Tag: Regression Analysis
How to Conduct a Normality Test in Simple Linear Regression Analysis Using R Studio and How to Interpret the Results
The Ordinary Least Squares (OLS) method in simple linear regression analysis is a statistical technique aimed at understanding the influence of an independent variable on a dependent variable. In simple linear regression, there is only one dependent variable and one independent variable.
Simple Linear Regression Analysis Using R Studio and How to Interpret It
In the real world, accurate decisions need to be based on a deep understanding of data. One tool for processing and elaborating data is simple linear regression analysis. Simple linear regression analysis allows us to read patterns among scattered data points. A correct understanding of regression analysis gives us the power to make more accurate decisions and minimize uncertainty.
Binary Logistic Regression Analysis in Research | Basic Theory
Regression analysis has become a staple tool among researchers. Indeed, regression analysis serves as a familiar associative test, aiming to discern the impact of one variable on another.
How to Interpret Dummy Variables in Ordinary Least Squares Linear Regression Analysis
Dummy variables, which have non-parametric measurement scales, can be used in specifying linear regression equations. The linear regression equation I’m referring to here is the ordinary least squares (OLS) method. As we already know, most variables are measured on interval and ratio scales in ordinary least squares linear regression equations.
Hypothesis Testing: Unveiling Insights in Multiple Linear Regression Analysis
In inferential statistics, we need to formulate research hypotheses. These research hypotheses are formulated according to the research objectives. Furthermore, statistical hypotheses need to be established in the analysis method, consisting of null and alternative hypotheses.