Case scenario: Ice-Vanilla Fashion Line

Ice-vanilla (IV) fashion line is a leading force in men’s and women’s fashion in Australia. Ice-vanilla (IV) stores bring customers the latest and inspired designs from the world’s fashion centers. The chain recently ran a promotion in which promotional codes were sent (via email and/or mail) to customers who are members of IV priority club throughout the country; these customers are referred to as the “VIP”, and they were invited to use their promotional codes in store on the 23rd of December 2013. The store collected data for a sample of 200 in-store credit card transactions at branches across the country on 23rd December 2013.
Customers who made a purchase, but did not use a promotional code are referred to as “RE” (i.e. regular). These customers did not receive a promotional code. Therefore, it can be concluded that the sales made to customers who present promotional codes (VIP customers) as sales the store would not otherwise make.
The CEO would like to use this sample data to learn about its customers, and to evaluate the effectiveness of the recent promotion program involving discount codes.
In the spreadsheet data file (called : Data Ice-Vanilla Stores) “Net Sales” refers to the total amount ($) charged to the credit card. “RE” refers to regular customers and “VIP” refers to customers who are members of royalty club. Information on costumer’s age, gender, marital status and location is also provided in the spreadsheet.
Imagine that you, as nationwide sales manager in IV, are asked by the CEO to report back on the indicators of sales force including the recent promotional program. As a result you need to prepare a statistical report (as guided by your lecturer on LearnJCU), and use the method of descriptive statistics you learned so far to summarise the data, and comment on your findings. In preparation of this report, you must use excel to generate results.
At minimum your report should address the following questions:
1- What are the variables in this database (name them), what scale of measurement is used for each variable, and what are the types of these variables?
2- Is the data collected in this sample cross-section or time series? Explain your answer.
3- Provide a table in which you summarise complete descriptive statistics on “net sales” (including but NOT limited to: measures of central location, measures of variability, etc.), then use the information in the summary table you prepared to calculate the coefficient of variation for “net Sales”. What insights you could potentially gain from these results?
4- Develop complete frequency table/s to make inferences on the “gender” and the “marital status” of costumers in the sample data. Carefully interpret your table/s.
5- Calculate the correlation coefficient between “age” and “net sales”. Interpret the result.
6- Create a bar chart to show comparisons between types of credit cards used in the sample data (where the vertical axis is the frequency and horizontal axis represents card types).
7- Create another bar chart to show comparisons between types of customers in the sample data, using your findings for this question; do you think the promotional program has been effective and/or successful? Explain.