Please answer the 3 questions below
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 answer the 3 questions below
Transcribed Image Text:An important application of regression analysis is in the estimation of cost. By
collecting data on volume and cost and using the least squares method to
develop an estimated regression equation relating volume and cost, one can
estimate the cost associated with a particular manufacturing volume. Consider
the following sample of monthly production volumes and total costs data for a
manufacturing operation for the year 2018.
Month
Production Volume (units)
Total Costs ($)
January 2018
February 2018
500
6,000
4,000
350
March 2018
450
5,000
April 2018
May 2018
550
5,400
600
5,900
June 2018
400
4,000
July 2018
August 2018
September 2018
400
4,200
350
3,900
400
4,300
October 2018
600
6,000
November 2018
700
6,400
December 2018
750
7,000
Which of the following is NOT necessarily true about the interpretation of the
value of b in the simple linear regression equation y = a + bx for this problem? *
The monthly total costs will increase by $7.6437 for every one-unit increase in the
production volume.
1.
II.
Since b> 0, there is a direct relationship between production volume and total
costs.
Because b> I, there is a very strong positive linear relationship between
production volume and total costs.
I.
O i and ii only
O i only
iii only
O ii and iii only
Which of the following statements are true about the dependent (or response)
and independent (or predictor) variables for the simple linear model in this
problem? *
Transcribed Image Text:Which of the following statements are true about the dependent (or response)
and independent (or predictor) variables for the simple linear model in this
problem? *
1.
Production volume is dependent on total costs.
The predictor and response variables are the production volume and total costs,
respectively.
The total costs can be projected using the simple linear regression equation if the
production volume is known.
II.
II.
i and ii only
i and iii only
ii and iii only
i, ii, and iii
Calculate the (Pearson) correlation coefficient between production volume and
total costs in this problem.
0.8391
0.9571
0.9160
0.9783
Which of the following is the most suitable interpretation of the (Pearson)
correlation coefficient between production volume and total costs in this
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