The data is Income (available in the quiz directions), have two variables, consumption, andIncome (in 1,000 dollars). We want to predict consumption based on Income, i.e., Income isthe independent variable.Use Excel to calculate the regression equation to answer the question.The 85% confidence interval for the slope is:O (0.430997, 0.753221)(0.3683183, 0.8158995)O(0.40670, 0.77752)O (0.32167, 0.86255)(0.39397, 0.79025)O (0.24305, 19.30748)

To answer your question, based on the confidence interval provided, the correct option is:(0.430997,…

Answered: The data is Income (available in 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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The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins (b) x = 10 wins (c) x = 19 wins (d) x = 15 wins E Click the icon to view the table of numbers of wins and earned run average. The equation of the regression line is y =x+ (Round to two decimal places as needed.) Construct a scatter plot of the data and draw the regression line. Choose the correct graph below. OA. OB. OC. OD. AERA 6- AERA AERA AERA 2- 2- 2- 0- 0- 12 18 24 12 18 24 12 18 24 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below…
You are studying how a penguin's flipper length (in mm) explains its body mass (in grams) using linear regression. You choose a non-directional alternative to be safe. You calculate an R2=0.7621. What is the interpretation of this value? O76.21% of the variability in body mass is explained by the flipper length. O 76.21% of the variability in flipper length is explained by the body mass. 0 Flipper length and body mass have a positive relationship becase R² is positive O76.21% of the body mass values will be inside the confidence interval
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were: y=ax+b a=-0.634 b=30.709 r2=0.948676 r=-0.974 Use this to predict the number of situps a person who watches 10.5 hours of TV can do (to one decimal place)
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins (b) x = 10 wins (c) x = 19 wins (d) x = 15 wins Click the icon to view the table of numbers of wins and earned run average. The equation of the regression line is y = x+. (Round to two decimal places as needed.)
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 41 inches, Is the result close to the actual weight of 273 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 40 53 38 43 44 58 227 360 153 206 234 414 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y = + x (Round to one decimal place as needed.)
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 58 inches. Is the result close to the actual weight of 672 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 46 57 53 41 40 40 384 580 542 358 306 320
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins (c) x = 19 wins (d) x = 15 wins (b)x= 10 wins Click the icon to view the table of numbers of wins and earned run average. .. The equation of the regression line is y=x+ X+ (Round to two decimal places as needed.) Construct a scatter plot of the data and draw the regression line. Choose the correct graph below. OA. B. O C. O D. AERA AERA 6+ Q AERA 6+ 4- 4- 2- 2- 0- 6 12 18 24 0 12 18 24 6 12 18 24 Wins 12 18 24 Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct…
The data show systolic and diastolic blood pressure of certain people. Find the regression equation, letting the systolic reading be the independent (x) variable. If one of these people has a systolic blood pressure of 125 mm Hg, what is the best predicted diastolic blood pressure? Systolic Diastolic Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? ŷ-+x (Round to two decimal places as needed.) What is the best predicted diastolic blood pressure? y=(Round to one decimal place as needed.) C 148 115 82 83 82 136 115 127 128 140 97 60 65 93 145 101 108
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.145 b=20.742 r?=0.508369 r=-0.713 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)
For the relationship between Calories and Carbs, here is the equation of the line of best fit: nts Regression Equation: Calories = 2.36 + 4.432 Carbs The range of Carb values in the dataset was between 17 and 47 Carbs. What wourd you say if asked to predict the number of Calories if a cereal had 60 Carbs? Type your response in the text box..
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 4141 inches. Is the result close to the actual weight of 273273 pounds? Use a significance level of 0.05. Chest size (inches) 4040 5353 3838 4343 4444 5858 Weight (pounds) 227227 360360 153153 206206 234234 414414 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. Question content area bottom Part 1 What is the regression equation? ModifyingAbove y with caretyequals=enter your response hereplus+enter your response herex (Round to one decimal place as needed.) Part 2 What is the best predicted weight of a bear with a chest size of 4141 inches? The best predicted weight for a bear with a chest size of 4141 inches is enter your response here pounds. (Round to one…
Critical Values of the Pearson Correlation Coefficientr a= 0.05 a= 0.01 NOTE: To test H, p-0 against H,: p#0, reject H, jr the absolute value of r is preater than the critical yalue in the table. 0.950 0.990 0.959 0.917 0.875 5 0.878 6 0.811 0.754 7 0.834 0.798 8 0.707 0.666 0.632 0.602 9 10 0.765 11 0.735 12 0.576 0.708 13 0.553 0.684 0.532 0.514 0.497 0.482 14 0.661 15 0.641 16 0.623 17 18 0.606 0.590 0.468 19 0.456 0.444 0.575 20 0.561 25 0.396 0.505 0.463 30 0.361 35 0.335 0.430 40 0.312 0.402 45 0.294 0.279 0.378 0.361 50 60 0.254 0.330 70 80 0.236 0.305 0.286 0.220 90 0.207 0.196 0.269 100 0.256 a= 0.05 a=0.01

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