When conducting a significance test to determine if there is a difference between two treatments, with a quantitative response variable, treatments are given to different experimental units, we summarize the data by: a) computing the difference in the proportion of the sample that reacted better to treatment one and the proportion of the sample that reacted better to treatment two. b) computing the proportion of the sample that reacted better to treatment one than treatment two. c) computing the difference in the responses for each experimental unit under both treatments, and then finding the mean and standard deviation of the differences. d) computing the mean and standard deviation of each treatment group separately.
When conducting a significance test to determine if there is a difference between two treatments, with a quantitative response variable, treatments are given to different experimental units, we summarize the data by: a) computing the difference in the proportion of the sample that reacted better to treatment one and the proportion of the sample that reacted better to treatment two. b) computing the proportion of the sample that reacted better to treatment one than treatment two. c) computing the difference in the responses for each experimental unit under both treatments, and then finding the mean and standard deviation of the differences. d) computing the mean and standard deviation of each treatment group separately.
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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When conducting a significance test to determine if there is a difference between two treatments, with a quantitative response variable, treatments are given to different experimental units, we summarize the data by:
a) computing the difference in the proportion of the sample that reacted better to treatment one and the proportion of the sample that reacted better to treatment two.
b) computing the proportion of the sample that reacted better to treatment one than treatment two.
c) computing the difference in the responses for each experimental unit under both treatments, and then finding the mean and standard deviation of the differences.
d) computing the mean and standard deviation of each treatment group separately.
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