Assignment

Learning Outcome

Apply quantitative reasoning skills to analyse business performance.

This assignment assesses the ability to use the appropriate technique to analyse the data, correctly interpret the analysis output and draw appropriate conclusions.

Apply quantitative reasoning skills to analyse business performance.

This assignment assesses the ability to use the appropriate technique to analyse the data, correctly interpret the analysis output and draw appropriate conclusions.

General Description / Requirements

The assignment requires that you analyse a data set, interpret and draw conclusions from your analysis, and then convey your conclusions in a written email. The assignment must be completed individually. The assignment, together with the appropriate Faculty assignment attachment sheet, must be submitted by the due date electronically in CloudDeakin. When submitting electronically, you must check that you have submitted the work correctly by following the instructions provided in CloudDeakin. Please note that we will NOT accept any hard copies or assignments submitted via email.

The assignment uses the file A1.xlsx which can be downloaded from CloudDeakin. Analysis of the data requires the use of techniques studied in Topics 1 to 5.

Scenario
You are Alex Cassidy, a business analyst who works for the BLITZ department store chain in their Research and Analysis department. You have been asked by the General Manager, Ms Jacinta Liu, to analyse a random sample of data collected from a recent survey of 300 randomly selected customers shopping in our stores. Her email making this request of you is reproduced below.

Email from the GM

To: Alex Cassidy

From: Jacinta Liu

Subject: Analysis of the BLITZ Department store data

Dear Alex,

Regarding the recent survey of the 300 customers in three major cities of Australia, the marketing department requires answers to the following questions. Your responses will be used as part of a report to senior management comparing customer habits and characteristics across the three cities.

1. Regarding the age of our customers and the amount they spent in our stores.

a. Can you provide a profile of our customers' age please?

b. Is there any evidence to suggest any differences in the average age of customers between the three cities?

c. Generally speaking, can we make the claim that the average amount spent per visit by all our customers is less than $105?

d. Is the amount of money spent per visit influenced by the age of the customer?
2. Regarding the shopping habits of our customers and their usage of the beauty sections within our department stores.

a. There have been some excellent instore promotions recently. Can you provide an estimate of the proportion of customers who shop in the beauty section in each of the three cities?

b. Do we have enough evidence to claim that the proportion who do shop in the beauty sections of all of our stores, could now be more than 48%?

c. Given that some of our customers are female, please indicate the likelihood that they might shop in the beauty section of our department store.

d. Is there any evidence to suggest that a relationship exists between shopping in the beauty sections of our department stores and whether or not a person is male or female?

Assignment instructions

The assignment consists of two parts:

Part 1: Data Analysis
In order to prepare a reply to the General Manager, you will need to examine and analyse the dataset thoroughly. The General Manager has asked a number of questions.
For all relevant questions in the email, you can assume that:
- a 95% confidence level is appropriate for confidence intervals and
- a 5% level of significance (that is, alpha (α) = 0.05) is appropriate for hypothesis tests.

The following guidelines for each question should be considered carefully:

Q1. Regarding customers' age and the amount of money spent on a visit.

a. You will need to produce the relevant summary statistics and suitable table(s) and graph(s).

b. Firstly, you will need to produce the relevant summary statistics. Once done, you should then use an appropriate inferential technique to determine if there is any difference in the average age of customers between the three cities.

c. Here, you will again need to generate the relevant summary statistics. Once done, you should then use an appropriate inferential technique to answer the question whether or not the average amount spent by all customers is less than $105.

d. You will need to use relevant relationship technique(s) to see whether the amount of money spent per visit is influenced by age of the customer.

Q2. Regarding the shopping habits of our customers and their usage of the beauty sections within our department stores.

a. After producing the relevant summary statistics, you will need to use an appropriate inferential technique to estimate the proportion of shoppers who are shopping in the beauty sections in each of the three cities.

b. Produce the relevant summary statistics. You will then need to use an appropriate inferential technique to determine if the proportion of all shoppers shopping in the beauty section could actually be greater than 48%.

c. This question is conditional upon the customer being a female. To assist in solving this question and the question below it (d.), you should create cross tabulations for the variables Beauty and the Gender.

General guidelines:
The analysis section you submit should be no more than 8 pages of computer output (ie. output that you have copied into your Word document from Microsoft Excel). When you conduct your analysis, you will produce much more than this initially, but you should trim it down to only show the most relevant results in your maximum of 8 pages. Where possible, it is always useful to produce both numerical and graphical statistical summaries as sometimes, something is revealed in one that is not obvious in the other. Within the Word document, your analysis should be presented in the same sequence (and contain that same numbered sequence) that the questions have been asked by Jacinta Liu (the General Manager), and be clearly labelled and grouped around each question. Poorly presented, unorganised analysis or excessive output (more than 8 pages) will be penalised.

Save your computer analysis frequently.

Part 2: Email

You are required to reply by email, detailing essential information and conclusions from your data analysis. You are allowed no more than 2 pages to convey your written conclusions.

Keep the English simple and the explanations succinct. Avoid the use of technical statistical jargon. Your reader will not necessarily understand even simple statistical terms, thus your task is to convert your analysis into plain, simple, easy to understand language.

Attachment:- Normal Distribution.rar