![stata 13 vs 14 stata 13 vs 14](https://docplayer.net/docs-images/47/20757930/images/page_14.jpg)
Note: If your independent variable has related groups, you will need to use a paired t-test instead. However, before we introduce you to this procedure, you need to understand the different assumptions that your data must meet in order for an independent t-test to give you a valid result.
Stata 13 vs 14 how to#
In this guide, we show you how to carry out an independent t-test using Stata, as well as interpret and report the results from this test. Note: In Stata 12, you will see that the independent t-test is referred to as the "two-group mean-comparison test", whereas in Stata 13, it is referred to as the "t test (mean-comparison test)". Alternately, an independent t-test could be used to understand whether there is a difference in salary based on educational level (i.e., your dependent variable would be "salary" and your independent variable would be "educational level", which has two groups: "undergraduate degree" and "postgraduate degree").
![stata 13 vs 14 stata 13 vs 14](https://i.ytimg.com/vi/YAVq99iUTTI/maxresdefault.jpg)
Specifically, you use an independent t-test to determine whether the mean difference between two groups is statistically significantly different to zero.įor example, an independent t-test could be used to test whether revision time amongst college students differed based on gender (i.e., your dependent variable would be "revision time", measured in minutes or hours, and your independent variable would be "gender", which has two groups: "male" and "female"). The independent t-test, also referred to as an independent-samples t-test, independent-measures t-test or unpaired t-test, is used to determine whether the mean of a dependent variable (e.g., weight, anxiety level, salary, reaction time, etc.) is the same in two unrelated, independent groups (e.g., males vs females, employed vs unemployed, under 21 year olds vs those 21 years and older, etc.). Independent t-test using Stata Introduction