MIS771 Descriptive Analytics and Visualisation

Assignment One

Background

This is an individual assignment. You need to analyse a given data set, and then interpret and draw conclusions from your analysis. You then need to convey your conclusions using plain language in a written report to a person with little or no knowledge of Business Analytics.

Assurance of Learning

This assignment assesses the following Graduate Learning Outcomes and related Unit Learning Outcomes:

Feedback before submission

You can seek assistance from the teaching staff to ascertain whether the assignment conforms to submission guidelines.

Feedback after submission

An overall mark together with feedback will be released via CloudDeakin, usually within 15 working days. You are expected to refer and compare your answers to the feedback to understand any areas of improvement.

Case Study

You are Natalia Navarska, a data analyst in the Research and Analysis group at Financial Review Magazine. Your primary role is to evaluate new products and services. You are often required to report outcomes of your analysis to senior editors at the Magazine who have little or no knowledge of data analysis.

Of specific interest to Financial Review magazine are the increasing numbers of companies that offer brokerage services for car insurance and potentially what this means for consumers. An insurance broker is an independent insurance agent who works with many insurance companies to find the very best available policies for his or her customers. Most of these brokers are advertising that they can save vehicle owners hundreds of dollars each year on insurance premiums.

Just recently, your research and analysis group secured a dataset from the Insurance Brokers Association (IBA), which is a random sample of 400 customers who obtained the services of car insurance brokers. You have performed an exploratory analysis and have emailed the results (see pages 6-7) to Edmond Kendrick, one of the senior editors of Financial Review Magazine.

Edmond has replied to your email regarding the Insurance Brokers. His email is reproduced next page:

Email from Edmond

To: Natalia Navarska

From: Edmond Kendrick

Subject: Analysis of car insurance brokerage services

Hi Nat,

Thank you for the comprehensive analysis and notes. Now I am more curious about what else could we learn from analysing the dataset.

1. From what I can gather from your notes, iChoose was able to save their customers more money than other brokers. Can I now conclude that iChoose, on average, can save more on insurance premiums than uChoose?
2. Your analysis of 400 customers showed that the proportion of dissatisfied (i.e. either

‘Dissatisfied’ or ‘Very Dissatisfied’) urban customers is smaller than the proportion of dissatisfied rural customers. Can we argue that this difference would hold across all urban and rural customers?

3. I did my own analysis of the sample and came to the following conclusions:
1. The average savings on insurance premiums differ between rural and urban customers.
2. On average, customers with ‘Agreed Value’ policy saved more on their insurance premiums than the customers with ‘Market Value’ policy;
3. The proportion of female customers with a diamond level no claim bonus rating (NCBR) is less than male customers with a diamond level no claim bonus rating (NCBR);

What would be great is if you can verify my findings and tell me how much the difference is in each of the three scenarios mentioned above.

4. I would like you to expand the analysis and look at whether:
1. The average savings on insurance premiums significantly differ between Victoria, NSW and Queensland.
2. The average savings on insurance premiums significantly differ between 4WD, Luxury and Sports car.
5. Does the proportion of customers who approached their insurance provider before reaching out to a broker differ between the insurance providers?
6. I asked Raj to design an experiment to see the effects of the valuation method and the vehicle type on savings on insurance premiums, he sent me a table with some numbers (see AppendixA). Can you complete the analysis?

I look forward to your response.

Regards

Eddie

Appendix- A: Data for the experiment prepared by Raj

An Extract of the Analysis and Notes Prepared by Nat

Customer Satisfaction

Customer Satisfaction by Area

Notes to Edmond

Savings:

From a sample of 400 customers,

• On average, car insurance brokers saved their customers $113 (median).
• The middle 50% of customers saved between $12 and $357; a quarter of the customers saved at most $12; three-quarter of the customers saved no more than $357.
• The savings ranged from a loss of $87 to a substantial gain of $1956.
• Almost 40% of the customers, saved between $1 and $200 on their current insurance premiums; car insurance brokers have shown their ability to find an appropriate policy for most of their customers.
• The bulk of the customers have relatively low (in few cases none at all) annual savings on premium, with a relatively small number having high savings. 89% of customers saved up to $600; Only 4% of consumers saved between $1000 and $2000; with only 1%; shows that brokers have the ability to save consumers a massive amount (more than $1600) on their annual premiums but the prospect of making such savings is low.
• 24% of consumers paid a higher premium than previously or did not save on their annual premium.
• 18% of customers made a loss; the brokers are claiming to save most customers hundreds of dollars, but the discussion about the possibility of customers paying more money for the insurance is missing.

SUBMISSION

The assignment consists of two parts: Analysis and Report. You are required to submit both your written report and analysis.

Guidelines for Data Analysis

Read the case study and questions asked by Edmond carefully. Then spend some time reviewing the data to get a sense of the context. The analysis required for this assignment involves material covered in Module 1, with the corresponding tutorials being a useful guide.

The analysis should be submitted in the appropriate worksheets in the Excel file. Each question from the email should be analysed in a separate tab (e.g. Q1, Q2 … or Q3.1, Q3.2 …). You need to add these. Before submitting your analysis, make sure it is logically organised, and any incorrect or unnecessary output has been removed. Marks will be penalised for poor presentation or disorganised/incorrect results.

For all questions in the email, you can assume that:

• 95 % confidence level is appropriate for confidence intervals and;
• 0 % level of significance (i.e. a = 0.05) is appropriate for any hypothesis tests.

You can complete all data analysis using the Excel templates provided in the assignment data file. In choosing the technique to apply for a given question, keep the following in mind:

• Are we dealing with a numerical variable or categorical variable?
• Are we dealings with one sample, two samples or more than two samples situation?
• Are we dealing with independent samples or paired-samples situation?
• Each question must be answered using the most appropriate technique.
• For all hypothesis questions, please formulate your hypotheses, and state them in both notation and words clearly.
• Even though question(s) may lead you to inferential technique, consider conducting a descriptive analysis of the sample data first.

ATTENTION!

• When you have established that there is a difference between two means or proportions, we expect you to estimate and report the difference.
• When you have established that there is a difference between two or more means or proportions, we expect you to follow up with an appropriate multiple comparison procedure.

You may need to make certain assumptions about the dataset we are using to answer some questions. For other questions, there will be technical/statistical assumptions that you need to make; for example, whether to use an equal or an unequal variance test…etc. You need to consider and incorporate any violations of assumptions such as unequal sample sizes as limitations of your analysis in your report.

Note: Give the Excel file the following name A1_YourStudentID.xlsx (use a short file name while you are doing the analysis.

Guidelines for your Business Report

Once you have completed your data analysis, you need to summarise the key findings for each question and write a response to Edmond in a report format. Your business report consists of four sections: Introduction, Main Body, Conclusion, and Appendices. The report should be around 1,500 words.

Use proper headings (e.g. Q1, Q2 … or Q3.1, Q3.2…) and titles in the main body of the report. Use subheadings where necessary.

Keep the language plain and the explanations brief. That is, avoid the use of any unnecessary technical statistical jargon. Your reader may not necessarily understand even the simplest statistical term. Thus your task is to convert your analysis into plain, easily understandable expressions.

General instructions:

• You MUST report both descriptive and inferential analysis results. Otherwise, marks will be deducted.
• The report is to be written as a stand-alone document (assume Edmond will only read your written report). Thus, you should not have any direct references in the report to your analysis.
• Your report may include relevant excel outputs including templates, tables, charts, and graphs but ONLY as Appendices (appendices are not included in the word count).
• Make sure these outputs in the Appendix are visually appealing, have a consistent formatting style and proper titles (title, axes titles, etc.), and are numbered correctly.
• The introduction begins by highlighting the main purpose(s) of the analysis and concludes by explaining the structure of the report (i.e., subsequent sections). The conclusion should highlight the key findings of the analyses and explain the main limitations (if any).
• Marks will be deducted for the use of technical terms, irrelevant material, and poor presentation/organisation.

When you have completed the report, it is a useful exercise to leave it for a day, return to it and then re-read. 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 clumsily, and you find that you can re-phrase them much more clearly.

Note: Give the report the following name A1_YourStudentID.docx or pdf.