(Week 15-16) Linear regression and Correlation ( r-language)
Introduction to Linear Regression, The Simple Linear Regression Model, Least Squares and the Fitted Model, Properties of the Least Squares Estimators, Multiple Linear Regression and Certain: Nonlinear Regression Models, Estimating the Coefficients, Linear Regression Model Using Matrices and correlation.
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Course Material
- Introduction to Statistics and Sampling Procedure
- Measure of location and dispersion
- Basic probability, sample space, Additive law, conditional probability
- Concept of RAndom variable and It,s probability distribution, discrete and continuous probability distribution
- Mathematical Expectation of Random variable,
- Discrete Probability Distribution (Binomial, negative Binomial, Poisson)
- Continuous Probability distributions (normal, gamma, beta)
- Fundamental Sampling Distribution
- (Week 9-10) intro to statistical inference, point estimation and interval estimation for single and two sample (Practical on R language)
- (Week 11-12) Concept of testing of hypothesis, one sample test
- (Week 13-14) Two sample test concerning with mean and variance ( r-language)
- (Week 15-16) Linear regression and Correlation ( r-language)
- Chapters 12
- Department CS & IT
- Teacher
Muhammad Wasim Amir
