex pyramids plot the age composition of the population of women and men as horizontal bars originating from the y-axis, using the absolute number of women and men by age group.
Because they use absolute numbers, age and sex pyramids tend to emphasize the concentration of population in particular age groups. Alternatively, this type of chart can be constructed using percentages instead of absolute numbers, emphasizing the groups where women or men are overrepresented. For example, chart IV. In comparison, chart IV. Proportion of population with at least secondary education, by sex and age group, Swaziland, Source: Other examples of age and sex pyramids include foreign-born population by sex, age group and marital status, or proportion of population smoking by sex and age group.
Pie charts must always show shares that total per cent. A common error with pie charts is to show too many categories, resulting in labels that are hard to read or shares that are too narrow. When too many categories need to be compared, bar charts are more suitable. Pie charts are best used when only one or two shares of the whole are shown for different years, different population groups or different related categories.
Other examples include the share of time used by women in total time invested by women and men in various types of unpaid housework, or the share of women among managers at two points in time. The Gambia, Bureau of Statistics, The two variables are plotted against each other in order to show the patterns of their grouping. Scatter plots are also used to identify and analyse outliers in the data.
Scatter plots are particularly useful when many data points need to be displayed, such as in the case of a large number of regions or subregions of a country that cannot be easily presented in tables or bar charts. The dots that are close to the diagonal represent the states where girls and boys have similar school attendance rates.
This is the case for most of the states in India; however, there are a few exceptions. A number of states with generally lower school attendance have higher rates for boys than for girls. These particular cases may be highlighted on the graph. ScrewTurn Wiki version 3. Some of the icons created by FamFamFam.