Regression Analysis: Analysis Of Linear Regression And Correlation

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Linear Regression and Correlation
Correlation and regression analyses are interrelated in an approach that they both deal with the relationship between variables. Correlation portrays the strength of a relationship between two variables, and is entirely proportioned, the correlation between X and Y is identical as the correlation among Y and X. However, if the two variables are associated it means that when one changes by a definite amount the other changes on an average by a certain amount. While in regression, if Y represents the dependent variable and X the independent variable, this relationship is described as the regression of Y on X.
Correlation
The relationship between two variables is known as correlation. It enlightens how much one …show more content…

The outcomes of the analysis, though, require to be understood with concern, predominantly when looking for a fundamental association or when using the regression equation for prediction.
Correlation and linear regression analysis are statistical procedures to enumerate associations between an independent, every now and then called a predictor, variable (X) and a continuous dependent outcome variable (Y). For correlation study, the independent variable (X) can be continuous or ordinal. Regression analysis can also accommodate dichotomous independent variables.
The procedures described here presume that the association between the independent and dependent variables is linear. With some modifications, regression analysis can also be used to estimate associations that go after another practical form (e.g., curvilinear, quadratic). Here we consider associations between one independent variable and one continuous dependent variable. The regression analysis is called simple linear regression - simple in this case refers to the fact that there is a single independent

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