Can someone walk me through step by step I am new to SPSS The purpose of this assignment is to apply simple regression concepts, interpret simple regression analysis models, and justify business predictions based upon the analysis You will use SPSS to analyze the data set and address the questions presented The business characteristics of n 250 U S trucking and delivery companies for calendar year 2011 were recorded Among the characteristics studied were the number of drivers and the number of trucks (power units) each company employed Part 1 Given that the data consists of counts and range of counts is large, a natural log transformation is usually performed to improve the linear model results Apply a natural log transform to both variables and then plot the Y ln(Trucks) vs X ln(Drivers) Is there a linear relationship Justify your answer by providing the SPSS output as an illustration Part 2 Build a simple linear model by regressing Y on X and testing whether or not a relationship exists between the number of drivers and the number of trucks Address the following questions in your written response After fitting the model, plot the standardized residuals (on vertical axis) vs the standardize predictions (on horizontal axis) Is there a pattern How would you interpret the pattern or lack of pattern After fitting the model, derive the normal probability plot and interpret what the plot means What is the coefficient of determination, R 2 , of the model How would you interpret the R 2 What is the estimate of 1 How would you interpret the estimate of 1 Is the estimate of 1 significantly different than 0 Assume an 0 01 What is a 95 confidence interval for 1 How would you interpret the 95 confidence interval for 1 If a new trucking and delivery company with 4,900 drivers were to be formed, how many trucks would you expect the company would employ based on the model 1 Company Trucks Drivers 2 UPS United Parcel Service 98908 102000 3 FedEx Corp 52287 125497 4 YRC Worldwide 15602 24335 5 Con way Inc 12533 17328 6 Swift Transportation 15900 16600 7 Schneider National Carriers 11780 13400 8 J B Hunt Transport 10512 10000 9 TransForce Inc 11390 12944 10 Landstar System 8371 8371 11 Werner Enterprises 7200 9423 12 U S Xpress Enterprises 7500 8721 13 Estes Express Lines 6655 6894 14 Old Dominion Freight Line 6128 6860 15 UniGroup Inc 10243 6491 16 Arkansas Best Corp 5047 7245 17 CRST International 4359 6737 18 Greatwide Logistics Services 5311 5243 19 C R England 4331 6016 20 Ryder Supply Chain Solutions 3709 4940 21 Prime Inc 4886 5304 22 Kenan Advantage Group N 4433 5538 23 Crete Carrier 5029 5068 24 Sirva Inc Moving Services 3923 3904 25 Saia Inc Johns 3716 4376 26 Averitt Express 3888 4609 27 Knight Transportation 4133 4548 28 R L Carriers 4515 4524 29 Southeastern Freight Lines 3723 4104

The Answer is in the image, click to view ...

Answered step by step

Verified Expert Solution

Link Copied!

Question

1 Approved Answer

Posted on Jul 09, 2024

Can someone walk me through step by step. I am new to SPSS The purpose of this assignment is to apply simple regression concepts, interpret

Can someone walk me through step by step. I am new to SPSS

The purpose of this assignment is to apply simple regression concepts, interpret simple regression analysis models, and justify business predictions based upon the analysis.

You will use SPSS to analyze the data set and address the questions presented.

The business characteristics of n = 250 U.S. trucking and delivery companies for calendar year 2011 were recorded. Among the characteristics studied were the number of drivers and the number of trucks (power units) each company employed.

Part 1:

Given that the data consists of counts and range of counts is large, a natural log transformation is usually performed to improve the linear model results. Apply a natural log transform to both variables and then plot the Y = ln(Trucks) vs. X = ln(Drivers).

Is there a linear relationship? Justify your answer by providing the SPSS output as an illustration.

Part 2:

Build a simple linear model by regressing Y on X and testing whether or not a relationship exists between the number of drivers and the number of trucks. Address the following questions in your written response:

After fitting the model, plot the standardized residuals (on vertical axis) vs. the standardize predictions (on horizontal axis). Is there a pattern? How would you interpret the pattern or lack of pattern?
After fitting the model, derive the normal probability plot and interpret what the plot means.
What is the coefficient of determination, R², of the model? How would you interpret the R²?
What is the estimate of ?₁? How would you interpret the estimate of ?₁?
Is the estimate of ?₁significantly different than 0? Assume an ? = 0.01.
What is a 95% confidence interval for ?₁? How would you interpret the 95% confidence interval for ?₁?
If a new trucking and delivery company with 4,900 drivers were to be formed, how many trucks would you expect the company would employ based on the model?

1 Company Trucks Drivers 2 UPS/United Parcel Service 98908 102000 3 FedEx Corp. 52287 125497 4 YRC Worldwide 15602 24335 5 Con-way Inc. 12533 17328 6 Swift Transportation 15900 16600 7 Schneider National Carriers 11780 13400 8 J.B.Hunt Transport 10512 10000 9 TransForce Inc. 11390 12944 10 Landstar System 8371 8371 11 Werner Enterprises 7200 9423 12 U.S. Xpress Enterprises 7500 8721 13 Estes Express Lines 6655 6894 14 Old Dominion Freight Line 6128 6860 15 UniGroup Inc 10243 6491 16 Arkansas Best Corp 5047 7245 17 CRST International 4359 6737 18 Greatwide Logistics Services 5311 5243 19 C.R. England 4331 6016 20 Ryder Supply Chain Solutions 3709 4940 21 Prime Inc. 4886 5304 22 Kenan Advantage Group N. 4433 5538 23 Crete Carrier 5029 5068 24 Sirva Inc. Moving Services 3923 3904 25 Saia Inc Johns 3716 4376 26 Averitt Express 3888 4609 27 Knight Transportation 4133 4548 28 R+L Carriers 4515 4524 29 Southeastern Freight Lines 3723 4104