Independent Samples t Test
The independent samples t test (also known as two-sample t test, or 2-sample t test) compares the means of two independent groups to determine whether there is statistical evidence that the associated population means are significantly different.
The assumptions for using this test are:
- The dependent variable should be measured on a continuous scale (i.e., it is measured at the interval or ratio level).
- The independent variable should consist of two categorical, independent groups.
- You should have independence of observations, which means that there is no relationship between the observations in each group or between the groups themselves.
- There should be no significant outliers.
- The dependent variable should be approximately normally distributed for each group of the independent variable.
- There needs to be homogeneity of variances.
For further reading about independent samples t test using SPSS, you may read this:
https://statistics.laerd.com/spss-tutorials/independent-t-test-using-spss-statistics.php
or watch these videos for both one sample and independent samples t test:
References
Lazar, J. , Feng, J. H., Hochheiser, H. (2017), Research methods in human-computer interaction: Morgan Kaufmann, 2017.
Rosenthal, R., Rosnow, R., 2008. Essentials of Behavioral Research: Methods and Data Analysis, third ed. McGraw Hill, Boston, MA.
Sauro, J., and Lewis, J. R., (2016). Quantifying the user experience: Practical statistics for user research: Morgan Kaufmann.