Psy 202, Chapter 7: The Single Sample t-Test
Psy 202, Chapter 7: The Single Sample t-Test Psy 202
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Popular in Psychology (PSYC)
This 2 page Class Notes was uploaded by T'Keyah Jones on Tuesday October 4, 2016. The Class Notes belongs to Psy 202 at University of Mississippi taught by Dr. Melinda Redding in Fall 2016. Since its upload, it has received 6 views. For similar materials see Elementary Statistics in Psychology (PSYC) at University of Mississippi.
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Date Created: 10/04/16
a) Effect Size Refers to the amount of impact that the explanatory variable has on the outcome variable The amount of the difference in a standardized manner Only used when you “Reject the Null” b) Size of Effect Cohen’s d Cohen’s d d = M - μ small 0.20 S medium 0.50 large 0.80 Serial Killer Example: d= 42-36 = .88 6.8 d= 0.88, which is a large effect and concludes that the means are 0.88 standard deviations apart 2 c) Co2fficient of Determination r = ___t __ Size of Effect r2 t + small 0.01 df medium 0.09 large 0.25 Serial Killer Example: r = __3.302 __ = .46 2 3.302 + 13 r = 0.46; approximately 46% of the variability in the introversion scores can be accounted for by criminal status d) Confidence Interval for the Difference between population means The difference between the population mean can be thought of as an effect size. The farther apart they are, the larger the effect size will be. 95%CI μDIFF (M - μ) ± (CVx SM) Serial Killer Example 95% CI μDIFF (42-36) ± (2.160 x 1.817) = (6.000) ± (3.9247) = 2.08 to 9.92 There is a 95% chance that the difference between the two population means fall somewhere between 2.08 and 9.92. Omega Squared More conservative estimate w = _t - 1_ 2 t + df Just Remember Hypotheses always reflect the population men Directional terms One-tailed Non-directional terms Two-tailed Study and memorize “Cohen’s d” and “Coefficient of Determination” because they will definitely be on the test
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