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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.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.1: Measures Of Center
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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.
Transcribed Image Text: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.
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.
Transcribed Image Text: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.
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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.
 

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Degrees of Freedom = 21

 
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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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