**Educational Task Description:**The data provided represents 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.**Instructions:**1. **Find the Equation of the Regression Line:** - Utilize the provided data to calculate the regression line equation, which will predict the earned run average $ y $ as a function of the number of wins $ x $.2. **Construct a Scatter Plot:** - Plot the data points on a graph, representing the number of wins on the x-axis and the earned run average on the y-axis. - Draw the regression line on this scatter plot.3. **Use the Regression Equation for Predictions:** - Apply the regression equation to predict the value of $ y $ for each of the given $ x $-values: (a) 5 wins, (b) 10 wins, (c) 21 wins, (d) 15 wins. - Determine if predictions are meaningful for each $ x $-value. If not, provide an explanation.**Click on the icon to view the table of numbers of wins and earned run average.****Equation Format:**The equation of the regression line is $ \hat{y} = [\text{intercept}] + [\text{slope}] \times x $.*(Round to two decimal places as needed.)* The image shows a statistical analysis activity focused on constructing a scatter plot and drawing a regression line using data from eight baseball pitchers regarding their number of wins and earned run averages (ERA) from a recent season.**Instructions:**1. **Data Table:** - The table provides the data points where the number of wins (x) and ERA (y) are paired: - Wins, x | Earned run average, y - 20 | 2.71 - 18 | 3.22 - 17 | 2.56 - 16 | 3.76 - 14 | 3.92 - 13 | 3.94 - 11 | 3.87 - 9 | 5.142. **Scatter Plot and Regression Line:** - Students are instructed to construct a scatter plot of the data and draw the regression line.3. **Equation of the Regression Line:** - The equation format is given as $ y = \square x + \square $. - Students must calculate and input the slope and intercept values, rounding to two decimal places as necessary.4. **Predictive Analysis:** - Using the regression equation, predict the ERA for: - (a) x = 5 wins - (b) x = 10 wins - (c) x = 21 wins - (d) x = 15 wins - Explain whether the predictions are meaningful based on the x-values.This exercise integrates concepts of linear regression and data analysis, helping students understand relationships between two quantitative variables.

Given Observation and calculation Wins x Earned run average y X2 Y2 xy 20 2.71…

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= 21 wins numbers of wins and earned run average (d) x= 15 wins Click the icon to view the table The equation of the regression line is y =x+ (Round to two decimal places as needed.)

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= 21 wins numbers of wins and earned run average (d) x= 15 wins Click the icon to view the table The equation of the regression line is y =x+ (Round to two decimal places as needed.)

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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