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two decimal places as needed.) e slope is e slope is expla e intercent is For each incre . For each $1 in e intercept of the regression line and expla two decimal places as needed.) A free turk

two decimal places as needed.) e slope is e slope is expla e intercent is For each incre . For each $1 in e intercept of the regression line and expla two decimal places as needed.) A free turk

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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Hello I need help for solving both parts for problem d, thank you.

d. Report the slope and intercept of the regression line and explain what they show. If the intercept is not appropriate to report, explain why. Report the slope of the regression line and explain what it shows. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to two decimal places as needed.) OA. The slope is B. The slope is For each increase of 1 pound in the weight of the turkey, the cost goes up by an average of $ For each $1 increase in the cost of the turkey, the turkey's weight goes up by an average of pound(s). Report the intercept of the regression line and explain what it shows. Select the correct choice below and fill in the answer box(es) to complete your choice. (Round to two decimal places as needed.) A. The intercept is B. The intercept is OC. The intercept is D. The intercept is A free turkey has a predicted average weight of A turkey that weighs 0 pounds has a predicted average cost of $ The interpretation of the intercept is inappropriate, because it is not possible to have a turkey that weighs 0 pounds. The interpretation of the intercept is inappropriate, because it is not possible to have a free turkey. pound(s).
Transcribed Image Text:d. Report the slope and intercept of the regression line and explain what they show. If the intercept is not appropriate to report, explain why. Report the slope of the regression line and explain what it shows. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to two decimal places as needed.) OA. The slope is B. The slope is For each increase of 1 pound in the weight of the turkey, the cost goes up by an average of $ For each $1 increase in the cost of the turkey, the turkey's weight goes up by an average of pound(s). Report the intercept of the regression line and explain what it shows. Select the correct choice below and fill in the answer box(es) to complete your choice. (Round to two decimal places as needed.) A. The intercept is B. The intercept is OC. The intercept is D. The intercept is A free turkey has a predicted average weight of A turkey that weighs 0 pounds has a predicted average cost of $ The interpretation of the intercept is inappropriate, because it is not possible to have a turkey that weighs 0 pounds. The interpretation of the intercept is inappropriate, because it is not possible to have a free turkey. pound(s).
7. The accompanying table shows a list of the weights and costs of some turkeys at different supermarkets. Complete parts (a) through (f) below. a Make a scatterplot with weight on the x-axis and cost on the v-axis Include the regression line on the scatterplot Weight (pounds) 12.3 18.8 20.4 16.5 15.8 10.7 Cost $17.08 $23.84 $26.82 $19.85 $23.29 $9.14 U
Transcribed Image Text:7. The accompanying table shows a list of the weights and costs of some turkeys at different supermarkets. Complete parts (a) through (f) below. a Make a scatterplot with weight on the x-axis and cost on the v-axis Include the regression line on the scatterplot Weight (pounds) 12.3 18.8 20.4 16.5 15.8 10.7 Cost $17.08 $23.84 $26.82 $19.85 $23.29 $9.14 U
Expert Solution
Introduction

You can use a statistical technique called simple linear regression to comprehend the relationship between two variables,

x and y.

The formula for the line of best fit is written as:

y^=b0+b1x

where ŷ is the predicted value of the response variable, b0 is the y-intercept, b1 is the regression coefficient, and x is the value of the predictor variable.

 

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