Math 2209 Minitab Assignment on Chapter 24 | Complete Solution

Math 2209                    Minitab Assignment on Chapter 24                            Summer Distance 2016

Is a house listing price a good predictor of its actual selling price? A random sample of 39 houses in Duchess County, New York was taken, and the listing price and actual selling price were recorded. In this assignment, you will look at the relationship between the LIST price (x) and SELL price (y) using regression analysis. If necessary, refer to the Minitab Survival Guide on your Lab Moodle site for more help. Use either Minitab version 17 or Minitab Express (not both!).

MINITAB 17 INSTRUCTIONS

1. Open the Minitab data file HOMES.MTW from your class Moodle site. You will see the data file has 2 columns: C1 is LIST the listed sale price of the home (x, the explanatory variable, in hundred thousand dollars), C2 is SELL, which is actual sale price of the home (y, the response variable, in hundred thousand dollars).

2. Type your name and id number into the session window. 

3. Make a scatterplot of SELL price vs. LIST price, with the regression line plotted on it. 
    To do this, click on Stat > Regression > Fitted Line Plot....
    SELL is the response variable and LIST is the explanatory or predictor variable. Click OK.  

    Print out a copy of this graph. The regression output will appear in your session window. 

4. Perform the regression of SELL on LIST and plot the residuals:
Stat > Regression > Regression > Fit Regression Model…, 
  Choose SELL as the response, LIST as the Continuous Predictor. 
  Choose Graphs .. and select Four in one then hit OK and OK

     Print out a copy of this graph. The regression output will appear in your session window.

5. Find the predicted SELL when the LIST price is 3.500 ($350,000):
            Stat > Regression > Regression > Predict …
             Leave choice as Enter Individual Values and type 3.500 into the first box under LIST.
             Hit OK.  The results will appear in the session window.

6.  Print out a copy of the Session window.

     Once you have completed the above steps, use the output to answer the questions on page 3. 

     Make sure to submit: the page with your answers, the plots, and the session window.
     There will be points for good presentation, and points taken away for poor presentation (which means write 
     clearly and staple your pages!).

MINITAB EXPRESS INSTRUCTIONS ARE ON THE NEXT PAGE.

MINITAB EXPRESS INSTRUCTIONS

1.     Open the Minitab data file HOMES.MTW from your class Moodle site. You will see the data file has 2 columns: C1 is LIST the listed sale price of the home (x, the explanatory variable, in hundred thousand dollars), C2 is SELL, which is actual sale price of the home (y, the response variable, in hundred thousand dollars).

2.    Perform the regression of SELL price on LIST price, make the scatterplot of SELL price vs LIST price with the regression line plotted on it and plot the residuals:
            Statistics > Simple Regression,     
Choose SELL as the Response (Y), LIST as the Predictor (X). 
       Choose Graphs .. and select Residual plots then hit OK and OK
  
        The graphs and regression output appear in the Output window. Print all of this output by choosing
 File > Print.

3.    Find the predicted SELL price when the LIST price is 3.500 ($350,000): 
            Statistics > Predict …
                    Type 3.500 into the first box under LIST. Hit OK.

         The result will appear in the Output window. Choose File > Print to print this output.

4.    In the Minitab spreadsheet, go to Column C3 and row 1. This means you’ll be right beside the 4.000 which is the first value in the SELL column C2. Type Math2209 in this spot.

Express on PC: Next choose Data > To Text. Enter C3 in the box Recode values in the following   columns. 
Express on Mac: Choose Data > Recode > To Text. Then enter C3 in the box values in the following columns.

Under the box Recoded value replace Math2209 with your name and student number. Then hit OK. The output will appear in the Output window. Choose File > Print to print this output.

Make sure to submit: the page with your answers and all your output (plots and regression output). There will be points for good presentation, and points taken away for poor presentation (which means write clearly and staple your pages!).

 
Math 2209        Answer Template for Minitab Assignment on Ch. 24      Name

a)    (16 pts) Check that the assumptions (and conditions) have been met, with reference to the appropriate plots where relevant.  

b)    ( 1 pt) State the regression equation:                     

c)    Perform a test to assess whether the selling price increases with the listing price: 

(i)    (1 pt)  Ho:                          Ha:                  (you don’t need to define the parameter)

(ii)    (2 pts) State the test statistic and p-value from the output: (remember to modify the P-value if needed). 

            Test Statistic:                         P-value:         

(iii)    (1 pt)  Briefly assess the strength of the evidence.

(iv)    (5 pts) Give your conclusion in the context of the problem.

Parts d) and e) on following page

d)    ( 5 pts) On the output, find the 95% CI for the mean selling price for a subpopulation and report it here: 
                                          CI:                 

        Give an interpretation of this 95% CI in full context: 

e)    (6 pts) On the output, find the 95% PI for the selling price and report it here:  
                                          PI:                 

        Give an interpretation of this 95% PI in full context: