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.

Week

Topics

1

Basic fundamentals, Simple linear regression analysis.

2

Simple linear regression analysis, Multiple linear regression analysis.

3

Multiple linear regression analysis. Diagnostics in multiple linear regression analysis.

4

Forecasting in linear regression models.

Mathematics background up to class 12 is needed. Some minor statistics background is desirable. 1. Introduction to Linear Regression Analysis by Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining (Wiley), Low price Indian edition is available. 2. Applied Regression Analysis by Norman R. Draper, Harry Smith (Wiley), Low price Indian edition is available.

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