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Description: 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-yearold women were asked about the preschool diet of their children (ages 2−4) using a food

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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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-yearold 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. The Pearson correlation between intake from the two recording methods was 0.448. Assume that FFQ and DR margarine intake are normally distributed.

11.118 Test the hypothesis that the true Pearson correlation (ρ) is significantly different from zero [provide a p-value (two-tailed)].

Table 1 Potential emoji based alternatives to denotation of statistical significance
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Psychological
Association style 1
Emoji denotation Ermoji denotation
P value
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2
denotation
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P>0,05
PS0.05
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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
7
8.5

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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