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picture1_Matrix Pdf 174576 | Lecture 13


picture2_Matrix Pdf 174576 | Lecture 13 picture3_Matrix Pdf 174576 | Lecture 13

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File: Matrix Pdf 174576 | Lecture 13
11:55 Wednesday 14th October, 2015 See updates and corrections at http://www.stat.cmu.edu/~cshalizi/mreg/ Lecture 13: Simple Linear Regression in Matrix Format 36-401, Section B, Fall 2015 13 October 2015 ...

icon picture PDF Filetype PDF | Posted on 27 Jan 2023 | 2 years ago

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...Wednesday th october see updates and corrections at http www stat cmu edu cshalizi mreg lecture simple linear regression in matrix format section b fall contents least squares form the basic matrices mean squared error minimizing mse fitted values residuals expectations covariances sampling distribution of estimators derivatives with respect to vectors second maxima minima variances further reading so far we have not used any notions or notation that goes beyond algebra calculus probability this has forced us do a fair amount book keeping as it were by hand is just about tolerable for model one predictor variable will get intolerable if multiple variables fortunately little application let abstract away from lot details make hardly more complicated than version thesenoteswill remind you how works however they review some results throughout bold faced letters denote opposed scalar our data consists n paired observations x response y i e wish t where var uncorrelated across mea surements...
								

							

						
	
												
				
					
					
					
			
					
				
				
		
	

	
		





	

	
				

						

						
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