To evaluate the effect of a treatment, a sample ofn = 8 is obtained from a population with a mean of m =50, and the treatment is administered to the individuals in the sample. After treatment, the sample mean is found to be M = 55.Assuming that the sample variance is s2 =32, use atwo-tailed hypothesis test with a = .05 to determine whether the treatment effect is significant and compute both Cohen’s d and r2 to measure effect size.Assuming that the sample variance is s2 = 72, repeat the test and compute both measures of effect size.Comparing your answers for parts a and b, how does the variability of the scores in the sample influence the outcome of a hypothesis test and measures of effect size?

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Description: To evaluate the effect of a treatment, a sample ofn = 8 is obtained from a population with a mean of m =50, and the treatment is administered to the individuals in the sample. After treatment, the sample mean is found to be M = 55.Assuming that the s

Given: Sample size=n=8, population mean=μ=50 and sample mean=x¯=55.

Answered: To evaluate the effect of a treatment,…

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To evaluate the effect of a treatment, a sample of
n = 8 is obtained from a population with a mean of m =50, and the treatment is administered to the individuals in the sample. After treatment, the sample mean is found to be M = 55.

Assuming that the sample variance is s2 =32, use a

two-tailed hypothesis test with a = .05 to determine whether the treatment effect is significant and compute both Cohen’s d and r2 to measure effect size.
Assuming that the sample variance is s2 = 72, repeat the test and compute both measures of effect size.
Comparing your answers for parts a and b, how does the variability of the scores in the sample influence the outcome of a hypothesis test and measures of effect size?

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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