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 theequation 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, ifmeaningful. 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 winsClick the icon to view the table of numbers of wins and earned run average.The equation of the regression line is y =(Round to two decimal places as needed.)X +0 Wins, x201817161412119Earnedrun average,y2.673.282.563.783.784.353.865.01

Answer Given,x = 20, 18, 17, 16, 14, 12, 11, 9y = 2.67, 3.28, 2.56, 3.78, 3.78, 4.35, 3.86, 5.01

Answered: The accompanying data are the number of…

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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Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 7.
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…
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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 Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…
The file Galton on D2L contains the 928 observations Francis Galton used in 1885 to estimate the relationship between the heights of parents and the heights of their children. The column Children refers to the height (in inches) of a child, and the column Mid-Parents refers to the average height (in inches) of the mother and father of that child. You can download this file into Excel and Minitab. a. Calculate the regression Height of Children = a +b (Height of Mid-Parents). b. Calculate the average for Height of Children, and calculate the average Height of Mid-Parents. c. Create a new variable in Minitab which is the Height of Children measured in terms of deviations from its mean. Call this new variable y. Also, create a new variable in Minitab with is the Height of Mid-Parents measured in terms of deviations from its mean. Call this new variable x. Calculate the regression y = a + bx. You can create the new y and x variables in Excel of Minitab, whichever you find more convenient.…
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