B.Sc. Statistics
6th Semester Syllabus
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MJC-10 : Linear Models (रैखिक मॉडल)
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Unit 1: UNIT I
◦Gauss-Markov set-up: Theory of linear estimation
◦Estimability of linear parametric functions
◦Method of least squares
◦Gauss-Markov theorem
◦Estimation of error variance
Unit 2: UNIT II
◦Regression analysis: Simple regression analysis
◦Estimation and hypothesis testing in case of simple and multiple regression models
◦Concept of model matrix and its use in estimation
Unit 3: UNIT III
◦Analysis of variance: Definitions of fixed
◦Random and mixed effect models
◦Analysis of variance and covariance in one-way classified data for fixed effect models
◦Analysis of variance and covariance in two-way classified data with one observation per cell for fixed effect models
Unit 4: UNIT IV
◦Model checking: Prediction from a fitted model
◦Violation of usual assumptions concerning normality
◦Homoscedasticity and collinearity
◦Diagnostics using quantile-quantile plots
◦Ridge Regression
Reference Books:
- Weisberg, S. (2005): Applied Linear Regression. Wiley.
- Wu, C. F. J. And Hamada, M. (2009): Experiments, Analysis, and Parameter Design Optimization, John Wiley.
- Renchner, A. C. And Schaalje, G. B. (2008): Linear Models in Statistics, John Wiley and Sons.
- Gupta, S. C. and Kapoor, V. K. (2020): Fundamentals of Applied Statistics, S. Chand & Sons, New Delhi.