KANDA DATA

  • Home
  • About Us
  • Contact
  • Sitemap
  • Privacy Policy
  • Disclaimer
  • Bimbingan Online Kanda Data
Menu
  • Home
  • About Us
  • Contact
  • Sitemap
  • Privacy Policy
  • Disclaimer
  • Bimbingan Online Kanda Data
Home/Linear regression

Tag: Linear regression

Econometrics

How to Interpret the Coefficient of Determination (R-squared) in Linear Regression Analysis

By Kanda Data / Date Sep 28.2023

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.

Continue Reading
Econometrics

Assumptions Required in Multiple Linear Regression Analysis Using Ordinary Least Squares (OLS) Method

By Kanda Data / Date Sep 26.2023

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.

Continue Reading
Assumptions of Linear Regression

Understanding Normality Test in Ordinary Least Squares Linear Regression

By Kanda Data / Date Sep 19.2023

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.

Continue Reading
Multiple Linear Regression

How to Detect Multicollinearity in Multiple Linear Regression Equations Using the OLS Method

By Kanda Data / Date Sep 15.2023

Multicollinearity testing is one of the assumptions in the least squares method of multiple linear regression. This test is conducted to determine whether there is a strong correlation between independent variables.

Continue Reading
Econometrics

Definition and Purpose of Determining Residual Values in Linear Regression Analysis

By Kanda Data / Date Sep 12.2023

In linear regression analysis, residual values play a crucial role. The residual value is the difference between the actual and predicted Y values. The actual Y value can be obtained from observations or samples of the dependent variable.

Continue Reading
Statistics

How to Create Statistical Hypotheses in Linear Regression, Correlation Analysis, and T-test

By Kanda Data / Date Aug 06.2023

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.

Continue Reading
Previous 1 2 3 4

Categories

  • Article Publication
  • Assumptions of Linear Regression
  • Comparison Test
  • Correlation Test
  • Data Analysis in R
  • Econometrics
  • Excel Tutorial for Statistics
  • Multiple Linear Regression
  • Nonparametric Statistics
  • Profit Analysis
  • Regression Tutorial using Excel
  • Research Methodology
  • Simple Linear Regression
  • Statistics

Popular Post

March 2026
M T W T F S S
 1
2345678
9101112131415
16171819202122
23242526272829
3031  
« Feb    
  • Interpretation of Negative Estimated Coefficients: A Case Study of the Effect of Price on Demand
  • Alternative to the t-test When Data Are Not Normally Distributed
  • When Should Natural Logarithmic Data Transformation Be Applied?
  • Should Data Normality Testing Always Be Performed in Statistical Analysis?
  • Differences in Nominal, Ordinal, Interval, and Ratio Data Measurement Scales for Research
Copyright KANDA DATA 2026. All Rights Reserved