Advanced ANOVA/Testing differences

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Resource type: this resource contains a tutorial or tutorial notes. Completion status: this resource is ~75% complete. This tutorial examines inferential techniques for 'testing differences' between the means for: a single variable across two independent groups, two related variables, and one sample mean compared to a fixed value. Practical exercises are based on using SPSS.

Contents 1 Types 1.1 1-sample t-test 1.2 Within-subjects t-test 1.3 Between-subjects t-test 2 Variance 3 Questions 4 Exercises 5 Tips 6 Readings/References 7 See also 8 External links

[edit] Types

There are three types of t-test"

[edit] 1-sample t-test

• Compares a sample mean with a known population mean
• Non-parametric equivalent is the chi-square goodness-of-fit test

[edit] Within-subjects t-test

• Compares two means that are repeated measures for the same participants
• Compares two means between matched samples
• Non-parametric equivalent is the Wilcoxon t-test

[edit] Between-subjects t-test

• Compares two means for independent groups
• Non-parametric equivalents are Mann-Whitney U and chi-square test for two independent samples (this can be used for nominal, interval, or ratio data)

[edit] Variance

• Within-group variance = individual differences + measurement error
• Between-group variance = individual differences + measurement error + treatment effect

[edit] Questions

1. What are the three types of t-test and when would you use each of them?
2. What are the assumptions of t-tests?
3. What are the non-parametric alternatives and when would you use each of them?
4. What graphical techniques could accompany the different ways of testing differences?
5. What measures of effect size are available for measuring differences?
6. What should be included in a results section write-up for analyses which involve testing differences?

[edit] Exercises

Using the LEQ dataset, provide analyses which demonstrate use of the each of the types of parametric and non-parametric tests of differences, including:

1. Assumption testing
2. Graphing
3. Descriptives
4. Inferential analyses of differences
5. Effect sizes
6. APA style write-up

[edit] Tips

• See SPSS tips
• See Thesis tips

[edit] Readings/References

1. Diekhoff Ch 6 and 7
2. Howell, D. C. (2002). Statistical methods for psychology. (5th ed.). Pacific Grove CA: Duxbury. Chapter 7.

[edit] See also

• Testing differences
• t-test
• z-test

[edit] External links

• Testing differences (ucspace)