example_MR4

# example_MR4 - Stat 2225 Multiple Regression Example #4:...

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Stat 2225 Multiple Regression Example #4: Adding and Deleting Variables There were 252 men selected to see how percent body fat depends on the various measurements from the body. In this example, we’re interested in: Response: body percent fat (in %); (Independent) Variables: (1) abdomen circumference (in cm), (2) chest circumference (in cm), (3) knee circumference (in cm) and (4) weight (in lbs). Initial Model: Multiple Regression Analysis ----------------------------------------------------------------------------- Dependent variable: Percent ----------------------------------------------------------------------------- Standard T Parameter Estimate Error Statistic P-Value ----------------------------------------------------------------------------- CONSTANT -17.5065 5.50806 -3.17835 0.0017 Abdomen 0.885166 0.0715378 12.3734 0.0000 Chest -0.211898 0.0890243 -2.38023 0.0181 Knee -0.619469 0.184939 -3.34958 0.0009 ----------------------------------------------------------------------------- Analysis of Variance ----------------------------------------------------------------------------- Source Sum of Squares Df Mean Square F-Ratio P-Value -----------------------------------------------------------------------------

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## This note was uploaded on 01/17/2010 for the course STATS 2225 taught by Professor Li during the Spring '09 term at Langara.

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example_MR4 - Stat 2225 Multiple Regression Example #4:...

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