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ed, in whole or in part. Due to electroc nghts, some thand party content may be suppeessed trom the ellook andior ethapterts) experience. Cengage Learning reserves the right so remove additional content at any time if subsequent rights restrictions require it. tions The Pearson correlation between intake from the two re- cording methods was 0.448. Assume that FFQ and DR margarine intake are normally distributed. 11.118 Test the hypothesis that the true Pearson correla- tion (p) is significantly different from zero [provide a p-value (two-tailed)]. 11.119 Provide a 95% confidence interval for p. The distribution of dietary intake for individual food items is often not very normally distributed. An alternative measure of correlation between the FFQ and DR that does not depend on the assumption of normality is the Speaman rank correlation (r). For the margarine data, r̟ = .679. 11.120 Test the hypothesis that the Spearman rank cor- relation is significantly different from o [provide a p-value (two-tailed)].

ed, in whole or in part. Due to electroc nghts, some thand party content may be suppeessed trom the ellook andior ethapterts) experience. Cengage Learning reserves the right so remove additional content at any time if subsequent rights restrictions require it. tions The Pearson correlation between intake from the two re- cording methods was 0.448. Assume that FFQ and DR margarine intake are normally distributed. 11.118 Test the hypothesis that the true Pearson correla- tion (p) is significantly different from zero [provide a p-value (two-tailed)]. 11.119 Provide a 95% confidence interval for p. The distribution of dietary intake for individual food items is often not very normally distributed. An alternative measure of correlation between the FFQ and DR that does not depend on the assumption of normality is the Speaman rank correlation (r). For the margarine data, r̟ = .679. 11.120 Test the hypothesis that the Spearman rank cor- relation is significantly different from o [provide a p-value (two-tailed)].

MATLAB: An Introduction with Applications
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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Please solve 11.119 and 11.120 (not use programme for example Minitab)

TABLE 11.36 Margarine intake assessed by two different recording methods (servings per week, [n = 12]) ID FFQ DR 340 7 399 7 0.5 466 502 541 554 7 2.5 558 7 3 605 7 0.5 611 21 3.7 618 2.5 653 21 4.1 707 8.5
Transcribed Image Text:TABLE 11.36 Margarine intake assessed by two different recording methods (servings per week, [n = 12]) ID FFQ DR 340 7 399 7 0.5 466 502 541 554 7 2.5 558 7 3 605 7 0.5 611 21 3.7 618 2.5 653 21 4.1 707 8.5
p00 Nutrition The assessment of diet is an important exposure for many disease outcomes. However, there is often much imprecision in dietary recall. In one study, 70- to 79-year- old women were asked about the preschool diet of their children (ages 2–4) using a food frequency questionnaire (FFQ). A unique aspect of the study is that simultaneous diet record data exist on the same children recorded in real time by their mothers when they were ages 2-4 and their mothers were 20 to 40 years old. The data in Table 11.36 were available on average servings of margarine per week. uplicated, in whole or in part. Due to electronic nghts, some third party content may be suppressed from the eHook and/or eChapters). caming experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. ributions The Pearson correlation between intake from the two re- cording methods was 0.448. Assume that FFQ and DR margarine intake are normally distributed. 11.118 Test the hypothesis that the true Pearson correla- tion (p) is significantly different from zero [provide a p-value (two-tailed). 11.119 Provide a 95% confidence interval for p. The distribution of dietary íntake for individual food items is often not very normally distributed. An alternative measure of correlation between the FFQ and DR that does not depend on the assumption of normality is the Speaman rank correlation (r). For the margarine data, r, = .679. 11.120 Test the hypothesis that the Spearman rank cor- relation is significantly different from 0 [provide a p-value (two-tailed)]. 11.121 Provide a 95% confidence interval for the true Spearman rank correlation (p).
Transcribed Image Text:p00 Nutrition The assessment of diet is an important exposure for many disease outcomes. However, there is often much imprecision in dietary recall. In one study, 70- to 79-year- old women were asked about the preschool diet of their children (ages 2–4) using a food frequency questionnaire (FFQ). A unique aspect of the study is that simultaneous diet record data exist on the same children recorded in real time by their mothers when they were ages 2-4 and their mothers were 20 to 40 years old. The data in Table 11.36 were available on average servings of margarine per week. uplicated, in whole or in part. Due to electronic nghts, some third party content may be suppressed from the eHook and/or eChapters). caming experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. ributions The Pearson correlation between intake from the two re- cording methods was 0.448. Assume that FFQ and DR margarine intake are normally distributed. 11.118 Test the hypothesis that the true Pearson correla- tion (p) is significantly different from zero [provide a p-value (two-tailed). 11.119 Provide a 95% confidence interval for p. The distribution of dietary íntake for individual food items is often not very normally distributed. An alternative measure of correlation between the FFQ and DR that does not depend on the assumption of normality is the Speaman rank correlation (r). For the margarine data, r, = .679. 11.120 Test the hypothesis that the Spearman rank cor- relation is significantly different from 0 [provide a p-value (two-tailed)]. 11.121 Provide a 95% confidence interval for the true Spearman rank correlation (p).
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