Tag: econometrics
The Difference Between Pearson Correlation and Spearman Rank Correlation in Research
For those currently conducting data analysis, correlation tests are commonly used to measure the relationship between two variables. However, not all correlation tests are suitable for every type of data. As we all know, data types and characteristics can vary.
Dummy Variables in Multiple Linear Regression Analysis with the OLS Method
Multiple linear regression analysis is a well-known technique frequently used by researchers to analyze the influence of independent variables on dependent variables. The ordinary least squares (OLS) method is one of the most commonly used methods in this analysis.
Interpreting Negative Intercept in Regression
When conducting regression analysis, we obtain the intercept and coefficient estimates for each independent variable. These values, both intercept and coefficients, can be positive or negative.
Choosing the Right Variables in Linear Regression using the OLS Method
Linear regression analysis is frequently employed by researchers to investigate the impact of independent variables on dependent variables. The Ordinary Least Squares (OLS) method is a popular choice among scholars for estimating parameters in linear regression models. The OLS technique aims to minimize the squared differences between observed and predicted values.
How to Analyze Correlation and Interpret for Variables Measured Using the Likert Scale
Researchers can choose correlation analysis to examine the relationship between variables. The selection of correlation analysis techniques depends on the scale of measurement used for the data. In statistics, the data measurement scale of a variable consists of nominal, ordinal, interval, and ratio scales.
How to Interpret the Coefficient of Determination (R-squared) in Linear Regression Analysis
The coefficient of determination (R-squared) is a statistical metric used in linear regression analysis to measure how well independent variables explain the dependent variable. It indicates the quality of the linear regression model created in a research study.
Assumptions Required in Multiple Linear Regression Analysis Using Ordinary Least Squares (OLS) Method
Multiple linear regression with the Ordinary Least Squares (OLS) method is one of the statistical techniques used to assess the influence of two or more independent variables on a dependent variable. The OLS method is carried out by minimizing the sum of squared errors between the model’s predictions and the actual values of the dependent variable.
Understanding Normality Test in Ordinary Least Squares Linear Regression
Linear regression analysis examines the influence of independent variables on dependent variables. This analysis can take the form of simple linear regression or multiple linear regression. Most linear regression analyses utilize the Ordinary Least Squares (OLS) method.