You can check the category codes for s1gender, or any other variable you choose, by finding the variable’s row in Variable View and clicking to open the Values cell.)Īfter you’ve entered the information into Define Groups, click Continue and then OK. (We are using the dataset’s codes for Male and Female. Move s1gender to the Grouping Variable box.Ĭlick on Define Groups and enter 1 in the Group 1 box and 2 in the Group 2 box, because 1=Male and 2=Female in the dataset. Move our variable s1gcseptsnew to the Test Variable(s) box. Select Analyze, Compare Means, and then Independent-Samples T Test.
We are going to use the Independent-Samples T Test, because we are interested in comparing the mean GCSE scores across the two unrelated categories male and female in the variable s1gender. If a p-value is greater than 0.05, then the result is insignificant.īecause we have already run frequencies and used a histogram to confirm the normal distribution of our sample, we can run a t test to check for significance. If a p-value reported from a t test is less than 0.05, then that result is said to be statistically significant. We can work out the chances of the result we have obtained happening by chance. If in the population there is no difference in GCSE score for males and females, we may have caused there to be a different mean for males and females just by randomly selecting the sample. A p-value is basically the likelihood of finding a mean difference by chance if indeed there is no difference in the population. In a t test, like in most tests of significance, the significance threshold is traditionally set at p = 0.05. In order to investigate this, we can run a t test to see whether this difference in means is statistically significant. Because we calculated these means from data from a sample of the population, it may be that the difference in means across both sexes is due to chance. Is this difference large enough to be interesting? Alternatively, you may want to consider whether the difference in means across both sexes is simply due to chance. On average, girls have higher mean GCSE scores than boys do. When we compared mean GCSE scores between boys and girls above, we saw a slight difference. Is the difference in mean GCSE scores between boys and girls in Year 11 statistically significant?