A regression line is conventional lines which efforts to forecast the association between two points, also identified as a trend line or line of best fit. Simple linear regression is a calculation when a variable (y) is reliant on on a second variable (x) based on the regression equation of a given set of figures. More precisely the simple linear regression tells us the relation between selected values of x and observed values of y.

General Concept

The general concept of regression is to study two things

  1. Does a set of forecaster variables do a good job in forecasting a result (dependent) variable?
  2. Which variables in specific are important forecasters of the result variable and in what way do they–point out the scale and sign of the beta estimates–influence the resultant variable?

These regression evaluations are used to clarify the association between one dependent variable and one or more independent variables.  The modest form of the regression equation with one dependent and one independent variable is defined by the formula

 y = c + b*x

Where y = estimated dependent variable score

 c = constant

 b = regression coefficient

x = score on the independent variable.

There are many terms used for a regression’s dependent variable.  It may be called an outcome variable, criterion variable, and endogenous variable.  The independent variables can be called exogenous variables, predictor variables

Main Applications

Three main applications for regression analysis are

  1. Defining the strength of forecasters
  2. Predicting an effect
  3. Trend forecasting.

Initially, the regression might be used to classify the power of the outcome that the independent variable(s) have on a dependent variable.  Usually questions arises that what is the strength of relationship between quantity and effect, sales and marketing spending, or age and income.

Secondly, it can be used to predict things or effect of variations. That is, the regression analysis benefits us to know how much the dependent variable changes with a change in one or more independent variables. 

Thirdly, regression analysis forecasts drifts and future values. The regression analysis can be used to get point estimates.

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November 13, 2018