Assuming that the sample consists of n = 36 individuals, use a two-tailed hypothesis test with a = .05 to determine whether the treatment effect is significant. t = ; the critical value is t = ± the null hypothesis. The treatment effect significant. Compute r2 and the estimated Cohen's d to measure the size of treatment effect. r2 = Estimated Cohen's d = Comparing the answers you found in the preceding two cases, how does the number of scores in the sample influence the measures of effect size? Increasing sample size causes in the measures of effect size.
Assuming that the sample consists of n = 36 individuals, use a two-tailed hypothesis test with a = .05 to determine whether the treatment effect is significant. t = ; the critical value is t = ± the null hypothesis. The treatment effect significant. Compute r2 and the estimated Cohen's d to measure the size of treatment effect. r2 = Estimated Cohen's d = Comparing the answers you found in the preceding two cases, how does the number of scores in the sample influence the measures of effect size? Increasing sample size causes in the measures of effect size.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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A random sample is obtained from a population with a mean of µ = 20. After a treatment is administered to the individuals in the sample, the sample mean is M = 21.3 with a variance of s² = 9.
t Distribution
Degrees of Freedom = 21
-3.0-2.0-1.00.01.02.03.0x.2500.5000.2500-0.6860.686
Assuming that the sample consists of n = 16 individuals, use a two-tailed hypothesis test with α = .05 to determine whether the treatment effect is significant.
t =
; the critical value is t = ±
.Reject the null hypothesis. The treatment effectis significant.
Compute r² and the estimated Cohen’s d to measure the size of treatment effect.
r² =
Estimated Cohen’s d =
Assuming that the sample consists of n = 36 individuals, use a two-tailed hypothesis test with α = .05 to determine whether the treatment effect is significant.
t =
; the critical value is t = ±
. the null hypothesis. The treatment effect significant.
Compute r² and the estimated Cohen’s d to measure the size of treatment effect.
r² =
Estimated Cohen’s d =
Comparing the answers you found in the preceding two cases, how does the number of scores in the sample influence the measures of effect size?
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