Home4U, a rental company, would like to normalize its rental charge model for rentals (Rent in $) of an apartment such that clients will know their rental cost. Three predictor variables are used: (1) beds (the number of bedrooms), (2) Baths (the number of bathrooms), and (3) square footage (Sqft). A sample of 40 recent rentals is collected. A fragment of the data is shown in the accompanying table:

As manager over the Home4U Rental Company, you have been asked to present a PowerPoint presentation to upper management and stakeholders. Presentation should analyze the following statistical data output from the data represented in the Excel file "Rental" and explain the implications of these results.

Requirements:

The presentation will address the following eight steps.

1. Estimate the model Rent = ₀ + ₁Beds + ₂Baths + ₃Sqft + .
   1. Explain what the beta coefficients reveal about the impact of each predictor variable on rental charges.
2. Examine the joint significance of the predictor variables at the 1% level.
   1. First, specify the competing hypotheses and the type of test run.
   2. Find the p-value. What is a p-value, and what does it tell you?
3. What is the conclusion to the test?
   1. Explain why you drew the conclusion you did.
4. Examine the individual significance of the predictor variables at the 1% level.
   1. State the competing hypotheses, then explain how this test is different than the previous test run.
5. For each predictor variable, state the p-value and determine whether the predictor variable is significant in explaining Rental Charges. Complete the table below.
   1. Discuss each predictor variable one at a time, state the conclusions drawn about each, and why that conclusion was drawn.
   2. Complete the table below.

Predictor Variables

p-value

Significant in Explaining Rental charges

Beds Baths

Square footage

1. Is there any evidence of multicollinearity?
   1. Provide a practical definition of multicollinearity.
   2. What statistic(s) do you use to evaluate multicollinearity?
   3. What is your criteria for determining if multicollinearity is present?

1. A graph of the residuals against the predicted values is shown below. Identify if there is any evidence of changing variability.
   1. Identify the two variables plotted here.
   2. Explain what you are looking for in this graph.