QMB 3200 Homework 2

QMB 3200 Homework 2

Complete your work in this document in black type. Leave the existing document in the blue type it is currently in and do not edit the document except to add your responses below each prompt. Submit to Canvas as a single Word or pdf document; submissions consisting of multiple files or files submitted in inaccessible formats will not be graded. The assignment is due by Thursday, Oct 21 at 11:59pm; late work will be penalized 20% per day or portion of a day that it is late. This assignment is worth 45 points (around 11%) of your total grade for the class. You will use your student data set (cars) to run all analyses. Four points are awarded for following directions.

 

Part 1.

1. Run an ANOVA to compare the mean prices of your three vehicle models. Insert a screenshot of the Printout. (5 points)

 

 

1. Is there a significant difference between the means (yes or no)? (2 points)

 

 

 

1. Run a Tukey post hoc test to rank the means of the model prices (even if there was not a significant difference). Insert a screenshot of your Printout. (5 points)

 

 

 

1. List your vehicle models in order from that with the largest mean price to that with the smallest mean price (indicate any “ties”). (3 points)

 

 

 

 

 

 

PART 2.

1. Imagine that you have reason to believe that the majority of used vehicles for sale were produced in the year 2015 or earlier. Test this assumption with a binomial test of proportions. Insert your Printout. (5 points)

 

 

1. Interpret the results of the above analysis by filling in the blanks. (3 points)

“ There is Click or tap here to enter text. evidence ( at α = Click or tap here to enter text.) to indicate that the majority of used vehicles for sale were Click or tap here to enter text.”

 

 

PART 3.

1. Run a simple linear regression of your student data set using the price of the vehicle as the dependent variable (y) and the mileage as the independent variable (x). Insert your Printout. (5 points)

 

1. What is the y-intercept of the model (fill in the blanks)? (2 points)

 

1. Can the y-intercept be practically interpreted in this case (yes or no)? (2 points)

 

1. What is the slope of the model? (2 points)

 

 

1. What is the R² (Lecture 10 Slide 11)? (2 points)

 

 

1. Interpret the R² by filling in the blanks (Lecture 10 Slide 11). (3 points)

 “ We can explain about Click or tap here to enter text. % of Click or tap here to enter text. using our model.”

 

1. Is this a useful model? Interpret the p-value based on a one-tailed test by filling in the blanks. (2 points)

“ There is Click or tap here to enter text. evidence (at α = Click or tap here to enter text.) to indicate that our model with Click or tap here to enter text.is useful for predicting Click or tap here to enter text..”