Transcription of Chapter 305 Multiple Regression - NCSS
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Chapter 305 Multiple Regression - NCSS
NCSS Statistical Software 305-1 NCSS, LLC. All Rights Reserved. Chapter 305 Multiple Regression Introduction Multiple Regression Analysis refers to a set of techniques for studying the straight-line relationships among two or more variables. Multiple Regression estimates the s in the equation jpjpjjj+x++x+x+y 22110= The X s are the independent variables (IV s). Y is the dependent variable . The subscript j represents the observation (row) number. The s are the unknown Regression coefficients. Their estimates are represented by b s. Each represents the original unknown (population) parameter, while b is an estimate of this . The j is the error (residual) of observation j. Although the Regression problem may be solved by a number of techniques, the most-used method is least squares. In least squares Regression analysis, the b s are selected so as to minimize the sum of the squared residuals.
To convert a categorical variable to a form usable in regression analysis, we have to create a new set of numeric variables. If a categorical variable has k values, k - 1 new variables must be generated. There are many ways in which these new variables may be generated. You can use the Contrasts data tool in
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