QUESTION 19A researcher is interested in studying older adults in Florida. It is appropriate for him to use a mean to describe which of thefollowing?O the sex of a typical older adult in FloridaO the race of a typical older adult in FloridaO the average age of older adults in FloridaO the marital status of a typical older adult in FloridaQUESTION 20The hours of sleep per night (x) and minutes of physical activity per week (y) were calculated for 200 teachers. Theregression equation for the analysis wasy3D290.2093 +3.502052xUse the regression analysis to predict minutes of physical activity per week for a teacher who sleeps an average of 10 hoursper night.250 minutes per week290minutes per weexSave Al AnsweClick Save and Subynit co sae and submt.Chck Save All Anscers to save all answersbre Chck Save All Answers to save all ansuers39°F Cloudy

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Answered: QUESTION 19 A researcher is interested…

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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Home Sale Prices. Regarding the relationship between the sale price of a home and the predictor variables size in square feet and type of roof (tile or non-tile). In that exercise, we considered the regression of price on size and roof, the indicator variable for type of roof. a. Obtain a plot of price versus size with different plot symbols for homes having a tile roof and for homes having a non-tile roof. Based on this plot, does it appear that roof is a useful predictor variable? Explain your answer. b. Obtain the regression analysis of price on size and roof. Conduct the t-tests for the individual utility of the two predictor variables at the 5% level of significance. Interpret your results. c. Based on the output in part (b), obtain the individual regression equations relating price to size for homes having tile roofs and for homes having non-tile roofs. d. Obtain plots of residuals versus fitted values, residuals versus size, residuals versus roof, and a normal probability plot…
Let x be the weight of a car (in hundreds of pounds), and let y be the miles per gallon (mpg). Suppose a car weighs 3800 pounds. What does the data forecast for the miles per gallon expected? x= 27 44 32 47 23 40 34 52 y= 30 19 24 13 29 17 21 14 State the correlation coefficient and state the regression lin equation.
Consider the following data set, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. hours/week X 6.5 10 11 12.5 13 14.5 15 17.5 19.5 20 Grade y 66.1 63 71.4 72.5 79.2 94.3 95 91.5 100 98 The regression equation is y = 3x + 41.3. a) Explain what the value of the slope means in this situation, where y is the final grade in a math class and is the average number of hours the student spent working on math each week. O For each additional hour per week that a student studies on average, their final grade will be about 3 points. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points higher. For each additional hour per week that a student studies on average, their final grade will be about 3 points higher. O For each additional hour per week that a student studies on average, their final grade will be about 41.3 points. b) Explain what the value of the…
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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.
A researcher is interested in examining the relationship between spousal abuse and child abuse. Specifically, they are interested in determining whether there is a predictive relationship between spousal abuse and child abuse in 5 county social services offices. Calculate the linear regression line for the following data. Note you have already calculated the first step to this analysis (Pearson's Correlation)
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Previous question K The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 272 pounds? Use a significance level of 0.05. $ Chest size (inches) Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. O What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest şize of 40 inches? The best predicted weight for a bear with a chest size of 40 inches is pounds. (Round to one decimal place as needed.) le the result cloen to the actual uninht of 272 nounde? S Copyright © 2022 Pearson Education Inc. All rights reserved. Terms of Use | Privacy Policy. Permissions | Contact Us % F 5 41 54 44 328 528 418 T V & Y B 55 39 51 C 580 296 503 H a 4 N 00 8 144 9 N K M N ? ► 11 L…
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Item9 eBook Item 9 The following regression output was obtained from a study of architectural firms. The dependent variable is the total amount of fees in millions of dollars. Predictor Coefficient SE Coefficient t p-value Constant 9.601 3.153 3.045 0.010 x1 0.221 0.110 2.009 0.000 x2 − 1.168 0.577 − 2.024 0.028 x3 − 0.106 0.073 − 1.452 0.114 x4 0.631 0.361 1.748 0.001 x5 − 0.043 0.029 − 1.483 0.112 Analysis of Variance Source DF SS MS F p-value Regression 5 1,844.31 368.9 9.37 0.000 Residual Error 56 2,205.62 39.39 Total 61 4,049.93 x1 is the number of architects employed by the company. x2 is the number of engineers employed by the company. x3 is the number of years involved with health care projects. x4 is the number of states in which the firm operates. x5 is the percent of the firm’s work that is health…

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