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Now say a simple linear regression model is fit to the data. Fitting the simple linear regression model, the estimated regression equation is: Ỹ; = 6.4285 +1.0534X; or distance; 6.4285 +1.0534heightį d. What is the predicted length of the jump for an athlete who is 72 inches tall? e. Interpret what the 1.0534 represents. f. Does the intercept of 6.4285 inches have any useful interpretation to the coach? = 2. A high school track & field coach wanted to assess the relationship between an athletes height and how far they can jump in the long jump event (both in inches). They collect data on each athletes height and how far they can jump. Let the height in inches of the athlete be the explanatory variable (X) and the distance in inches of the jump be the response (Y). The scatterplot of the data based on 32 athletes is as follows: distance 88 86 84 82 80 78 00 O o 70 Scatter Plot 72 height 00 000 00 00 8 74 8 O ¥75 76 一念 78

Now say a simple linear regression model is fit to the data. Fitting the simple linear regression model, the estimated regression equation is: Ỹ; = 6.4285 +1.0534X; or distance; 6.4285 +1.0534heightį d. What is the predicted length of the jump for an athlete who is 72 inches tall? e. Interpret what the 1.0534 represents. f. Does the intercept of 6.4285 inches have any useful interpretation to the coach? = 2. A high school track & field coach wanted to assess the relationship between an athletes height and how far they can jump in the long jump event (both in inches). They collect data on each athletes height and how far they can jump. Let the height in inches of the athlete be the explanatory variable (X) and the distance in inches of the jump be the response (Y). The scatterplot of the data based on 32 athletes is as follows: distance 88 86 84 82 80 78 00 O o 70 Scatter Plot 72 height 00 000 00 00 8 74 8 O ¥75 76 一念 78

MATLAB: An Introduction with Applications
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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Please solve f and g. 

Now say a simple linear regression model is fit to the data. Fitting the simple linear regression model, the estimated regression equation is: Ỹ; = 6.4285 +1.0534X; or distance; 6.4285 +1.0534heightį d. What is the predicted length of the jump for an athlete who is 72 inches tall? e. Interpret what the 1.0534 represents. f. Does the intercept of 6.4285 inches have any useful interpretation to the coach? =
Transcribed Image Text:Now say a simple linear regression model is fit to the data. Fitting the simple linear regression model, the estimated regression equation is: Ỹ; = 6.4285 +1.0534X; or distance; 6.4285 +1.0534heightį d. What is the predicted length of the jump for an athlete who is 72 inches tall? e. Interpret what the 1.0534 represents. f. Does the intercept of 6.4285 inches have any useful interpretation to the coach? =
2. A high school track & field coach wanted to assess the relationship between an athletes height and how far they can jump in the long jump event (both in inches). They collect data on each athletes height and how far they can jump. Let the height in inches of the athlete be the explanatory variable (X) and the distance in inches of the jump be the response (Y). The scatterplot of the data based on 32 athletes is as follows: distance 88 86 84 82 80 78 00 O o 70 Scatter Plot 72 height 00 000 00 00 8 74 8 O ¥75 76 一念 78
Transcribed Image Text:2. A high school track & field coach wanted to assess the relationship between an athletes height and how far they can jump in the long jump event (both in inches). They collect data on each athletes height and how far they can jump. Let the height in inches of the athlete be the explanatory variable (X) and the distance in inches of the jump be the response (Y). The scatterplot of the data based on 32 athletes is as follows: distance 88 86 84 82 80 78 00 O o 70 Scatter Plot 72 height 00 000 00 00 8 74 8 O ¥75 76 一念 78
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