Please may I get help on Question 2 (I included the question 1 as reference)

QUESTION 2 [20] The following data was considered in Assignment 01, Question 1, and a graphical approach was used to assess first order autocorrelation in residuals. year month time (t) sales (yr) 1 1 1 200 1 2 2 21 1 1 3 3 203 1 4 4 247 1 5 5 239 1 6 6 269 1 7 7 31 1 1 8 8 262 1 9 9 260 1 1O 1 0 256 1 1 1 1 1 261 1 12 1 2 288 2 1 1 3 296 2 2 1 4 276 2 3 1 5 305 2 4 1 6 308 2 5 1 7 356 2 6 1 8 393 2 7 1 9 363 2 8 20 386 2 9 21 443 2 1O 22 308 2 1 1 23 365 2 12 24 391 STA2604I01 2/3I2021 (2.1) Use a formal test statistic to assess whether the residuals are positively or negatively auto- correlated. (1 6) (2.2) Do you reach the same conclusion as the one reached in Assignment 01, Question 1, part (1 .4)(e)? Explain your answer. (4) QUESTION 1 [32] Describe the usefulness of following statistics and indicate how they are calculated: (1.1) The variance inflation factor. (4} (1.2] The adjusted coefficient of determination. (4] (1.3] The C-statistic. (4] (1.4} The table below describes the sales (yr) of a certain product in two consecutive years. As- sume that the simple linear regression model y: = 10 + 81: + 6. provides the trend of the data. year month time (I) sales (yr) 1 1 1 200 1 2 2 21 1 1 3 3 203 1 4 4 247 1 5 5 239 1 6 6 269 1 7 7 31 1 1 8 8 262 1 9 9 260 1 1 0 1 0 256 1 1 1 1 1 261 1 1 2 1 2 288 2 1 1 3 296 2 2 1 4 276 2 3 1 5 305 2 4 1 6 308 2 5 1 7 356 2 6 1 8 393 2 7 1 9 363 2 8 20 386 2 9 21 443 2 1 0 22 308 2 1 1 23 365 2 1 2 24 391 (a) Calculate the point estimates fig and :8] of ,30 and 81, respectiver Then write down the fitted model. Do not use Excel built-in routines for regression, but you can use Excel as a calculation spreadsheet. (8} (b) Use the results in part (a) to calculate the fitted values 3?; of the data. Insert the fitted values in the table after rounding them to the nearest integer. (4] (0) Calculate the residuals 1rr = y, 3;}. (4) (d) Plot the residuals r; versus times I. Use Excel for the plot. (2) (e) Do the plot of residuals indicate first order autocorrelation in the data? If so, which type of autocorrelation is displayed? Explain your answer without using a formal test for autocorrelation. (2]