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Subject 1. Simple Linear Regression PDF Download

Linear regression is used to quantify the linear relationship between the variable of interest and other variable(s).

The variable being studied is called dependent variable (or response variable). A variable that influences the dependent variable is called an independent variable (or a factor).

For example, you might try to explain small-stock returns (the dependent variable) based on returns to the S&P 500 (the independent variable). Or you might try to explain inflation (the dependent variable) as a function of growth in a country's money supply (the independent variable).

Regression analysis begins with the dependent variable (denoted Y), the variable that you are seeking to explain. The independent variable (denoted X) is the variable you are using to explain changes in the dependent variable. Regression analysis is trying to measure a relationship between these two variables. It tries to measure how much the dependent variable is affected by the independent variable. The regression equation as a whole can be used to determine how related the independent and dependent variables are.

It should be noted that the relationship between the two variables can never be measured with certainty. There always exists other variables that are unknown that may have an effect on the dependent variable.

User Contributed Comments 1

User Comment
jocelyn22 The goal is to fit a line to the observations
on Y and X to minimize the squared deviations from the line;
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I was very pleased with your notes and question bank. I especially like the mock exams because it helped to pull everything together.
Martin Rockenfeldt

Martin Rockenfeldt

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