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SPSS T-Test Tutorials

SPSS T-Test Tutorials - Overview

Independent Samples T-Test

SPSS Independent Samples T-Test

A very complete and up-to-date tutorial on running and interpreting t-tests in SPSS. Includes:

  • Assumptions
  • Understanding the SPSS Output
  • Effect Size (Cohen’s D)
  • APA Style Reporting

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Independent Samples T-Test – Quick Introduction

An independent samples t-test examines if 2 populations have equal means on some variable.

Example: do Dutch women have the same mean salary as Dutch men?

This tutorial quickly walks you through the basics such as the assumptions, null hypothesis and effect size for this test.


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Paired Samples T-Test

SPSS Paired Samples T-Test Tutorial

A paired samples t-test examines if 2 variables have equal means in some population.

Example: were the mean salaries over 2018 and 2019 equal for all Dutch citizens?

This tutorial quickly walks you through the correct steps for running this test in SPSS.


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One Sample T-Test

One-Sample T-Test – Quick Tutorial & Example

A one-sample t-test examines if a population mean is likely to be x: some hypothesized value.

Example: do the pupils from my school have a mean IQ score of 100?

This tutorial quickly walks you through the basics for this test, including assumptions, formulas and effect size.


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SPSS One Sample T-Test Tutorial

How to run a one sample t-test correctly in SPSS?

This simple tutorial with downloadable practice data quickly walks you through the right steps!


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T-Test Background Tutorials

Cohen’s D – Effect Size for T-Test

Cohen’s D is the effect size measure of choice for t-tests.

This simple tutorial quickly walks you through

  • rules of thumb for small, medium and large effects;
  • formulas for computing Cohen’s D and;
  • software options for obtaining it.

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Z-Scores – What and Why?

Z-scores are scores that have mean = 0 and standard deviation = 1.

All scores can be standardized into z-scores by subtracting the mean from each score and then dividing it by the standard deviation.

Such standardized scores may be easier to interpret than the original scores. Z-scores may or may not be normally distributed.


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What is a Dichotomous Variable?

Dichotomous variables are variables that hold precisely two distinct values.

Example: sex can only be male or female.

Some analyses that are only suitable for dichotomous variables are


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