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Lecture 3 Summary
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- 1in two-sample tests we are interested in comparing two means. what are the two situations?within-subjects
(aka repeated)
between-subjects
(aka independent groups) - 2What situation is using the same people ?Within subjects design/
Repeated measures - 3What situation is using different people ?Between subjects design/ Independent groups
- 45 different names for repeated measures t-testswithin subjects t-test
correlated scores t-test
paired samples
dependent groups t-test
matched t-test - 5what type of test would you use if you design a program that you think will reduce social anxiety in children?Repeated Measures t-test
target a group of socially anxious children and measure their levels of social anxiety before and after your treatment. - 6Repeated measures designs 1) do you need to consider carry over effects? 2) do you need to use a control group?1) Yes, having been tested in one condition affects how participants respond in another condition
2) sometimes, use a control group for intervention-type studies. (see what happens overtime w/o an intervention) - 7What are the 3 different names for 'independent groups t-test'between subjects t-test
unrelated t-test
uncorrelated scores t-test - 8Independent groups t-test at what point do we say a difference was real and was due to levels of the IV, not by chance?observed difference relative to the difference we expect
- 9Differences between repeated measures and independent t-test 1. repeated measuresBecause scores are linked (each person gives two sets of scores) actually asking what, on average, is the difference between score 1 and score 2 for each person, and then tests whether this average is different from zero (by comparing it to a population where the mean difference score is zero).
- 10Differences between repeated measures and independent t-test 1. independent t-testThere is no relationship between the scores - thus need to first work with the two sets of scores independently. Then the mean of one set is compared with the mean of the other. If this difference between the means is sufficiently different from zero, then there is a significant difference between the groups.
- 11Whats the pooled variance?the larger group gets weighed more heavily
- 12when do you use single sample z and t tests- population mean and SD is known (z-test)
- population mean is known but the population SD is not known (t-test) - 13when do you use repeated measures t-testthe same person or a matched pair gives you two scores
- 14when do you use independent groups t-testwhen you have two independent samples
- 15What are the 6 steps of interpreting rsults1. type of test
2. significant or not significant
3. DV
4. levels of IV
5. state statistic
6. (if sig - direction of effect) - 16what are the assumptions of t-tests and z-tests1. normality (that the sampling distribution is normal)
- if its skewed, then the assumption is met if N is large enough
2. random sampling - 17Independent groups t-test assumptions1. independence of observations
- samples of N1 and N2 randomly selected
2. population normality
3. homogeneity of variance
- the populations have equal variances
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- Fichas sobre Lecture 3 Summary, creado por Hailey Brown el 08/04/2020.
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- Hailey Brown
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