OMIS 2010 Chapter Notes - Chapter 16: Regression Analysis, Interval Estimation, Royal Guelphic Order

• School: York University
• Department: Operations Management and Information System
• Course: OMIS 2010
• Professor: Alan Marshall

Document Summary

Regression analysis: used to predict value of one variable on basis of other variables. Independent variable: variable that practitioner believes are related to dependent variables (x1, x2, xk) Deterministic models: equation that allow us to determine value of the dependent variable from values of independent variables. First-order linear model (simple linear regression model): y (dependent variable) = b0 (y-int) (y-int) Draw random samples from population of interest. Calculate sample statistics to estimate b0 and b1. Residuals are observations of the error variable. Minimized sum of squared deviation called sum of squares for error (sse) Residuals are differences between observed values of y1 and y hat. Note: we can"t determine value of y-hat for value of x that is far outside the range of sample values of x. Objective is to see how independent variable is related to dependent variable. When data is observational, both variables are random variable (don"t need to specify which is dependent and which is not)