Unrelated t-test PDF

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Notes on Unrelated t-tests....

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Notes Unrelated t-test

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Assumptions of data for Parametric Tests o Must be at least interval 

Interval-On scale

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Ratio- On scale with absolute zero 

Also ok

o Sample drawn at random from population o Sample data should come from normally distributed population 

Does not mean that sample data should be normally distributed

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Most samples are too small to assess whether they are normal

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In practice- assumed population has a normal distribution 

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Decision may be based on past experience or theory

Unrelated t-test o Looks at differences between 2 conditions or groups o Must have interval level data o Must be between groups design o Test-independent samples on SPSS o Data Assumptions 

All of the above Parametric assumptions

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Homogeneity of variance 

Variances of groups should not be significantly different

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Need to check when… o Using an unrelated design o Sizes of groups are different o SPSS does this automatically-Levene’s test

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Robust test- some leeway in assumptions 

Normal distribution- Some flexibility

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Homogeneity of variance (tested by SPSS)- Alternative results to report

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Data must be interval

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Alternative- Run a Mann-Whitney

o Reporting the test 

T(df)= t value, P=significance level

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Format is the same for both related and unrelated t-tests 

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Ex. T(26)=2.79, p=.01

Ignore signs of values, always put in as positive...