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Lecture 11

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Department
Psychology
Course
PSYC 2002
Professor
Steven Carroll
Semester
Winter

Description
Lecture 11 related samples The story so far… - Single sample, parameters known - Single sample, parameters unknown - Two separate samples, parameters unknown Consider the following and… What’s the difference? - In this experiment, I was interested in how RT changes as a function of stimulus complexity - Each P would make a series of 2AFC decisions and then a series of 4AFC decisions and I would compare RTs for the two levels - How does this paradigm differ from the one we studied last week? Repeated measures/ dependent measures - Repeated measures design • Also known as a within-subjects design • Two separate scores are obtained for each individual in the sample - The same participants are used in all treatment conditions - As such, there is NO RISK of the treatment groups differing from each other in any truly significant way Matched subjects design - Approximates the advantages of a repeated measures design, except: - Two separate samples are uses • Each individual in a sample is matched one-to-one with an individual in the other sample  They are matched on relevant variables • Participants are NOT identical to their match  You have to justify why you believe the samples are equivalent with respect to some specific variables Some data… Participant 2AFC RT 4AFC RT Difference 1 3 5 ? 2 2 6 ? 3 3 4 ? 4 1 3 ? 5 1 7 ? Some data… Participant 2AFC RT 4AFC RT Difference 1 3 5 -2 2 2 6 -4 3 3 4 -1 4 1 3 -2 5 1 7 -6 - The difference column is what we are interested in!!! - If the difference column’s values were all positive, it would not make any difference to the results of the test. WHY? Step 1 - Our null hypothesis for the single sample t-test was H H 0 : µ = X , 1 : µ ≠ X - Our null hypothesis for the independent samples t-test was H 0 µ 1 µ2 H 1 µ1 µ2 : - = 0 , : - ≠ 0 - What will be our hypothesis for the dependent samples t-test? Step 1 H µ H µ 0 : D = 0 , 1 : D ≠ 0 - What is meant by µ D ? The rest of the formulae 2 M −D D S SD S D T = SM MD = = n D √ n 2 SSD SD = df = n – 1 n−1 Df = n – 1 - Wait! - Why aren’t we pooling variance here like we did for the independent samples t-test?! Step 2 - Critical values let’s keep this Type I error rate to 1% - How do you know when a test is one-tailed or two-tailed? - What do you do if it’s two-tailed? Step 2 - At  = .01 (two-tailed), t-critical
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