Transcription of MATH 3P82 REGRESSION ANALYSIS Lecture Notes
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MATH 3P82 REGRESSION ANALYSIS Lecture Notes
MATH 3P82 REGRESSION ANALYSISL ecture Notesc Jan Vrbik23 Contents1 PREVIEW52 USINGMAPLE7 Basics .. 9 Procedures .. 10 MatrixAlgebra .. 10 Otherusefulcommands: .. 113 SIMPLE REGRESSION13 MaximumLikelihoodMethod .. 15 ConfidenceIntervals .. 17 REGRESSION coefficients .. 18 Residual 19 Hypotheses 20 ModelAdequacy(Lack-of-FitTest).. 20 Weighted REGRESSION .. 22 Correlation .. 24 Large -Sample 26 Confidence interval for the correlation 274 MULTIVARIATE (LINEAR) REGRESSION29 MultivariateNormalDistribution.
>a:= (3.0+4)∗(2−6)+2/3−4/5; a:= −28.13333333 >a/7+9; 4.98095238 >a:= 14/6; a:= 7 3; >a/7+9; a:= 28 3; (from now on, we will omit the >prompt from our examples, showing only what we have to type). Maple can also handle the usual functions such as sin, cos, tan, arcsin, arccos, arctan, exp, ln, sqrt , etc. All angles are always measured ...
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