Indosearch Research Center [IRC]

1. From the menu at the top of the screen click on Graphs, then Bar.
2. Click on Clustered.
3. In the Data in chart are section, click on Summaries for groups of cases. Click on Define.
4. In the Bars represent box, click on Other statistics (e.g., mean).
   
5. Click on the continuous variable you are interested in (e.g. confidence in press). This should be appear in the box listed as Mean. This indicates that the mean on the confidence in press for different groups will be displayed.
6. Click on your first categorical variable (e.g. agegp3). Click on the arrow button to move it into the Category axis box. This variable will appear across the button of your bar graph (X axis).
7. Click on another categorical variable (e.g. sex) and move it into the Define Clusters by: box. This variable will be represented in the legend.
8. Click on the Options button. Remove the tick from Display groups defined by missing values. To do this, click once on the box.
9. Click on OK

The output generated from this procedure is presented below:


Reading the output:
The output from this procedure shows a summary of the distribution of scores for the groups that have been requested (i.e. males and females from the different age groups). The graph presented above suggests that females had slightly higher confidence in press than males, and that this difference is more pronounced among the two older age groups. Among the 18 to 35 age group and 36-51 age group the difference in scores between males and females is very small.

1. From the menu at the top of the screen, click on Graphs, then on Histogram.
2. Click on your variable of interest and move it to the Variable box (e.g. age).
3. Click on Display normal curve. This option will give the distribution of your variable and superimposed over the top, how a normal curve for this distribution would look.
4. If you want to give your graph a title click on the Titles button and type the desired title in the box (e.g. Histogram of age).
5. Click on Continue, then OK.

Reading the output:

Inspection of the shape of the histogram provide you with the information about the distribution of scores on the continuous variable. In this example, the scores are not reasonably normally distributed, with most scores occurring in the center. However, it is common to find data not normally distributed in the social sciences. This issue is well-discussed in the normality part of statistics books.