Tag: econometrics
Comparing Logistic Regression and Ordinary Least Squares Linear Regression: Key Differences Explained
The analysis of Ordinary Least Squares (OLS) linear regression is most commonly used to estimate the influence of independent variables on a dependent variable. In OLS linear regression analysis, several assumptions must be fulfilled to obtain the best linear unbiased estimator.
How to Create Statistical Hypotheses in Linear Regression, Correlation Analysis, and T-test
Formulating hypotheses is a crucial step in any research activity. Researchers need to conduct a series of scientifically-based research activities to test these research hypotheses. This series of scientific activities include formulating a research proposal, presenting the proposal in a research proposal seminar to gather feedback, data collection, data analysis, and hypothesis testing to draw research conclusions.
How to Interpret the Output of Correlation Analysis | Hypothesis Testing, Sign, Size, and Direction
Correlation analysis is an associative test commonly used by many researchers to understand the relationship between variables. Before discussing how to interpret the results of correlation analysis, it is essential to understand the basic theory of correlation analysis.
How to Distinguish Cross-Section Data, Time Series Data, and Panel Data
Based on the collection method, data can be divided into cross-section, time series, and panel data. A good understanding of the differences between the three types and how to collect the three types of data will lead to the right choice of analysis.
How to Interpret Negative Coefficients of Linear Regression Output
Regression analysis is commonly used by researchers to analyze influence of independent variables on a dependent variable. But what if the estimated regression coefficient turns out to be negative and its influence is significant? In this article, we will explore and review the based on a case study where the estimation coefficient is negative and how to interpret it in an academic context.
Interpreting the estimation coefficients of dummy variables in linear regression analysis
Linear regression analysis using the Ordinary Least Squares (OLS) method is the most commonly used technique for examining the influence of one variable on another. There are certain assumptions that need to be met when employing linear regression. Assumption testing is necessary to ensure consistent and unbiased estimation results.
How to Analyze Pearson Correlation Using Excel
Correlation analysis is one of the analytical techniques used to test the associative relationship between variables. In correlation analysis, testing can be conducted to answer whether the relationship between variables is significant and how strong and the sign of the relationship between the variables.
How to Interpret Negative Coefficient Estimations in Linear Regression?
The ordinary least squares (OLS) method is commonly employed in linear regression analysis to establish the relationship between the independent and dependent variables. Despite its numerous advantages, researchers must meet certain requirements to use this method.