4. All but one of these statements contain a mistake. Which could be true?A. The correlation between a car's length and its fuel efficiency is 0.71 miles per gallon.B. There is a correlation of 0.63 between gender and political party.C. There is a high correlation (1.09) between height of a corn stalk and its age in weeks.The correlation between the amount of fertilizer used and the yield of beans 0.42.E. The correlation between a football player's weight and the position he plays is 0.54.5. A company's sales increase by the same amount each year. This growth is...A. quadraticB. exponentialC. linearD. logarithmicE. power

Dear students as per guidelines we solve only first question when questions are different. Solution…

Answered: 4. All but one of these statements…

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 following statement contains an error. Choose the statement that best explains the error. "The correlation between shoe size and height is 0.87 inches" A. Correlation requires that both of the variables be categorical B. When stating the correlation coefficient, one must state whether it is a positive or negative relationship C. This statement does not tell us whether or not shoe size is correlated with height D. When reporting correlation, one does not report units because correlation has no units E. There is no error in this statement
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3. .... 2. 5. 4. 3. 2. 参 dollars per year) Salary (thousands of Acreage dollars per year) Salary (thousands of square feet for the same houses, what would the correlation be? for some houses is 0.91. If you found the correlation between house price in thousands of dollars and area in 4.24 House Price The correlation between house price (in dollars) and area of the house (in square feet) Education (years) 2. 4. 0. 12 1. 8. 20. 60- Start Year 1985 40 2005 1995 2010 09 li. 06 (B) Full Bath 4. 1. 7. 6. 5. : (A) 0.777 0.374
6. Which of these relationships would be better described with a Spearman's rank coefficient than with a Pearson's coefficient? a. The association between income and educational attainment (measured in years of school) b. The association between hours of sleep and score on an exam C. The association between years aged and price of wine d. The association between ice cream sales and crime rates e. The association between number on NY Times Best Seller List and copies of book sold
5. You have a sample of 19 students and plan to determine if a linear relationship can be used to predict the SAT score as a function of the high school GPA. What value does the correlation coefficient need to exceed, according to the r√n> 3 rule, in order for you to be able to say that the correlation between the SAT score and the high school GPA is significant, instead of it having occurred by random chance? Write your answer as a decimal correctly rounded to three decimal places.
1. A study of the relation between the waistline and percent body fat in men yielded the data shown (waistline measurement in inches). waistline (x) 34.7 46.5 32.8 41.3 29.8 39.3 35.7 29.0 percent fat (y) 21.8 33.6 13.4 27.1 13.7 30.2 18.5 11.2 x = 36.1375 y = 21.1875 SSxx = 248.53875 SSay = 332.67375 SSyy = 494.30875 (a) Find the proportion of the variability in percent body fat that is accounted for by the size of the waistline. Explain fully. (b) Find the regression line for predicting y from x. (c) Construct a 95% confidence interval for the average percent body fat of all men whose waistline size is 34.0 inches. (d) test HO: Beta1 is 0 vs. Ha : Beta1 is not 0, compute the appropriate test statistic and p-value, then make your decision at a = 0.05. (e) Construct a 90% confidence interval for beta1. (f) Compute a 90% confidence interval for the average percent fat when waistline is 35.
Q2. A fast-food chain decided to carry out an experiment to assess the influence of advertising expenditure on sales. Different relative changes in advertising expenditure, compared to the previous year, were made in eight regions of the country, and resulting changes in sales levels were observed the accompanying table shows the results. Increase in advertising expenditure (%) 0 5 15 20 25 30 35 40 Increase in sales (%) 5 10 18 25 35 50 60 65 Determine the value of ∑X, ∑X2, ∑Y, ∑Y2, ∑XY. Where X represent independent variable and Y for dependent variable. [2] Determine and interpret the coefficient of correlation between the two variables. [1] Determine the value of regressions coefficients and write down the simple linear regression
6. Which of the following are true? Select all that apply. a. The coefficient of determination is the proportion of variation in the response variable that is explained by the regression line. b. We often use the symbol r to represent the coefficient of determination. c. In simple linear regression, the coefficient of determination equals the square of the linear correlation coefficient r. d. The closer the regression line comes to the data points, r should go to eleven.
The following data refers to the amount of caffeine (in mg) consumed by ten university students and their time to complete a practice test (in minutes) for a Economics Exam. Use attached Graph and Table to answer question below pls Describe the overall pattern of the relationship between caffeine amount and time to finish the practice exam in graph diagram provided. Does it follow a straight-line pattern? Is there a positive or negative association, or neither? How strong is the relationship?
10. The sign of the Pearson’s correlation coefficient (r) tells us what information? a. only the strength of the correlation (small, medium, or large) b. only the direction of the correlation (negative or positive) c. both the strength and direction of the correlation d. the strength, direction, and form of the correlation
5If the linear correlation coefficient between the weights (in kg) and heights (in inches) of 6 randomly selected males is 0.95, then 95% of the variation in weights of males can be explained by the linear correlation between height and weight? 1. True 2. False

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