Note: this file corresponds to a random sample of 30 sales transactions. Not 100.... Please use excel functions such as

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answerhappygod
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Note: this file corresponds to a random sample of 30 sales transactions. Not 100.... Please use excel functions such as

Post by answerhappygod »

Note: this file corresponds to a random sample of
30 sales transactions. Not 100.... Please use excel
functions such as ANOVA and Regression analysis when necessary.
Thank you!
Note This File Corresponds To A Random Sample Of 30 Sales Transactions Not 100 Please Use Excel Functions Such As 1
Note This File Corresponds To A Random Sample Of 30 Sales Transactions Not 100 Please Use Excel Functions Such As 1 (103.07 KiB) Viewed 21 times
Case Scenario: Congratulations. You have just inherited your uncle's business, which is a clothing store. Although the business was successful, your uncle was a "seat of the pants" type of businessman. There was never any sales analysis conducted concerning, e.g. determining the effectiveness of promotional policies. You intend to analyze past sales data to gain insight into the business operations. The following data in this file corresponds to a random sample of 100 sales transactions that took place over the previous year. Because all transactions took place during the previous year and all transactions took place on Saturdays, on non-holiday weekends, you are confident that seasonal and cyclical effects are absent from the data. Case Analysis: (use excel functions when necessary. Thank yor) Based on this sample, you seek to answer the following questions: 1. What is the lag effectiveness of current advertising policy? In answering this question, consider the following: a) Does the average amount of sales differ 0, 1, and 2 weeks after an advertisement? (a=.05) b) Test the hypothesis that the average amount of sales o weeks after an advertisement is larger than the average amount of sales 2 weeks after an advertisement. (a-05) 2. Can multiple regression be used to "profile" a sale and determine whether a customer is spending more or less than anticipated, i.c, to predict the amount of a sale given the profile of a sale? To answer this question, conduct a regression analysis, *) How does the regression analysis support (or not support) your answers above?
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