Lab10_Fall2011

Lab10_Fall2011 - EXST 7003 Lab 10 Fall 2011 EXST 7003 Lab 10 Simple Linear Regression Week of November 14th-18th DUE November 29th(Section 1

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EXST 7003 Lab 10 Fall 2011 EXST 7003, Lab 10: Simple Linear Regression Week of: November 14 th -18 th DUE: November 29 th (Section 1) December 2 th (Section 2 and 3) In the previous labs, our objective was to sample from one or more populations and to compare certain parameters either with each other or with a specified value. In a regression analysis, the objectives are slightly different. The purpose of a regression analysis is to observe sample measurements taken on different variables, called factors or independent variables, and to examine the relationship between these variables and a response or dependent variable. This relationship is then expressed as a statistical model called the regression model. Suppose that a response variable Y can be predicted by a linear function of a regressor variable X. You can estimate β 0 , the intercept, and β 1 , the slope, in i i i X Y ε β + + = 1 0 for the observations 1, 2, . .., n. Fitting this model with the REG procedure requires only the following MODEL statement, where y is the outcome variable and x is the regressor variable. = i proc reg; model y=x; run; For example, you might use regression analysis to find out how well you can predict a child's weight if you know that child's height. The following data are from a study of nineteen children. Height and weight are measured for each child. title 'Simple Linear Regression'; data Class; input Name $ Height Weight Age @@; datalines; Alfred 69.0 112.5 14 Alice 56.5 84.0 13 Barbara 65.3 98.0 13 Carol 62.8 102.5 14 Henry 63.5 102.5 14 James 57.3 83.0 12 Jane 59.8 84.5 12 Janet 62.5 112.5 15
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This note was uploaded on 12/28/2011 for the course EXST 7003 taught by Professor Moser,e during the Fall '08 term at LSU.

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Lab10_Fall2011 - EXST 7003 Lab 10 Fall 2011 EXST 7003 Lab 10 Simple Linear Regression Week of November 14th-18th DUE November 29th(Section 1

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