QUESTION A10 (5A research was conducted to observe the effect of sunlight exposure on vitamin D concentrationamong women with deficiency. The result obtained in the research was r = 0.843.(a) Interpret the value of product-moment correlation, r.(b)#Compute the coefficient of determination, r², and interpret the result.

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Answered: A research was conducted to observe the…

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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Acid rain Biologists studying the effects of acid rainon wildlife collected data from 163 streams in theAdirondack Mountains. They recorded the pH (acidity) of the water and the BCI, a measure of biological diver-sity, and they calculated R2 = 27,. Here’s a scatterplot of BCI against pH:a) What is the correlation between pH and BCI?b) Describe the association between these two variables.c) If a stream has average pH, what would you predictabout the BCI?d) In a stream where the pH is 3 standard deviationsabove average, what would you predict about the BCI?
Using the linear correlation coefficient of r = 0.89, the coefficient of determination (R²) is determined to be 7.921% True False
A paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a scatterplot in the paper. BMI Change (kg/m2) 0.7 0.8 1 1.5 1.2 1 0.4 0.4 0.5 -0.5 0.1 Depression Score Change -1 | 4 5 8 13 14| 17| 18| 12 14 The accompanying computer output is from Minitab. Fitted Line Plot Depression score change = 6.512 + 5.472 BMI change 5.26270 20 - R-Sq R-Sq (adj) 19.88% 27.16% 15- 10-. 5- -0.5 0.0 0.5 1.0 1.5 BMI change 5.26270 27.166 Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 6.512 2.26 2.88 0.0164 BMI change 5.472 2.83 1.93 0.0823 1.00 Regression Equation Depression score change = 6.512 + 5.472 EMI change (a) What percentage of observed variation in depression score change can be explained by the simple linear regression model?…
A study was conducted to determine if the number of hours of sleep per night was related to exam performance on an exam taken the following day. The correlation coefficient was found to be .78. Which statement is FALSE? The relationship between hours of sleep and exam performance the following day is strong. As the number of hours of sleep increases, exam performance is also expected to increase at a similar rate. The r-value is .78. The number of hours of sleep cannot be used to estimate or predict possible performance on an exam the following day.
An economist conducted a study of the possible association between weekly income and weekly grocery expenditures. The particular interest was whether higher income would result in shoppers spending more on groceries. A random sample of shoppers at a local supermarket was obtained, and a questionnaire was administered asking about the weekly income of the shopper’s family and the grocery bill for that week. The correlation was found to be r=0.675. The percentage (to two decimal places) of variation in grocery bills explained by the family's weekly income regression line is:
Data collected by a psychology professor over a four-year period examined the relationship between class attendance and average test grades in introductory psychology. Results revealed that the correlation between the number of classes attended was positively correlated with the students' average test gradeover the course of the semester (r = 0.35). (a) What is the proportionate reduction in error, or r2, for predicting average test grade from the number of classes attended? (b) Explain what this r2 means for this set of data.
Compute the value of correlation coefficient of using data in table 1 for the number of hrs. a person works per week and thenumber of accidents or injuries that the person has over a peroid of one week. Table :1 Hrs.Worked ( x ) No. of accidents( y ) 30 2 42 3 25 4 44 8 56 5
find the linear correlation coefficent and the critical value(s)
An analyst takes a sample of 10 households and records their weekly consumption expenditure (in RM) and weekly household income (in RM). The Pearson coefficient of correlation between weekly consumption expenditure and weekly household income is found to be 0.9563. Therefore, an increase in the weekly household income causes a very high increase in the weekly consumption expenditure. Select one: O True O False
Find coefficient of association between literacy and employment and comment on your result using the following information. Total number of adults=1000,Total number of literates=129 Total number of unemployed=139,Total number of literates unemployed=82
A paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter2) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a scatterplot in the paper. BMI Change (kg/m²) Depression Score Change S = The accompanying computer output is from Minitab. Depression score change 15- 10- -0.5 S Fitted Line Plot Depression score change = 6.577 +5.440 BMI change 20- 5.30586 Coefficients T 0.0 0.5 -0.5 R-sq 25.96% - 1 Term Coef Constant 6.577 BMI change 5.440 % 0.5 BMI change 1.0 SE Coef 2.28 2.90 9 0 0.1 0.7 0.8 1 1.5 4 T-Value 2.88 1.87 Interpret this estimate. s is the typical amount by which the ---Select--- line. 4 5 Regression Equation Depression score change = 6.577 +5.440 BMI change P-Value 0.0164 0.0906 S 5.30586 25.96% R-Sq R-Sq (adj) 18.56% 8 (b) Give a point estimate of o. (Round your answer to…
In a regression study, relating Price/unit (x) to Weekly Sales (in Kg.), with the scatter plot showing a strong negative direction, 63% of the variability in sales could be accounted for by the variation in the Unit Price. The correlation coefficient in this study is: 0.79 -0.4 -0.79 0.4

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