Regression Regression Regression Regression

V

1. SIMPLE REGRESSION S.VIVITHA 1 ST MFSC

2. What is simple regression? Simple regression is a regression model that estimates the relationship between one independent variable and one dependent variable using a straight line. Both variables should be quantitative.

3. X is independent variable( explanatory variable) Y is dependent variable( explained variable) Eg : your consumption depends on your income

4. Types of Regression 1.Simple and multiple 2.Linear and Non- Linear 3.Total and Partial

5. Simple and Multiple SIMPLE REGRESSION: In case of simple relationship only two variables are considered Eg : The influence of advertising expenditure on sales turnover

6. MULTIPLE REGRESSION: In case of multiple relationship , more than two variables are involved. Here one variable is dependent variable and remaining is an independent variable.

7. Eg : The turnover (y) may depend on advertising expenditure (x) is the income of the people(z). The functional relationship can be expressed as a y = f (x , z).

8. LINEAR AND NON LINEAR LINEAR RELATIONSHIP: The linear relationship based on straight line trend, the equation of which has no power higher than one.

9. NON-LINEAR RELATIONSHIP In case of non-linear relationship curved trend lines are derived. The equations of these are parabolic.

10. TOTAL AND PARTIAL TOTAL: In the case of total relatioships all the important variables are considered normally, They take form of multiple relatioships because most of the economics and business problems are affected by multiplicity of cases.

11. PARTIAL In the case of partial relationship one or more variables are considered, but not all, thus excluding the influence of those not found relevant for a given purpose.