IS 281

Summer 2017 Assignment 8

 

When you complete the assignment, upload the Excel file by clicking on the Assignment 8 link in the Assignment link on the Course Menu.

 

A. Documentation [1]

1.      Open the assignment workbook, and then save the file as Lastname_ assignment8 (For example, Johnson_ assignment8 if your last name is Johnson).

2.      On the worksheet ‘Part A’, enter your name in cell B2. 

3.      Enter the current date in cell B3.

 

B. Correlation [8]

We want to investigate the relationship between the cost of heating a home and the home’s square footage. The data in the worksheet ‘Part B’ represents the data for a random sample of 10 homes.

1.      Draw a scatter plot. Move the scatter plot to a new worksheet and name this worksheet ‘Scatter Plot’. Add a trendline to the scatter plot. Also display the R-squared (R²) value on the scatter plot.

2.      What does the scatter plot suggest about the relationship between the cost of heating and square footage? Are there any outliers?

3.      What does the R²-value suggest about the relationship between the cost of heating and square footage?

4.      Calculate a matrix of correlation coefficients for the data set.

5.      What does correlation coefficient suggest about the relationship between the cost of heating a home and the home’s square footage?

 

C. Two-Variable Regression [14.5]

The worksheet ‘Part C’ provides the weekly wages (Wages) of 50 women along with their length of service (LOS) with their employer in months. The goal of this analysis is to determine whether length of service predicts wage.

1.      Use Excel to obtain the regression estimates.

2.      Identify the independent and dependent variables.

3.      Write the regression equation.

4.      Interpret the intercept and the slope.

5.      Make a prediction of wage when LOS = 125.

6.      What is the R²? Based on the R², what can you say about the fit of the regression model?

7.      What is the F-statistic for the regression? What is the associated p-value? Is the regression significant?

8.      What is the t-statistic for the intercept? What is the associated p-value? Is the intercept significant?

9.      What is the t-statistic for the slope? What is the associated p-value? Is the slope significant?

 

 

D. Multiple Regression [19]

The worksheet ‘Part D’ provides the takeoff thrust (Thrust) of jet turbine engines along with the temperature of the turbine in degrees Fahrenheit (TurbTemp), the takeoff airflow in pounds per second (AirFlow), and the turbine speed in rpm (TurbSpeed). The goal of this analysis is to determine whether turbine temperature, takeoff airflow, and turbine speed predict takeoff thrust.

1.      Use Excel to obtain the regression estimates

2.      Write the regression equation.

3.      Interpret each regression coefficient.

4.      What is the coefficient of determination (R²). Based on the R², how would you describe the fit of the model?

5.      What is the adjusted R²? Does the model contain useless predictors?

6.      What is the F statistic and its p-value? Based on the p-value, is the regression significant overall at the 0.05 significance level?

7.      Fill the first two columns of the table in the Part E worksheet with the t statistic and the p-value for the t statistic for the intercept and each of the correlation coefficients.

8.      Based on the p-value for the t statistic, fill the last column of the table to indicate whether these regression coefficients are significant or not at the 0.05 significance level.

 

E. Time Series Analysis [7.5]

The worksheet ‘Part F’ provides data on U.S. workers involved in work stoppages.

1.      Use Excel to fit each of the three trends (linear, quadratic, and exponential) to the time series data. Make sure that you display the equation and R-squared value on the each of the charts.

2.      Based on the R² value, which trend model would you choose? Why?

3.      Use each of the three fitted trend equations to make numerical forecasts for the year 2007.

 

 

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Status NEW Posted 14 Aug 2017 03:08 PM My Price 10.00

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