provided male/female were the two options, it is considered a binary variable. Now there are all kinds of tests that can deal with that kind of data. It just depends on what you the other variable is you want to compare them on. For example male/female vs. age, then age is a scale variable so we have binary vs. scale. A independent samples t-test is then often used. Have a look at peterstatistics.com. It has on the homepage a long table with all kinds of tests you can do. Hope this helps.
yep. The double click on the diagram in the output is only to change the appearance of the diagram. If you look at the top of that window it is called the 'chart editor'. Good luck with your research/study/analysis.
what statistical analysis can you do to compare male and female, or do you have to go back to the start?
provided male/female were the two options, it is considered a binary variable. Now there are all kinds of tests that can deal with that kind of data. It just depends on what you the other variable is you want to compare them on. For example male/female vs. age, then age is a scale variable so we have binary vs. scale. A independent samples t-test is then often used. Have a look at peterstatistics.com. It has on the homepage a long table with all kinds of tests you can do. Hope this helps.
@@stikpet Thank you, exactly what I needed to know. So you cant double click on the graph, you have to go back to analyze on the data.
yep. The double click on the diagram in the output is only to change the appearance of the diagram. If you look at the top of that window it is called the 'chart editor'. Good luck with your research/study/analysis.