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Chapter 13

Ch. 13 - The Comparison of Two Conditions.pdf

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PSYC 3525
Josee Rivest

Ch. 13 - The Comparison of Two Conditions Tuesday, February 26, 20132:17 PM What do signal-to-noiserationshaveto do with t tests? • Three most popular statistical tests: t test, F test, and chi-square test • The hypothesis determines which statistical test is used ○ t test-- used for comparing the means of two groups • A signal-to-noise ratio is set up ○ Signal is represented by the difference between the two means ○ Noise is represented by the variability of the scores within the samples • The larger this ratio, them more likely it is that the null hypothesis will be rejected • The independent-sample t test tests statistical significance by examining the difference between two independent means (the signal) against the background of the within-group variability (the noise) • The larger the difference between the means (i.e., the greater the signal), and/or the smaller the within-group variability for a given size study (i.e., the less the noise), the greater will be the value of t (larger t value is preferable) How do I computean independent-sample t test? • t test for independent samples (i.e., not repeated-measures designs) • • Where (unbiased estimator of the population variance) What cana tableof p valuesfor t teachme? • t distribution-- a family of curves, where there is a different curve (each one resembling the standard normal distribution) for every possible value of what are called the degrees of freedom (df)-- the number of values free to vary ○ For an independent-samples t test with two groups, • In order for a t test to be accurate, homogeneity of variance (the idea that the population variance of the groups being compared is assumed to be equal) must be met ○ Raw scores are often tr
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