Reference no: EM132983031 , Length: word count:1500

MIS771 Descriptive Analytics and Visualisation

LO 1: Apply quantitative reasoning skills to solve complex problems.
LO 2: Plan, monitor, and evaluate own learning as a data analyst.
LO 3: Deduce clear and unambiguous solutions in a form that they useful for decision making and research purposes and for communication to the wider public.

The Case Study for Data Analysis and Business Report

You are 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 is the increasing number 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 advertise that they can save vehicle owners hundreds of dollars each year on insurance premiums.

Your research and analysis group recently secured a dataset from the Insurance Brokers Association (IBA). It is a random sample of 400 customers who obtained the services of car insurance brokers.

Your Manager - Edmond Kendrick, has asked you to analyse the collected data. In particular, you are expected to perform a series of descriptive and inferential analyses and produce a report based on your findings.

As discussed earlier, I got one of the IT colleagues to clean and simplify the dataset for your convenience. The cleaned dataset contains information about 400 randomly selected customers, and I have the following questions/issues relating to the insurance brokers data.

1. Do female drivers under 30 save more on car insurance premiums than their male counterparts, on average?

2. Is the proportion of dissatisfied urban customers smaller than the proportion of dissatisfied rural customers?

3. Does the average savings on car insurance premiums differ across the two valuation methods?
4. I would also like you to analyse whether:
a. The average savings on insurance premiums significantly differ across NSW, Victoria, and Queensland.
b. The proportion of satisfied customers differ across the insurance brokers.

5. I would like you to design and run an experiment to see the effect of the valuation method and the vehicle type on savings on insurance premium using the data set in the attached Excel File - use Data in the "Experiment" worksheet.

Attachment:- Descriptive Analytics and Visualisation.rar