Need one word file and one excel filedata is attached and the answer needs to be in that excel file
Scenario According to a study published in the US News and World Report the cost of medical malpractice in the United States is $55.6 billion a year, which is 2.4 percent of annual health-care spending. Another 2011 study published in the New England Journal of Medicine revealed that annually, during the period 1991 to 2005, 7.4% of all physicians licensed in the US had a malpractice claim. These staggering numbers not only contribute to the high cost of health care, but the size of successful malpractice claims also contribute to high premiums for medical malpractice insurance. A report from McKinsey (May 2013) Unleashing the Value of Advanced Analytics in Insurance states: “The proliferation of third-party data sources is reducing insurers’ dependence on internal data. Digital “data exhaust” from social media and multimedia, smartphones, computers, and other consumer and industrial devices — used within privacy guidelines and assuring anonymity — has become a rich source for behavioural insights for insurance companies, as it has for virtually all businesses. Recently, the release of previously unavailable or inaccessible public sector data has greatly expanded potential sources of third-party data. The US and UK governments and the European Union have recently launched “open data” Web sites to make available massive amounts of government statistics, including health, education, worker safety, and energy data, among others. With much better access to third-party data from a wide variety of sources, insurers can pose new questions and better understand many different types of risks.” An insurance company in Australia has collated a range of data and wants to develop a better understanding of its claims paid out for medical malpractice lawsuits. Its records show claim payment amounts, as well as information about the presiding physician and the claimant for a number of adjudicated or settled lawsuits in this year. The Data The data set contains numerous variables and details about the claims. For the purpose of this assignment the data set has been simplified to nine variables with information about 200 randomly selected claims made this year. The questions you need to answer are contained in the following memorandum Memorandum Date: 24th August, 2020 To: Ellyse Perry, Analyst, iFastInsurance From: Daisy Pearce, Manager, Medical negligence claims Team, iFastInsurance Subject: Analysis of medical malpractice Claim Data Dear Ellyse, Can you please carry out an analysis of the medical malpractice Claim data (contained in the file (MedMalLawsCliam Data.xlsx) and prepare a report for me containing answers to the following questions. My specific questions are: Q1. An Overall View of both “Amount” and “severity rating of damage” Can you provide me with overall summaries of a) the amount of the claim payment in dollars? b) the severity rating of damage to the patient. Q2. Relationships a) Is there a difference in ‘MILD’, ‘MEDIUM’ or ‘SEVERE’ claims when comparing males and females? b) Is there a relationship between the age of the claimant and the amount of the claim payment? c) The insurance company would like to get an understanding of the relationship between the speciality of the physician involved and claim amount. I realise that the survey relates to a random sample of 200 claims paid out for medical malpractice lawsuits, and that this information can be used to draw inferences about all claims paid out for medical malpractice lawsuits by iFastInsurance. With that in mind, I hope you are able to provide me with answers to the following questions: Q3. The insurance company would like to get an estimate of the following. a) Average age of the claimant in years b) Proportion of claims made with a severity condition ‘SEVERE’. Q4. The insurance company would like to compare this year’s claims with the industry average. a) The industry average of amount of payment per claim is 68,000 dollars. Is this the same or different this year? b) Based on the industry average, less than 51% of the claimants are either divorced or widowed. Is it the same this year? Q5. Appropriate Sample Size Finally, the General Manager of the insurance company is concerned that a sample of only 200 claimants seems too small to draw reliable inferences from. I am concerned that increasing the sample to 400 Australians would still be too small to provide accurate results. For a survey we intend to undertake next year, we would like your advice on the following: a) Should a large sample be collected? Does the precision of an estimate increase when a large sample is being used? b) What size sample should be taken to accurately estimate the average amount of claims per year to within 4,000 dollars? I look forward to your responses. Sincerely, Daisy Business Report Requirements • Your report should be no longer than 3 pages and should not include any charts and tables, or appendices in the report. Charts/graphics and tables are only to be placed in the Data Analysis file i.e. the Excel spreadsheet and not reproduced in the report. • Suggested formatting for the report: single‐line spacing; no smaller that 10‐ point font; page margins approx. 25mm, and good use of white space. • Your report must have a cover sheet containing your particulars and Unit details. • The report is to be written as a stand‐alone document (assume Daisy will only read your report). Thus, you should not have any references in the report to your data analysis output. Eg. “According to Table 1 in the analysis…” • Your report must contain an executive summary that explains in plain language the purpose of the report and summarises the main findings. The executive summary should be no more than 700 words long. • The body of your report must be set out in the same order as in the originating memorandum from Daisy, with each section (question) clearly marked • Use plain language and succinct explanations. Avoid the use of technical or statistical jargon as Daisy cannot be expected to understand statistical terminology. As a guide to the meaning of “Plain Language”, imagine you are explaining your findings to a person without any statistical training (e.g. someone who has not studied this unit). What type of language would you use in this case? • Marks will be lost if you use unexplained technical terms, irrelevant material, or have poor presentation/ organization • All Microsoft Excel data analysis output associated with each question in the Memorandum are to be placed in the corresponding tab in the T22020MIS770_A2_yourstudentid.xlsx file Data Analysis Instructions/Guidelines In order to prepare a reply to Daisy’s memorandum, you will need to examine and analyse the dataset MedMalLawsClaimData.xlsx thoroughly. Daisy has asked a number of questions and your Data Analysis output (i.e. your charts/tables/graphs) should be structured such that you answer each question on the separate tab/worksheet provided in your Excel document. There are also three extra tabs in MedMalLawsClaimData.xlsx called CI, HT and SampleSize and you may use the various templates contained in these tabs arriving at your “Confidence Interval”, “Hypothesis” and “Sample Size” answers, should you wish to do so. Q1. An overall summary of Amount (in dollars) and summary of Severity You are required to comprehensively describe the variable ‘Amount’ by itself and ‘Severity’ by itself using the most appropriate techniques from module 1. Your analysis should include numerical summaries, graphs and tables. The importance of other variables is considered in other questions. You should thoroughly investigate relevant summary measures (and their reliability) for these two variables. Also, there may well be suitable tables and charts/graphs that will illustrate more clearly other important features of amount and severity. (See Topics 1-3 learning materials) Q2. Descriptive measures and insights Your course notes (Module One) give methods (numerical summaries/tables/graphs/charts) for summarising a single variable and investigating the relationships (dependencies) between two variables for these situations. For example • Pie/Bar charts • Summary/Frequency Distribution tables • Comparative summary measures including quartiles and percentiles • Scatter diagrams • Coefficient of correlation, R2 value • Contingency tables/Cross tabs • Stack bar charts, side-by-side bar charts • Histograms/Frequency polygons/Ogives • Single/Multiple box and whisker plots etc. (See Module One learning materials) Use whatever techniques you have studied in Module 1 to investigate this matter. Generate suitable visualisations (Tables/Graphs/Charts) and numerical measure(s) demonstrating the existence or otherwise of a relationship. Remember to provide a brief overall summary when concluding these questions. Q3-Q4 The analysis required involves inferential statistics, which are covered in Module 2. Use the relevant Excel templates (CI and HT) provided in the Data file. These questions will require you to complete either a confidence interval or a hypothesis test. Go through each of the questions asked by Daisy and decide which technique is the most appropriate. Below are some hints regarding the most appropriate technique: • Do we have to make an estimate, and therefore need a confidence interval? • Are we testing a theory/claim/ or comparing values… and therefore need a hypothesis test? So decide which you think is the most appropriate technique (tutorials for topics 6 and 7 help here). • You can assume that a 95% confidence level is appropriate. • Use 5% significance in any hypothesis tests you perform, and provide a summary of your conclusions. Where appropriate, make comparisons with other levels of significance (e.g. 10%, 1%). • To answer some questions you may need to make/check certain assumptions about the data set we are using. Mention these in your data analysis, where relevant. There is no need to mention this in the report. Q5. Use the relevant Excel templates provided in the Data file. • You should include comparisons for 90%, 95% and 99% and a recommendation the appropriate sample size. Note: There is an Appendix at the end of each Chapter of the Prescribed Textbook which describes the basic Excel steps associated with that Topic. Chapters 1 to 9 are applicable for this assessment. Other Guidelines: • To answer some questions, you may need to make certain assumptions about the data set we are using. Mention these in your data analysis, where relevant. There is no need to mention this in the report. • Please ensure you analyse the data thoroughly but do not go beyond what the question asks – for example, if one question requires comparison for the Gender classification, it does not mean you must do it for any other question, unless specifically asked to do so. • We assume you will be using Excel to perform you data analysis. • Detailed algebraic responses are not expected. Thus, avoid including extensive derivations, formulae, etc. You are to use Excel where possible to complete your answers. • In