Tag: statistics
Testing and Interpreting Homoscedasticity in Simple Linear Regression with R Studio
Homoscedasticity is a crucial assumption in ordinary least square (OLS) linear regression analysis. This assumption refers to the consistent variability of regression residuals across all predictor values. Homoscedasticity assumes that the spread of residual regression errors remains relatively constant along the regression line.
Descriptive Statistics Analysis in Excel: A Step-by-Step Guide for Researcher
Descriptive statistics analysis is a crucial step in research, aimed at summarizing and illustrating fundamental information from a dataset. Through descriptive statistics, we can present data in a more informative and easily understandable format.
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.
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.
Can Data Transformation Be Done More Than Once?
For those of us accustomed to conducting research, understanding how to analyze data is a crucial skill to master. In the process, when we are processing data, we are sometimes faced with the choice of data transformation.
Easy Guide to Finding the Standard Deviation of Research Variables in Excel
Standard deviation is a statistical metric designed to measure the spread or variation of data within a research variable. You can determine how far each data point is from the average data in that variable through the standard deviation value.
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.