#STATA 13 FOR DUMMIES HOW TO#

Assumption #1: Your dependent variable should be measured at the interval or ratio level (i.e., they are continuous).

However, you should decide whether your study meets these assumptions before moving on. Since assumptions #1, #2 and #3 relate to your study design and choice of variables, they cannot be tested for using Stata. If any of these six assumptions are not met, you cannot analyse your data using an independent t-test because you will not get a valid result. There are six 'assumptions' that underpin the independent t-test.

#STATA 13 FOR DUMMIES HOW TO#

We also have a guide on how to run an independent t-test using Minitab. However, if you only have one group and wish to compare this to a known or hypothesized value, you could run a one-sample t-test. Alternatively, if you have more than two unrelated groups, you could use a one-way ANOVA. 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. 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'). Specifically, you use an independent t-test to determine whether the mean difference between two groups is statistically significantly different to zero.ДЇor 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

Stata 13 for dummies