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MATH 3P82 REGRESSION ANALYSIS Lecture Notes

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MATH 3P82REGRESSION ANALYSISLecture Notesc Jan Vrbik23Contents1PREVIEW52USINGMAPLE7Basi cs ..................................... 9Procedures .................................. 10MatrixAlgebra ................................ 10Otherusefulcommands: ........................ 113 SIMPLE REGRESSION13MaximumLikelihoodMethod ........................ 15ConfidenceIntervals ............................. 17Regression coefficients ......................... 18Residual 19Hypotheses 20ModelAdequacy(Lack-of-FitTest)........ ............. 20Weighted REGRESSION . ............................ 22Correlation .................................. 24Large -Sample 26Confidence interval for the correlation 274 multivariate (LINEAR) REGRESSION29MultivariateNormalDistributi on ...................... 29Partial correlation 30Multiple REGRESSION - Main 33Weighted-case 35SearchingforOptimalModel.

values with, inevitably, some random component). The ’independent’ variable xis ... xk- multiple (multivariate) linear regression, 3. a polynomial function of x- polynomial regression, 4. any other type of function, with one or more parameters (e.g. y= aebx) - nonlinear regression.

  Multivariate, Random

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