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An accountant monitors the number of items produced per month by a company, together with the total production cost (RM). Table Q3 shows the data which is used to develop a simple regression model. Table Q3: Number of items and production cost Number of items (000) Production costs (000) 21 39 40 58 67 45 48 24 72 75 15 89 96 37 35 53 62 83 102 35 75 81 12 56 a) Sketch a scatter plot for the data. b) (i) Find the estimated regression line by using the least square methe (ii) Interpret the result in Q3(b)(i). (c) Predict the production cost when the number of item is 74000.

An accountant monitors the number of items produced per month by a company, together with the total production cost (RM). Table Q3 shows the data which is used to develop a simple regression model. Table Q3: Number of items and production cost Number of items (000) Production costs (000) 21 39 40 58 67 45 48 24 72 75 15 89 96 37 35 53 62 83 102 35 75 81 12 56 a) Sketch a scatter plot for the data. b) (i) Find the estimated regression line by using the least square methe (ii) Interpret the result in Q3(b)(i). (c) Predict the production cost when the number of item is 74000.

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
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23 An accountant monitors the number of items produced per month by a company, together with the total production cost (RM). Table Q3 shows the data which is used to develop a simple regression model. Table Q3: Number of items and production cost Number of items (000) Production costs (000') 21 40 39 38 48 67 24 45 72 75 89 96 15 35 37 53 62 83 81 102 12 35 56 75 a) Sketch a scatter plot for the data. b) (i) Find the estimated regression line by using the least square method. (ii) Interpret the result in Q3(b)(i). (c) Predict the production cost when the number of item is 74000.
Transcribed Image Text:23 An accountant monitors the number of items produced per month by a company, together with the total production cost (RM). Table Q3 shows the data which is used to develop a simple regression model. Table Q3: Number of items and production cost Number of items (000) Production costs (000') 21 40 39 38 48 67 24 45 72 75 89 96 15 35 37 53 62 83 81 102 12 35 56 75 a) Sketch a scatter plot for the data. b) (i) Find the estimated regression line by using the least square method. (ii) Interpret the result in Q3(b)(i). (c) Predict the production cost when the number of item is 74000.
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