Saturday, July 27, 2024

Statistics

Statistics

What to Do If the Regression Coefficient Is Negative?

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Linear regression is one of the most commonly used statistical analysis techniques to understand the impact of independent variables on a dependent variable. In...

Why Should Data Transformation Be Done Only Once?

Data Transformation to Address Non-Normally Distributed Data

Handling Non-Normally Distributed Data by Removing Outliers

The Differences Between Nominal Data Scale and Ordinal Data Scale in Research Variable Measurement

Econometrics

Econometrics

How to Find Residuals Using the Data Analysis ToolPak in Excel

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Residuals are the differences between the observed values of the dependent variable and the predicted values from the dependent variable. Residuals are an important...
Econometrics

The Difference Between Simultaneous Equation System Model and Linear Regression Equation

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We might all be familiar with linear regression equations, but how many of us have delved deeper into the simultaneous equation system model? It's...

Can Data Transformation Be Done More Than Once?

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

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

Definition and Purpose of Determining Residual Values in Linear Regression Analysis

RESEARCH METHODOLOGY

EXCEL TUTORIAL FOR STATISTICS

Simple Linear Regression

MULTIPLE LINEAR REGRESSION

Multiple Linear Regression

Linear Regression Residual Calculation Formula

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In linear regression analysis, testing residuals is a very common practice. One crucial assumption in linear regression using the least squares method is that...

Multicollinearity Test in Multiple Linear Regression Analysis

Assumption of Residual Normality in Regression Analysis

DATA ANALYSIS IN R

Testing and Interpreting Homoscedasticity in Simple Linear Regression with R Studio

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Homoscedasticity is a crucial assumption in ordinary least square (OLS) linear regression analysis. This assumption refers to the consistent variability of regression residuals across...

How to Conduct a Normality Test in Simple Linear Regression Analysis Using R Studio and How to Interpret the Results

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The Ordinary Least Squares (OLS) method in simple linear regression analysis is a statistical technique aimed at understanding the influence of an independent variable...

Simple Linear Regression Analysis Using R Studio and How to Interpret It

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In the real world, accurate decisions need to be based on a deep understanding of data. One tool for processing and elaborating data is...

How to Test for Normality in Linear Regression Analysis Using R Studio

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Testing for normality in linear regression analysis is a crucial part of inferential method assumptions, requiring regression residuals to be normally distributed. Residuals are...

How to Test Normality of Residuals in Linear Regression and Interpretation in R (Part 4)

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The normality test of residuals is one of the assumptions required in the multiple linear regression analysis using the ordinary least square (OLS) method....

ARTICLE PUBLICATION

How to Write an Abstract of an Article for Publication in a Scientific Journal

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Article Publication
Skills in writing articles, nowadays are increasingly needed. A researcher is not only required to be able to produce novelty in research activities but...

ASSUMPTION OF LINEAR REGRESSION

COMPARISON TEST

NON PARAMETRIC STATISTICS

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