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Intro to Stats. Dependent t-tests. Dependent t-tests. Use when: You are examining differences between groups (times) You are comparing two groups (time points) Each participant was tested more than once. The idea. Time1score – Time2score ___________________________________
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Intro to Stats Dependent t-tests
Dependent t-tests • Use when: • You are examining differences between groups (times) • You are comparing two groups (time points) • Each participant was tested more than once
The idea Time1score – Time2score ___________________________________ Spread • t is increased (likely significant) when: • Differences between two time points are large • When spread is very small
Uses of dependent t-tests • Requires fewer subjects • Ideal for studying changes over time • Controls for the impact of individual differences • But sensitive to order effects and other changes over time
Calculating t = ΣD nΣD2 – (ΣD)2 n -1 ΣD = sum of differences between scores n = number of pairs of scores
Example 1 • Study: • Effects of “study drugs” on performance • Given study drugs before a memory test (Adderall?) • (75, 80, 82, 90, 80) • Not given study drugs before a 2nd memory test • (85, 90, 95, 95, 90)
Example 1 • 1. State hypotheses • Null hypothesis: no difference between scores on drugs versus scores off drugs • μdrug = μnodrug • Research hypothesis: difference between scores on drugs versus scores off drugs • Xdrug ≠ Xnodrug
Calculating t = ΣD nΣD2 – (ΣD)2 n -1 ΣD = sum of differences between scores n = number of pairs of scores
Example 1 • 6. Determine whether the statistic exceeds the critical value • -7.45 > 2.78 (and 4.60) • So it exceeds the critical value • 7. If over the critical value, reject the null • & conclude that there was a difference in test scores after taking performance drugs versus not taking them
Example 1 • In results • Participants scored significantly higher on tests when they did not take performance enhancing drugs (M = 91.00, SD = 4.18) than when they did take the drugs (M = 81.40, SD = 5.46), t(4) = -7.45, p < .05 (can say p < .01).