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 (GLO) |
Unit Learning Outcome (ULO) |
GLO1: Discipline-specific knowledge and capabilities - appropriate to the level of study related to a discipline or profession. GLO3: Digital Literacy - Using technologies to find, use and disseminate information GLO5:Problem Solving - creating solutions to authentic (real world and ill-defined) problems. |
ULO 1: Apply quantitative reasoning skills to solve complex problems. ULO 2: Use contemporary data analysis and visualisation tools and recognise the limits of such tools. |
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 knowledgeof 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.
‘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?
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.
I look forward to your response.
Regards
Eddie
Vehicle Type |
||||||
Valuation Method |
4WD |
Family |
Sport |
Luxury |
||
Agreed Value |
1068 |
169 |
1799 |
966 |
||
128 |
150 |
680 |
1144 |
|||
98 |
-59 |
373 |
893 |
|||
560 |
22 |
143 |
1144 |
|||
429 |
108 |
442 |
629 |
|||
Market Value |
104 |
54 |
99 |
1273 |
||
72 |
0 |
156 |
247 |
|||
311 |
94 |
1084 |
357 |
|||
146 |
84 |
357 |
676 |
|||
135 |
-10 |
131 |
366 |
An Extract of the Analysis and Notes Prepared by Nat
Saving Outcome
Mean 229.64 Not benefited from (saving < 0) 72
Standard Error 16.03 & Neither benefited nor lost (saving =0) 25
Median 113
Mode 0 Benefited from (saving > 0) 303
Standard Deviation |
320.56 |
||
Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count |
102759.59 5.46 2.08 2043 -87 1956 91857 400 |
180 160 140 120 100 80 60 40 20 0 (Broker P |
HISTOGRAM: SAVING |
Q1 Q3 IQR LF UF OUTLIERS |
12 357 345 -505.5 874.5 YES |
||
Summary of Saving by Broker |
|||
iChoose uChoose vChoose yChoose
Mean |
262.442 |
230.847 |
137.381 |
204.188 |
Standard Error |
25.883 |
36.672 |
14.330 |
31.575 |
Median |
127 |
94.5 |
123.5 |
100 |
Mode |
0 |
0 |
294 |
0 |
Standard Deviation |
356.766 |
311.169 |
92.868 |
309.368 |
Sample Variance |
127281.930 |
96825.934 |
8624.437 |
95708.659 |
Kurtosis |
4.121 |
4.678 |
-0.461 |
6.102 |
Skewness |
1.826 |
1.934 |
0.442 |
2.210 |
Range |
2034 |
1645 |
392 |
1738 |
Minimum |
-78 |
-69 |
-31 |
-87 |
Maximum |
1956 |
1576 |
361 |
1651 |
Sum |
49864 |
16621 |
5770 |
19602 |
Count |
190 |
72 |
42 |
96 |
Q1 |
0 |
24 |
65.5 |
0 |
Q3 |
412.5 |
388.75 |
200 |
338 |
IQR |
412.5 |
364.75 |
134.5 |
338 |
LF |
-618.75 |
-523.125 |
-136.25 |
-507 |
UF |
1031.25 |
935.875 |
401.75 |
845 |
OUTLIERS |
YES |
YES |
NO |
YES |
• Customer Satisfaction
Customer Satisfaction Count of Customers Very Dissatisfied 35 Dissatisfied 57 Satisfied 174 Very Satisfied 134 Total 400
• Customer Satisfaction by Area
Satisfaction Area Very Dissatisfied Dissatisfied Satisfied Very Satisfied Total Rural 10 23 32 30 95 Urban 25 34 142 104 305 Total 35 57 174 134 400
Notes to Edmond
Savings:
From a sample of 400 customers,
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, MainBody, 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.
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