Question;Question 1 Real Estate and Real t-testsSee the Real Estate Mini Case Study Project on page 417 of the textbook and theRealEstate worksheet of the data spreadsheet.Two random samples of 75 listings each have been extracted from the much largeroriginal dataset. One sample has houses with fireplaces and the other has houses withoutfireplaces. The spreadsheet also has: Price ($), Living Area (sq ft), and Age (years) foreach listing.a) Describe, in one short phrase each, the populations being examined.b) Carry out three hypothesis tests to see whether there is a real difference in mean price,mean living area, and mean age of these two populations.Do only the first test, of mean price, manually and show the details of your hypothesistest for the mean price. For the other two tests you may use Excel and you do not need toreport the details, just report the hypotheses, value of the test statistic, and conclusion.Note: The level of significance is not specified. Draw your conclusions by referring to thestrength of evidence indicated by the p-value. Hint: Remember the three alpha valuesmost commonly used: 0.10 = moderate, 0.05 = strong, 0.01 = very strong.c) For the difference in mean house prices, find a 95% confidence interval.d) Give one sentence to describe how the first hypothesis test in part b) and theconfidence interval in part c) reflect the relationship between confidence intervals andhypothesis tests as introduced in section 12.7 of the textbook.1Question 2 Consumer Spending Patterns: Be PrepairedSee the Consumer Spending Patterns Mini Case Study Project on page 441 of the textand the Spending worksheet of the data spreadsheet. Note that the data set is a subset ofthe much larger original dataset.You are on the financial planning team for monitoring a high-spending segment of acredit card. You know that customers tend to spend more during December before theholidays, but youre not sure about the pattern of spending in the months after theholidays. The spreadsheet has the monthly credit card spending of 150 customers duringthe months December, January, February and March and the average across January toMarch.a) Carry out a hypothesis test to compare December with the average spending over thethree following months (JantoMarAvg) to confirm the belief that customers spend moreon average in December. Use a 5% level of significance.b) Carry out three more hypothesis tests to compare the average spending from January toFebruary, January to March, and February to March. Use a 5% level of significance.c) Construct 95% confidence intervals to supplement the four hypothesis tests you carriedout in parts a) and b). Do the confidence intervals confirm your previous conclusions?Question 3 C291 Survey of Males and Females Viva la difference!On the C291Survey worksheet of the data spreadsheet are selected variables from the2013 online survey of C291 students. Assume that these results represent a randomsample of all Sauder undergraduate students. The variables are as follows (coding is alsoprovided as comments in the spreadsheet):GenderGender1=Male, 2=FemaleBornCanadaBorn in Canada?1=Yes, 2=NoPTWorkPart-Time Work1=Yes, 2=NoAlcoholAlcohol Consumption 1=Yes, regularly, excess,2=Yes, regularly, moderate3=Yes, occasionally, 4=NeverOutlookC291 Outlook1=Dreading it, 2=Will survive,3=Moderately excited, 4=Very excited,5=Most thrilling everTwitterTwitter User1=Yes, 2=NoIncomplete records have been removed so you dont need to worry about missing data.There are 606 records in total.You will test for differences between males and females with respect to the other fourvariables, as explained below. Use a 0.01 (i.e. 1%) level of significance for all tests.Details are on the next page.2a) Carry out two hypothesis tests (z-tests) to compare the proportions of males andfemales who do part-time work, and to compare the proportions who use Twitter.b) Construct two 99% confidence intervals for the differences in proportions tested in parta).c) Carry out three chi-square hypothesis tests to determine association between (1)Gender and Alcohol, (2) BornCanada and Alcohol, and (3) Gender vs. Outlook. For eachtest provide:hypothesestwo-way table of observed countstwo-way table of expected countsvalue of the test statistic, to two decimal places SEE NOTE FOLLOWINGcritical value from Appendix C of the textbook (include degrees of freedom)exact p-value using CHIDIST in Excel.conclusion, dont simply say reject or do not reject, include a statement withpractical meaning.NOTE: Only for the first test of part c), Gender vs. Alcohol, write out long-hand yourwork done to compute the test statistic. Neat hand-writing is preferred to typing in thiscase. Retain all precision during calculations but write down the test statistic to twodecimal places only.
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