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Linear Regression Analysis and Forecasting

Linear Regression Analysis and Forecasting. Instructor: Prof. Shalabh, Department of Mathematics and Statistics, IIT Kanpur. Forecasting is an important aspect of any experimental study. The forecasting can be done by finding the model between the input and output variables. The tools of linear regression analysis help in finding out a statistical model between input variables and output variable which in turn provides forecasting. For example, the yield of a crop depends upon the area of crop, quantity of seeds, rainfall etc. The statistical relation between yield and area of crop, quantity of seeds, rainfall etc. can be determined by the regression analysis and forecasting can be done to know the yield in future. The accuracy of forecasting depends upon the goodness of obtained model. What are its steps and checks required to obtain a good model and in turn, how to do forecasting is being aimed to be taught in this course. (from nptel.ac.in)

Basic Fundamental Concepts of Modeling


Lecture 01 - Basic Fundamental Concepts of Modeling
Lecture 02 - Regression Model - A Statistical Tool
Lecture 03 - Simple Linear Regression Analysis
Lecture 04 - Estimation of Parameters in Simple Linear Regression Model
Lecture 05 - Estimation of Parameters in Simple Linear Regression Model (cont.)
Lecture 06 - Estimation of Parameters in Simple Linear Regression Model (cont.)
Lecture 07 - Maximum Likelihood Estimation of Parameters in Simple Linear Regression Model
Lecture 08 - Testing of Hypothesis and Confidence Interval Estimation in Simple Linear Regression Model
Lecture 09 - Testing of Hypothesis and Confidence Interval Estimation in Simple Linear Regression Model (cont.)
Lecture 10 - Software Implementation in Simple Linear Regression Model using MINITAB
Lecture 11 - Multiple Linear Regression Model
Lecture 12 - Estimation of Model Parameters in Multiple Linear Regression Model
Lecture 13 - Estimation of Model Parameters in Multiple Linear Regression Model (cont.)
Lecture 14 - Standardized Regression Coefficients and Testing of Hypothesis
Lecture 15 - Testing of Hypothesis (cont.), Goodness of Fit of the Model
Lecture 16 - Diagnostics in Multiple Linear Regression Model
Lecture 17 - Diagnostics in Multiple Linear Regression Model (cont.)
Lecture 18 - Diagnostics in Multiple Linear Regression Model (cont.)
Lecture 19 - Software Implementation of Multiple Linear Regression Model using MINITAB
Lecture 20 - Software Implementation of Multiple Linear Regression Model using MINITAB (cont.)
Lecture 21 - Forecasting in Multiple Linear Regression Model
Lecture 22 - Within Sample Forecasting
Lecture 23 - Outside Sample Forecasting
Lecture 24 - Software Implementation of Forecasting using MINITAB

References
Linear Regression Analysis and Forecasting
Instructor: Prof. Shalabh, Department of Mathematics and Statistics, IIT Kanpur. Forecasting is an important aspect of any experimental study.