Using Linear Regression test in Research
This easy tutorial will show you how to run Simple Regression Analysis test in SPSS, and how to interpret the result.
Regression analysis is a parametric technique that we can use to examine the relationship between two variables, one dependent and one independent. Firstly, The value of the dependent variable is estimated based on the value of the independent variable. Secondly, the dependent variable is usually denoted by Y, and the independent variable by X. Certainly, the regression equation takes the following form:
where y is a dependent variable, is intercept, is the slope of the regression line, x is the independent variable, and is error term.
Regression analysis is a type of statistical evaluation that enables three things:
Description: Relationships among the dependent variables and we can describe the independent variables as a means of regression analysis.
Estimation: We can estimate the values of the dependent variables from the observed values of the independent variables.
Prognostication: We can identifi the risk factors as an influence the outcome, and we can determined the individual prognoses. (Source)
Assumptions of the Regrression Analysis Test:
Assumptions for simple regression:
- continuous dependent variable
- continuous or dichotomous (1 or 0, dummy variable) independent variable
- normal distribution of data
- no autocorrelation
An Example: Simple Regression Test
This guide will explain, step by step, how to run a Simple Regression Test in SPSS statistical software by using an example.
Firstly, We collected data from students about their level of happiness with their life and level of depression. Moreover, happiness was rated on a scale of 1 to 2, while depression was rated on a scale of 1 to 10. As a result, we wanted to examine how the level of depression predicts the level of happiness.
This easy tutorial will show you how to run a Simple Regression Test in SPSS, and how to interpret the result.