Explain your regression models in your own words.

 

The data set shows Sales Price, Area, Number of Rooms, Number of Bedroom, Age and River View

of 63 single family homes.  Sales Price is in thousands and River View indicates whether a home has the

view of river or not. A home with the river view is code as 1 and with no view is given by 0.

 

Using a random sample of 30 to 35 homes conduct three multiple regression analyses: (1) multiple

linear regression with the quantitative variables, (2) multiple linear regression both quantitative

qualitative variables, and (3) multiple regression with interaction.

 

The steps for the analysis are give below:

 

Step 1

Select a sample of 30 to 35 random homes from the data set.  You can do it manually.

Provide the following:

 

Step 2

  1. Specify the regression models.
  2. Explain your regression models in your own words. There are three of them: multiple linear regression with all quantitative variables,multiple linear regression with all the quantitative variables and dummy variable, and multiple linear regression with the quantitative variables and interaction effect.
  3. Explain the basic assumptions in regression model in your words.
  4. Identify the independent and dependent variables.
  5. Explain the nature of the variables.

 

Step 3

  1. Find the descriptive statistic of all the variables.
  2. Generate appropriate charts each variable (pie, bar charts, histogram, box plots, stem-and-leaf, and QQ plot).
  3. Interpret the major findings (in tasks# 6 and #7).

 

Step 4

  1. Conduct the correlation analysis with the software.
  2. Explain the findings of correlation analysis.
  3. Generate scatter plots with the quantitative variables.
  4. Explain the outputs of scatter plots.

 

Step 5

  1. Conduct the following multiple regression analyses with the software (SPSS):
  2. Linear regression analysis with the quantitative variables
  3. Explain the findings of your regression analysis
  4. Conduct one forecast for a set of independent variables and find the residual

iii.     Conduct hypothesis testing for the slope of an independent variable

  1. Conduct interval estimate for the slope of an independent variable
  2. Linear regression analysis with all the six variables which includes the dummy variable
  3. Explain the findings of your regression analysis with the dummy variable
  4. Linear regression analysis all the quantitative variables and an interaction of two independent variables.
  5. Explain the findings of your regression analysis with the interaction effect.

Step 6

  1. Draw conclusions from your analyses.

 

Step 7

  1. Write a report with all the findings, following the format given below.

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