09 October Summary

Continuing on Regression study, we discussed degrees of freedom in different estimators and error sum of squares calculations. We then looked at Coefficient of Determination and discussed its use/application in Regression analysis and its application with respect to gene expression data study. For next week we will be reading the paper by Dougherty et. al on CoD relevant to our work. Archana gave us a brief overview on estimation by maximum likelihood and went through the formulas used to derive the maximum-likelihood estimators.
Next week we will also discuss the first 2 chapters in Linear Algebra by Prof. Gilbert Strang, namely :
1. Matrices and Gaussian Elimination
2. Vector Spaces.

Online lectures of his are available at : http://web.mit.edu/18.06/www/Video/video-fall-99-new.html

Revised Schedule

Revised Schedule

Date	Topic
9/3	Statistical Distributions
9/8	Statistical Distributions
9/10	Normalization
9/15	Normalization
9/17	Hypothesis Testing
9/22	Hypothesis Testing
9/24	Hypothesis Testing
9/30	P-Value Corrections
10/2	Significance Testing
10/7	Regression Analysis
10/9	Regression Analysis
	Matrices, Gaussian Elimination, Vector Spaces (Ch 1&2)
	Matrices, Gaussian Elimination, Vector Spaces (Ch 1&2)
	Orthogonality and Determinants (Ch 3& 4)
	Orthogonality and Determinants (Ch 3& 4)
	Eigenvalue and EigenVectors (Ch5)
	Eigenvalue and EigenVectors (Ch5)
	Positive Definite Matrices (Ch6)
	Computations with Matrices (Ch7) if possible else Ch 6
	Error Estimation
	Error Estimation
	Feature Selection
	Feature Selection
	Kernel Methods (Classification)
	Kernel Methods (Classification)
	EM Optimization (Clustering)
	EM Optimization (Clustering)