$FL2@(#) SPSS DATA FILE MS Windows 17.0.0 ##########################Y@25 Feb 1017:49:12 ###########################AGE ####Age of customers########################ORDERS !###Number of orders placed in a year ############################################################## #######################################################AGE=Age ORDERS=Orders############################################ ###windows-1252#######mpsgmpgjpjmjmpjmmpjmmggsp###### $FL2@(#) IBM SPSS STATISTICS DATA FILE 64-bit MS Windows 20.0.0 ################ #########Y@22 Oct 1418:39:12 ###########################SALES ####Sales in thousands of dollars ########################ADS ###Number of Ads ########################COUPONVA####Dollar value of coupon ############################################################## ############ ########################################### #######(###SALES=Sales ADS=Ads COUPONVA=CouponValue######################## ###################<###Sales:$@Role('0' )/Ads:$@Role('0' )/CouponValue:$@Role('0' )############ ###windows-1252##############@d#@######)@j? ######)@6 @######)@|?##### R@#######@#######@#####`i@s######)@d#@#####`Y@|? #####E@#######@#######@s#######@j? #######@#####E@#######@s####|?j? $FL2@(#) SPSS DATA FILE MS Windows 17.0.0 ################ #########Y@01 Mar 1022:08:25 ###########################SALES ####Sales in thousands of dollars ########################PRICE ####Price in dollars########################ADS ####Number of Ads Placed############################################################## ############ ########################################### ###########SALES=Sales PRICE=Price ADS=Ads######################## ################### ###windows-1252#######qg# hc@?4#6<@@######? Qc@?qelg#H.wW@0*##;@?`TR'V`@eomn{/L Z@333333?#(u]@######?gpe8gDiop@@?[8b@######? K#=V@ll####X5;W@######? $FL2@(#) SPSS DATA FILE MS Windows 17.0.0 ##########################Y@25 Feb 1018:04:58 ###########################PRICE ####Price per pound of steak in dollars ########################SALES .###Weekly sales expressed as thousands of dollars ############################################################## #######################################################PRICE=Price SALES=Sales############################################ ###windows-1252#######uB m #@&jC@#@B m #@&D@B m @h~}\\UU@@#@K#GUU>@]#8:#@d$I#@#####D@p| m#@}\\UU#C@*#uP##@?@<#A#@u##@K#GUUU;@i| #######:@#.#@k##@#####3@ Assignment 3 (Individual) 60 points 1) A direct marketing company is interested in finding the relationship between age of their customers and the number of orders customers place in a given year. The company randomly samples 25 customers and records their age and computes the total orders they placed last year. The data is in age.sav. Run a simple linear regression to explain the impact of age on number of orders. Express the model you are estimating and state the null and alternate hypothesis. Given the results of your estimation, what is the expected number of orders placed by a 55 year old customer? 2) A meat processing company is interested in understanding the relationship between the price of their steak (per pound) and the total sales of steak in a week. The company records the average price charged (in dollars) per pound of steak and the total sales (in thousands of dollars) per week for 15 weeks. The data is in steak.sav. Run a simple linear regression to explain the impact of price on weekly sales. Express the model you are estimating and state the null and alternate hypothesis. Given the results of your estimation, what is the expected weekly sales when the company charges $3.75 for a pound of steak? 3) A consumer packaged goods company puts out several advertisements every month in the local news paper and includes a discount coupon with the advertisements. The company has collected data on the number of advertisements it ran for the last 12 months as well as the dollar value of the coupon offered in each of the last 12 months. The sales (in thousands of dollars) is also recorded. The company wishes to investigate the impact of advertising and coupon value on sales. The company suspects that advertising and coupon value have a positive impact on sales. Express the regression model that the company must use, state the null and alternate hypothesis, estimate the model and provide interpretation. Given the results of your estimation, what are the expected sales in a month where 8 advertisements were put out using a $3 coupon. The data is in coupon.sav. 4) The price of the \"Spirit of the Devil\" brand beer fluctuates from month to month due to the change in raw material prices and other factors. The company that sells this beer also advertises several times a month. The company wishes to investigate the impact of price and advertising on beer sales and collects monthly sales data (in thousands of dollars), number of advertisements per month and the average monthly price of beer (in dollars). The company suspects that higher prices lead to lower sales and more advertising leads to greater sales. In addition, the company also expects that the negative impact of prices on sales is affected by the level of advertising such that higher levels of advertising may lower the negative effect of price. Express the regression model that the company must estimate to test their intuition, state the relevant hypothesis, estimate the model and provide interpretation. Given the results of your estimation, predict the beer sales when the company spends on 12 advertisements and prices the beer at $1.25. The data is in spirit.sav . Note: Assume alpha=0.05 for all questions