# econometrics

## 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.