This assignment is to be done using Excel. Submit ONE MS Excel file containing all work on Blackboard. (No Hard Copy). Bianca Frantini, a Humber College graduate who always had only perfect marks in statistics, was hired by the famous Healthy Life medical insurance company. Bianca is assigned to conduct statistical analysis of medical and financial data. As Bianca is on probation, please help her to complete the following six tasks. In problems 2-6 state hypotheses H0 and H1, and provide detailed conclusions (based on P-values or critical values/test statistics) together with the Excel output. For your convenience the data are given in Major Assignment Data file. 1. Biancas manager Dr. Bennet Klein, who has degrees in both mathematics and medicine, asked her to find estimates of the average dental claim reimbursement for 2015. As Healthy Life has hundreds of thousands of clients it is virtually impossible to calculate the population mean. Using the Excel Random Number Generator function, Bianca found a random sample of 25 dental claims submitted to Healthy Life. The amounts covered by insurance you can see in Major Assignment Data file. Please help Bianca to construct 90%, 95%, and 99% confidence intervals for the true average reimbursement. Use t-distribution and Descriptive Statistics function from Data Analysis. 2. Analyzing most recent data, Biancas manager Dr. Klein found out that in 2015 the anti- cancer prescription drug claims submitted by Healthy Life clients contained amounts considerably greater than he anticipated. Specifically, he asked Bianca to check whether patients with Oncotype DX scores over 30 claimed, on average, more than $1000 per month. Using the systematic sampling method Bianca selected 45 patients from this category (see the Major Assignment Data file). Please help Bianca to test the claim that the population mean monthly amount of the anti-cancer prescription drug claims was over $1000 in 2015. Use Data Analysis t-Test: Two-Sample Assuming Unequal Variances and fool Excel approach. Use 5% significance level. Is it possible to reach the same conclusion at 1% significance level? 3. From time to time, unfortunately, Healthy Life employees have to deal with insurance fraud. Say, some people claim medical services that have never been provided or money they never paid. To that end, Healthy Life hired a number of investigators whose functions are not much different from those of police detectives. Doctor N.N. has been under suspicion for some time for deceiving and overcharging his patients. Healthy Life approached the provincial authorities and they agreed to launch a formal investigation and open a case given a credible evidence of fraud is provided. The Healthy Life investigation department found a number of offences.These included up- coding or upgrading, which involved billing for more expensive treatments than those actually provided; providing and subsequently billing for treatments that were not medically necessary; scheduling extra visits for patients; referring patients to another physician when no further treatment was actually necessary; "phantom billing," or billing for services not rendered; and ganging, or billing for services to family members or other individuals who were accompanying the patient but who had not personally received any services. Bianca took part in this investigation. At one point, she was asked to compare the amount doctor N.N. charged for a certain medical procedure with the city average. Bianca randomly selected a sample of forty five physicians of the same qualification and specialty in order to compare their fees with ones of doctor N.N. (see the Major Assignment Data file). Can we conclude at 0.1% significance level that the population average is significantly below $600 that N.N. charged for this procedure? After carefully reviewing the data Bianca and her manager decided that variability in the population did not change over the last years so they assumed that the population standard deviation is still about $175 as it had been several years ago. Therefore Bianca decided to use z-distribution. Please help Bianca to test the claim. Use Z.TEST dialog box. (Please note that the test returns the one-tailed right P-value). 4. It appears that not all people are equally vulnerable to cancer. People from some ethnic groups have higher or lower than average chances of developing certain types of cancer. Biancas manager Dr. Klein thinks that the companys insurance policy should reflect this fact and constantly raises this question in the meetings. To be more convincing, he asked Bianca to take a random sample of those Healthy Life clients who belong to ethnic group X (at least on their maternal or paternal side) and a similar sample consisting of the clients without X ancestry. Then, Bianca was asked to compare Y parameters indicating likelihood of developing W cancer. (As the matter is ticklish, we will not be naming the ethnic group, the type of cancer, the medical parameter, and the gender of sample members.) Then, it is known that in the general population Y parameters are distributed with the standard deviation of 3.0 (therefore the population variance is equal to 9.0). However in the X ethnic group the population standard deviation is about 2.1(and the population variance is equal to 4.41). As only 2-3% of Canadians have X ancestors, Bianca and her manager assume that the standard deviation in the population of those who have no X ancestry is also around 3.0 as in the country in general. This assumption allows using z-distribution. The data are provided. Can we state at 1% level of significance that it matters whether a person belongs to X group or not in terms of the risk of developing W cancer? Or the chances are equal (on average Y parameters are the same)? Help Bianca to conduct the test. Use Data Analysis z-Test: Two- Sample for Means. 5. Smoking is a risk factor affecting patients cardiovascular system (and not only cardiovascular system, of course). Bianca was asked to take random samples of male Healthy Life members recently admitted to hospitals in GTA with heart attacks. She compiled two separate files consisting of those who smoked and those who never smoked. The purpose of this research is to prove that the first heart attack occurs at an earlier age if a patient smoked. After carefully analyzing the data Bianca came up with the hypothesis that smokers who suffer a first heart attack are, on average, seven years younger than non-smoking people who suffer a first heart attack. Please calculate sample variances for both files and decide what function is most appropriate: Data Analysis t-Test: Two-Sample Assuming Equal Variances or Data Analysis t-Test: Two-Sample Assuming Unequal Variances. Please help Bianca to conduct the test at 1% significance level. 6. Biancas manager Dr. Bennet Klein wonders whether Healthy Life members needed more chiropractic help in 2015 than in 2014, on average. Bianca found a random sample of those who were treated by chiropractic doctors in both years. Data provided. Please help Bianca to check whether annual expenses and number of visits increased, on average. For both tests use Data Analysis t-Test: Paired Two Sample for Means and 2% significance level. Notes:(could you please give me your email to send you Excel file to use the digits by completing the assignment)