Linda is a heavy coffee drinker and a friend recommends that she try Sunrise Coffee, a new coffee house in town, because it sells delicious coffee. Linda replies that she really prefers to drink her coffee in the peace and quiet of her own home. One morning, Linda is running late and doesn't have time to make herself a cup of coffee, so she stops by Sunrise and is greeted by a cheerful staff and a great-tasting coffee, all of which put Linda in a good mood. Upon arriving at work, a coworker comments on her alert, up-beat attitude that morning. Linda replies that it must be the great weather that day, sunshine after a week of solid rain. The following morning, Linda recalls what a pleasant experience she had at Sunrise and decides to go again. -In the COFFEE MINI CASE, Linda's initial resistance to the idea of trying Sunrise Coffee arises from which of the following multiattribute attitude models? A) attitude-toward-behavior model
B) trying-to-consume model
C) attitude-toward-object model
D) attitude-toward-consumer model
E) attitude-toward-the-ad model

Which alternative accounting method allows farmers to record expenses and incomes in the year in which they sell their yield? gaap allows for the method, which permits farmers to subtract the expenses of producing the crop in the year in which they sell the yield and earn the revenue.

Select the correct answer a research organization conducts certain chemical tests on samples. they have data available on the standard results. some of the samples give results outside the boundary of the standard results. which data mining method follows a similar approach? o a. data cleansing ob. network intrusion o c. fraud detection od. customer classification o e. deviation detection

An important application of regression analysis in accounting is in the estimation of cost. by collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. consider the following sample of production volumes and total cost data for a manufacturing operation. production volume (units) total cost ($) 400 4000 450 5000 550 5400 600 5900 700 6400 750 7000 compute b 1 and b 0 (to 2 decimals if necessary). b 1 b 0 complete the estimated regression equation (to 2 decimals if necessary). = + x what is the variable cost per unit produced (to 1 decimal)? $ compute the coefficient of determination (to 4 decimals). note: report r 2 between 0 and 1. r 2 = what percentage of the variation in total cost can be explained by the production volume (to 2 decimals)? % the company's production schedule shows 500 units must be produced next month. what is the estimated total cost for this operation (to 2 decimals)? $