Week 8: Comparing Group Means (t-tests)

Lesson 1: Comparing Group Means (t-Tests)

Introduction

A good research study begins with the end in mind. How you design a study also impacts the choice of statistical analyses for the study. Comparing group means is the basis for most studies that look at two or more groups and evaluate dependent variables for those groups.

When you reviewed Randomized Controlled Trials (RCTs), remember that one group received an intervention and the other did not. How do you determine if there was a statistically significant difference in one group versus the other? You run statistical tests that examine the probability that there is difference in the experimental group. For example, did the independent variable impact the dependent variable?

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Similar principles also apply to descriptive research. As an example, are there statistically significant differences in income based on gender? Here, we are comparing income levels between two groups, male and female. In order to compare means, measure data on the ratio level of measurement so we can compare means.

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Learning Outcomes

At the end of this lesson, you will be able to:

• Compare group means by conducting t-tests.
• Analyze research design techniques as applicable to the final project.

Before attempting to complete your learning activities for this week, review the following learning materials:

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Learning Materials

Read the following in your Kim, Mallory, & Vallerio (2022) Statistics for evidence-based practice in nursing textbook:

Chapter 11, “Tests for Comparing Group Means: Part I”

Using JASP to Conduct an Independent T-test Screencast Transcript

Okay. So in this recording, we’re going to use JASP to conduct an independent T-test. So this is our data view right here. And we’re going to look at gender right here, this variable right here. And we’re going to look at comparing men and women on sodium content, the variable right to the left of gender. So this is going to be an independent T-test. So we select independent T-test. We want to put our variable there, and that is our dependent variable. So, that will be sodium. And then our grouping variable, how do we want to group it? That’s our independent variable and we want to group it on gender. And here we see our T value, our degrees of freedom. And then we see a notation here, 2.617, and it says E minus five. So that means we have to move the decimal point 5 times to the left. So it’s 0.000002617. So definitely significant. Well below 0.05. So that notation there, it’s a way to abbreviate long notations and telling you, you have to move the decimal point again, five spaces to the left.

We also probably want to run descriptive statistics. So we have significance, but we don’t know, as our… Do men have higher sodium levels than women or vice versa? And we see here in our descriptive. First, we have 50 men and 50 women, and we see that the mean score, that men have a higher sodium level than women. We can do that visually, look at it visually with a descriptive plot, and we can see the difference there. So that is a dependent or excuse me, an independent T-test using JASP.

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