IBM SPSS Essentials, 2nd Edition

9Z‐ and T‐Tests

Chapter Menu

• Chapter Learning Objectives
• The One Sample Z-Test
• The t-Test
• Summary

Chapter Learning Objectives

1. Select the appropriate analysis for your data
   1. One sample z‐test
   2. One sample t‐test
   3. Two independent samples t‐test
   4. Two correlated samples t‐test
2. Identify important and unimportant output
   1. Mean difference
   2. Standard error
   3. “t”
   4. “p”

Welcome to the wonderful world of inferential analyses. These chapters are not “best practice” recommendations on performing statistics – you need to get that information from your statistics instructor (alphas and hypotheses and similar stuff summarized in Chapter 8). Here, we're just trying to show you how to run some common analyses and navigate the output. All analyzed data are pictured in the screenshots, so you can enter data and follow along if you are so inclined.

The One Sample Z‐Test

The most basic analytical procedure you'll want to perform involves a determination of whether or not two numbers differ from each other. Most often, the analysis you'll use in these situations is some type of t‐test. Invariably, however, statistics texts first introduce you to the one‐sample z‐test. This is not a very practical analytical procedure, because it requires that you know two things about your population of interest (called parameters): the population mean (μ) and the population standard deviation (σ). Outside ...