He decides to explore this phenomenon and asks 15 of

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He decides to explore this phenomenon, and asks 15 of his neighbors howmany times they wash their cars each year and how much they paid in car repair costs last year.His results are in the table below:MeanStandard deviationx= number of car washes per year6.43.78y= repairs costs for last year$955.30$323.50The correlation for these to two variables isr= -0.7116.Find the equation of the least-squares regression line (withyas the response variable).17.What percentage of the variation in repair costs can be explained by the number of times peryear a car is washed?18.Based on these data, can we conclude that washing your car frequently will reduce repaircosts?Explain.
Test 3BAP StatisticsName:Part 1:Multiple Choice.Circle the letter corresponding to the best answer.Questions1and2refer to the following information:For children between the ages of 18 months and 29 months, there is an approximately linearrelationship between height and age. The relationship can be represented byˆy= 64.93 + 0.63x,whereyrepresents height (in centimeters) andxrepresents age (in months).1.Joseph is 22.5 months old.What is his predicted height?87.40
2.Loretta is 20 months old and is 80 centimeters tall. What is her residual?77.53
3.You have data for many families on the parents’ income and the years of education theireldest child completes.Your initial examination of the data indicates that children fromwealthier families tend to go to school for longer.When you make a scatterplot,
4.A community college announces that the correlation between college entrance exam grades andscholastic achievement was found to be –1.08.On the basis of this you would tell the collegethat(a) the entrance exam is a good predictor of success.(b) the exam is a poor predictor of success.(c) students who do best on this exam will be poor students.(d) students at this school are underachieving.(e) the college should hire a new statistician.
126The Practice of Statistics, 4/e- Chapter 3© 2011 BFW Publishers

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Term
Spring
Professor
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Tags
Statistics, Least Squares, Linear Regression, Regression Analysis, Errors and residuals in statistics, regression line, BFW Publishers

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