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Home/Archive for: January 2023

Month: January 2023

Research Methodology

How to Generate a Random Sample using Excel

By Kanda Data / Date Jan 28.2023

The sampling technique of simple random sampling is a sampling method that provides equal opportunities for each member of the population to be selected as a sample. This sampling technique randomly selects the sample from the existing population. To be able to use the simple random sampling technique, researchers need to ensure that there are at least two assumptions that must be met.

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Multiple Linear Regression

Formula to Calculate Analysis of Variance (ANOVA) in Regression Analysis

By Kanda Data / Date Jan 21.2023

In regression analysis, both simple linear regression and multiple linear regression, it is necessary to conduct an analysis of variance calculation to find the statistical F value. The table for the analysis of variance in the regression analysis is called the ANOVA table.

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Comparison Test

Paired Sample T-test: Definition, Analysis Stage, and Interpreting the Results

By Kanda Data / Date Jan 14.2023

Researchers often use the t-test to analyze differences in two sample groups. The t-test that researchers often use consists of the paired sample t-test and the independent sample t-test.

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Multiple Linear Regression

How to Find Residual Value in Multiple Linear Regression using Excel

By Kanda Data / Date Jan 07.2023

Residual values in linear regression analysis can be used to test for normality. In addition, the heteroscedasticity test also requires the variance value of the residual. Therefore, the residual value is important in the linear regression assumption test with the Ordinary Least Square (OLS) method.

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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

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