Question 2 - simple linear regression The following is the simple linear regression model: y= Bo+ Bix For a given set of

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Question 2 Simple Linear Regression The Following Is The Simple Linear Regression Model Y Bo Bix For A Given Set Of 1 (36.14 KiB) Viewed 16 times

Question 2 Simple Linear Regression The Following Is The Simple Linear Regression Model Y Bo Bix For A Given Set Of 2 (133.83 KiB) Viewed 16 times

Question 2 - simple linear regression The following is the simple linear regression model: y= Bo+ Bix For a given set of (xi, yd), i = 1,... k, the following best-fit equation can be used to calculate the Bo and B1 values, Ek-1(x,* yi)-(k *** y) Bi X-1 (x²)-(k+x2) Bo =ỹ - Bix where (Xi, yd) are observed values, ã is the mean = ZX-1 X3), õ is the mean = 2X=1 yi), yi Σ), and the corresponding line is called the line of best fit. i= k i=1
Radio ads 21 3 Data 4 Jan 5 Feb 6 Mar 7 Apr 8 May 9 Jun 10 Jul 11 Aug 12 Sep 13 Oct 14 Nov 15 Dec 180 50 195 96 44 171 135 120 75 106 198 Revenue $8,350.0 $22,755.0 $13,455.0 $21,100.0 $15,000.0 $12,500.0 $20,700.0 $19,7220 $16,115.0 $13,100.0 $15,670.0 $25,300.0 a) Plot on a 2-dimensional graph the above data with “Radio ads” on x-axis, “Revenue" on y-axis. Assuming there is a linear relation between “Revenue” and “Radio ads”. Make a guess of the line of best fit Lg in the form of y=kx+b for the above 12 points. Draw the guessed best-fit line on the coordinate system as well. b) Manually calculate the Bo and B. for the linear regression model using the formula given above. Draw the line of best fit Le based on the calculated Bo and Bi. c) The least-squares error is defined as below: - 6 = 2k yi - Vy - y) = where ġi is the predicted value (through the best fit line) for a given Xị, and €;= (yi - Wi). Compute the least-squares errors for both Lg and Le. Compare which line has a smaller least-squares error.