Please need answer asap and the graph and the data of the question is attached below

Market Share 0.248 0.256 0.267 0.253 0.267 0.267 0.265 0.255 0.262 0.261 0.265 Detail Voice 0.054 0.065 0.076 0.085 0.021 0.094 0.099 0.109 0.119 0.124 0.136 Week 1 2 3 4 5 5 6 7 8 9 10 11 The data available below describe spending by a major pharmaceutical company for promoting a cholesterol-lowering drug. The data cover 11 consecutive weeks and isolate an urban area. The variables in this collection are shares. The column Market Share is sales of this product divided by total sales for such drugs in the area. The column Detail Voice is the ratio of the number of promotional visits to doctors' offices for this drug to the number of promotional visits for all cholesterol-lowering drugs in the area. Formulate the SRM with Y given by the Market Share and X given by the Detail Voice and complete parts (a) through (d) below. Click here to view the data. Click here to view the SRM. The SRM is Y = + x (Round to three decimal places as needed.) (a) Identify the week associated with the outlying value marked with an x in the given graph. The figure shows the least squares fitted line. Does this week have unusually large sales given the level of promotion, or unusually low levels of promotion? Take a look at the timeplots to help you decide. The outlying value is for week . (Type a whole number.) Does this week have unusually large sales or unusually low levels of promotion? A. This week has unusually large sales. The level of promotion is fairly consistent. OB. This week has unusually low levels of promotion. The level of sales is fairly consistent. O C. This week has unusually large sales and unusually low levels of promotion. D. This week has unusually low levels of sales and promotion. (b) How does the fitted regression equation change if this week is excluded from the analysis? V to The intercept V to and the slope (Round to three decimal places as needed.) (c) The r of the fit gets larger and se gets smaller without this week; however, the standard error for by increases. Why? This week the variation in the variable. Without this case there is variation in and a larger standard error. (d) These are time series data. Do other diagnostics suggest a violation of the assumptions of the SRM? A. Since the timeplot of the residuals has no pattern and the Durbin-Watson statistic is near 2, there is no evidence of any violations. OB. Since the timeplot of the residuals has a pattern and the Durbin-Watson statistic is not near 2, there is evidence of a lurking variable and autocorrelation. OC. The timeplot of the residuals has no pattern, but the Durbin-Watson statistic is not near 2, so there is evidence of autocorrelation. D. The Durbin-Watson statistic is near 2, but the timeplot of the residuals has a strong pattern, so there is evidence of a lurking variable. 0.2707 Y 0.2404 0.14 x Market Share 0.248 0.256 0.267 0.253 0.267 0.267 0.265 0.255 0.262 0.261 0.265 Detail Voice 0.054 0.065 0.076 0.085 0.021 0.094 0.099 0.109 0.119 0.124 0.136 Week 1 2 3 4 5 5 6 7 8 9 10 11 The data available below describe spending by a major pharmaceutical company for promoting a cholesterol-lowering drug. The data cover 11 consecutive weeks and isolate an urban area. The variables in this collection are shares. The column Market Share is sales of this product divided by total sales for such drugs in the area. The column Detail Voice is the ratio of the number of promotional visits to doctors' offices for this drug to the number of promotional visits for all cholesterol-lowering drugs in the area. Formulate the SRM with Y given by the Market Share and X given by the Detail Voice and complete parts (a) through (d) below. Click here to view the data. Click here to view the SRM. The SRM is Y = + x (Round to three decimal places as needed.) (a) Identify the week associated with the outlying value marked with an x in the given graph. The figure shows the least squares fitted line. Does this week have unusually large sales given the level of promotion, or unusually low levels of promotion? Take a look at the timeplots to help you decide. The outlying value is for week . (Type a whole number.) Does this week have unusually large sales or unusually low levels of promotion? A. This week has unusually large sales. The level of promotion is fairly consistent. OB. This week has unusually low levels of promotion. The level of sales is fairly consistent. O C. This week has unusually large sales and unusually low levels of promotion. D. This week has unusually low levels of sales and promotion. (b) How does the fitted regression equation change if this week is excluded from the analysis? V to The intercept V to and the slope (Round to three decimal places as needed.) (c) The r of the fit gets larger and se gets smaller without this week; however, the standard error for by increases. Why? This week the variation in the variable. Without this case there is variation in and a larger standard error. (d) These are time series data. Do other diagnostics suggest a violation of the assumptions of the SRM? A. Since the timeplot of the residuals has no pattern and the Durbin-Watson statistic is near 2, there is no evidence of any violations. OB. Since the timeplot of the residuals has a pattern and the Durbin-Watson statistic is not near 2, there is evidence of a lurking variable and autocorrelation. OC. The timeplot of the residuals has no pattern, but the Durbin-Watson statistic is not near 2, so there is evidence of autocorrelation. D. The Durbin-Watson statistic is near 2, but the timeplot of the residuals has a strong pattern, so there is evidence of a lurking variable. 0.2707 Y 0.2404 0.14 x