Let XB and XA denote, respectively, the weight of a person before and after a certain weight loss diet regime. If D = XA- XB, then the mean of the differences, D, calculated on a random sample of size n, can be used as a basis to test Ho: µD = 0 against H1: µD > 0 and thus verify if the weight loss diet has been effective. A t-test statistic is usually built as the ratio of an estimator of the population parameter of interest (or a function of the population parameters of interest in the case of the difference of two means), divided by its standard error. A significant treatment-by-block interaction in the ANOVA for an RCBD with more than one replicate per treatment per block indicates that differences among treatments are not constant from block to block.
Let XB and XA denote, respectively, the weight of a person before and after a certain weight loss diet regime. If D = XA- XB, then the mean of the differences, D, calculated on a random sample of size n, can be used as a basis to test Ho: µD = 0 against H1: µD > 0 and thus verify if the weight loss diet has been effective. A t-test statistic is usually built as the ratio of an estimator of the population parameter of interest (or a function of the population parameters of interest in the case of the difference of two means), divided by its standard error. A significant treatment-by-block interaction in the ANOVA for an RCBD with more than one replicate per treatment per block indicates that differences among treatments are not constant from block to block.
Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter10: Sequences, Series, And Probability
Section10.8: Probability
Problem 32E
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