Analyse given data set and interpret and draw conclusions

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Reference no: EM132359968 , Length: word count:1500

Descriptive Analytics and Visualisation Assignment -

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:

Graduate Learning Outcome -

1: Discipline-specific knowledge and capabilities - appropriate to the level of study related to a discipline or profession.

2: Digital Literacy - Using technologies to find, use and disseminate information

3: Problem Solving - creating solutions to authentic (real world and ill-defined) problems.

Unit Learning Outcome -

1: Apply quantitative reasoning skills to solve complex problems.

2: Use contemporary data analysis and visualisation tools and recognise the limits of such tools.

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 (attached) 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 -

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:

a. The average savings on insurance premiums differ between rural and urban customers.

b. On average, customers with 'Agreed Value' policy saved more on their insurance premiums than the customers with 'Market Value' policy;

c. 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:

a. The average savings on insurance premiums significantly differ between Victoria, NSW and Queensland.

b. 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 Appendix- A). Can you complete the analysis?

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.

Attachment:- Descriptive Analytics and Visualisation Assignment File.rar

Reference no: EM132359968

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Reviews

len2359968

8/24/2019 2:43:56 AM

Total words – 1500. A1 has the data and other 2 excels are templates. Submission instructions - The assignment 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 paper or email copies, or part of the assignment submitted after the deadline. No extensions will be considered unless a written request is submitted.

len2359968

8/24/2019 2:43:47 AM

Penalties for late submission: The following marking penalties will apply if you submit an assessment task after the due date without an approved extension: 5% will be deducted from available marks for each day up to five days, and work that is submitted more than five days after the due date will not be marked. You will receive 0% for the task. 'Day' means calendar days or part thereof. The Unit Chair may refuse to accept a late submission where it is unreasonable or impracticable to assess the task after the due date.

len2359968

8/24/2019 2:43:37 AM

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.

len2359968

8/24/2019 2:43:29 AM

For all questions in the email, you can assume that: 95 % confidence level is appropriate for confidence intervals and; 5.0 % level of significance 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.

len2359968

8/24/2019 2:43:23 AM

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.

len2359968

8/24/2019 2:43:16 AM

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.

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