Reference no: EM132267227 , Length: word count:2000

Business Analytics Assignment -

Learning Outcomes -

• Apply quantitative reasoning skills to analyse business performance.
• Create data-driven / fact-based solutions to complex business scenarios.
• Use contemporary data analysis tools to analyse business performance.

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.

Scenario -

Aussie University is an Australian university that offers various courses such as the Bachelor of Commerce. To complete the Bachelor of Commerce students must attain 24 credit points including 8 credit points of core units. Claudia Brady is the Associate Dean, Teaching and Learning at the Aussie Business School. She has asked you, Sam Mannix, to conduct exploratory and descriptive analysis to gain a better understanding of the performance of the Bachelor of Commerce students. You can see her email on the next page.

As a result, can you investigate the following?

1. Average core score is the most important measure that the board is interested in. Can you provide me with an overall summary of the average student score for the 8 core units?

2. The board believes that performance in core unit 4 (Business Analytics) does not differ between genders. Can you provide a comparison of the core unit 4 scores across different genders?

3. The board wants to find out whether the proportion of students origin differs between different genders. Can you provide some insights?

4. Some of the board members believe that the number of attendances influences student grades. Can you investigate if there is a relationship between the total number of attendances and core unit 4 grades?

5. The board also wants to know if there is a relationship between the total number of attendances and core unit 4 scores. Can you provide some information?

Assignment instructions -

The assignment consists of three parts:

Part 1: Data Analysis

When conducting the analysis, you will apply techniques from descriptive analytics and visualisations; hence you will use various tables, graphs, and summary measures. Sometimes we refer to this type of analysis as "exploratory analysis". When exploring data, we often produce more results than we eventually use in the final report, but by investigating the data from a number of angles, we can develop a much better 'feel' for the data: a deeper understanding of the data.

In order to prepare a reply to Claudia, you will need to examine and analyse the data set thoroughly. The following guidelines for each question should be considered carefully:

1. A summary of average scores: To answer this question you should firstly calculate the average student scores for the 8 core units and then analyse them. You should derive summary measures and check for unusual data along with producing any suitable graphs and tables.

2. Core unit 4 score by gender: Investigate any particular relationship(s) between core unit 4 scores and gender.

3. Origin by gender: Explore any particular relationship between student origin and gender.

4. Core unit 4 grade by attendance rate: Research any particular relationship between student grades in core unit 4 and their attendance rate in lectures and seminars. You need to convert core unit 4 scores to grades and total number of attendances in lectures and tutorials into three rates.

Grade	Description	Meaning
HD	High Distinction	80% and over
D	Distinction	70 - 79%
C	Credit	60 - 69%
P	Pass	50 - 59%
N	Fail	below 50%

 

Attendance rate	Description	Meaning
High	High attendance rate	More than or equal to 17 attendances
Average	Average attendance rate	More than or equal to 8 and less than 17 attendances
Low	Low attendance rate	Less than 8 attendance

5. Core unit 4 score by total attendance: Research any particular relationship between student scores in core unit 4 and their total number of attendances.

The analysis you submit should be on the provided 5 sheets (Q1 to Q5). 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. Poorly presented, unorganised analysis or excessive output will be penalised.

It is usual, when writing any professional document, to caption any tabular or graphical output professionally. For example, TABLE 1: Summary statistics for the variable Average Core Score.

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. Remember you should use font size 12 and leave a margin of 2.54 cm.

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.

The email is to be written as a stand-alone document (assume that the Claudia Brady will only read your email). Thus, you should not have any references in the email to your analysis, nor should you include any charts and tables within it.

Use an email format for your reply. This means the email heading (e.g., To:, From:, Subject:) should be included, the recipient should be addressed at the beginning and the signature or name of the sender should be included at the end.

When composing your reply, make sure that you actually answer the questions asked. Cite (state)the summary statistics of importance (without referring to your analysis section). Sequentially number your answers in your email to match the email of the Associate Dean, Teaching and Learning. Include a simple introduction at the start of the email and a summary/conclusion at the end.

Marks will be deducted for the use of technical terms, irrelevant material, poor presentation /organisation/formatting and emails that are over two pages long.

When you have completed the email, it is a useful exercise to leave it for a day, return to it and re- read it as if you knew nothing about the analysis. Does it flow easily? Does it make sense? Can someone without prior knowledge follow your written conclusions? Often on re-reading, you become aware that you have made some points in a clumsy manner and find that you can re-phrase them much more clearly.

Part 3: Interactive Dashboard

The minimum requirement is a neat, functional, interactive dashboard. It is expected that the dashboard includes up to 4 interactive components.

The following questions will guide you in designing an interactive dashboard.

1. What are the most appropriate visualisations for the dashboard?

2. What about the choices of colour?

3. How can I make the dashboard interactive?

Note - Words: as per the answers around 2000.

Attachment:- Assignment Files.rar