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NPTEL

Linear Regression Analysis and Forecasting

NPTEL and Indian Institute of Technology Kanpur via YouTube

Overview

COURSE OUTLINE: 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 variables which in turn provides forecasting. For example, the yield of a crop depends upon the area of crop, the 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 the 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.

Syllabus

Basic Fundamental Concepts Of Modelling..
Regression Model-A Statistical Tool.
Simple Linear Regression Analysis.
Estimation Of Parameters In Simple Linear Regression Model.
Estimation Of Parameters In Simple Linear Regression Model (continued) Some Nice Properties.
Estimation Of Parameters In Simple Linear Regression Model (continued).
Maximum Likelihood Estimation of Parameters in Simple Linear Regression Model.
Testing of Hypotheis and Confidence Interval Estimation in Simple Linear Regression Model.
Testing of Hypotheis and Confidence Interval Estimation in Simple Linear Regression Model(Contd).
Software Implementation in Simple Linear Regression Model using MINITAB.
Multiple Linear Regression Model.
Estimation of Model Parameters in Multiple Linear Regression Model.
Estimation of Model Parameters in Multiple Linear Regression Model (continued).
Standardized Regression Coefficients and Testing of Hypothesis.
Testing of Hypothesis (continued) and Goodness of Fit of the Model.
Diagnostics in Multiple Linear Regression Model.
Diagnostics in Multiple Linear Regression Model (continued).
Diagnostics in Multiple Linear Regression Model (continued).
Software Implementation of Multiple Linear Regression Model using MINITAB.
Software Implementation of Multiple Linear Regression Model using MINITAB (continued).
Forecasting in Multiple Linear Regression Model.
Within Sample Forecasting.
Outside Sample Forecasting.
Software Implementation of Forecasting using MINITAB..

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Linear Regression Analysis and Forecasting

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