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Home/Archive for: January 2024

Month: January 2024

Correlation Test

How to Analyze Correlation between Ratio and Ordinal Scale Variables (Different Measurement Scales)

By Kanda Data / Date Jan 30.2024

In correlation analysis, we often use Pearson correlation to test the relationship between variables measured on a ratio/interval scale. Variables measured on a ratio/interval scale have a greater potential to meet the normality assumption for data testing.

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Simple Linear Regression

Tutorial on How to Calculate Residual Values in Excel

By Kanda Data / Date Jan 24.2024

Regression analysis is already widely used by researchers to explore the influence of independent variables on dependent variables. If we use regression analysis, we must have a good understanding of residual values. These residual values are needed in regression analysis. In addition, in the assumption tests required in linear regression analysis using the ordinary least square method, some also use residual values.

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Multiple Linear Regression

Understanding the Difference Between R-squared and Adjusted R-squared in OLS Linear Regression Output

By Kanda Data / Date Jan 21.2024

R-squared (R²) and Adjusted R-squared (R² adjusted) are key metrics frequently used to assess the effectiveness of a linear regression model. The R-squared value provides information about the proportion of variability in the dependent variable explained by the independent variable in the linear regression equation.

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Statistics

Can nominal scale data be analyzed using regression analysis?

By Kanda Data / Date Jan 16.2024

Regression analysis is commonly used to examine the influence of independent variables on dependent variables observed in a study. However, regression analysis is more suitable for data with interval or ratio scales. How about data with nominal scales, can regression still be used?

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Statistics

Data That Cannot Be Transformed Using Natural Logarithm (Ln)

By Kanda Data / Date Jan 13.2024

In quantitative data analysis, data transformation is not a new concept. It is a process of converting the original form of data into another form to improve the data and meet the assumptions required for quantitative data analysis.

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Statistics

Differences Between Paired Sample T-Test, Independent Sample T-Test, and One-Way ANOVA

By Kanda Data / Date Jan 08.2024

Differential testing is aimed at determining the mean differences in the tested sample groups. In practice, paired sample t-test, independent sample t-test, and one-way ANOVA are often used to test means in more than one sample group.

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Simple Linear Regression

Simple Linear Regression Analysis in Excel and How to Interpret the Results

By Kanda Data / Date Jan 05.2024

Simple linear regression analysis aims to determine the influence of one independent variable on a dependent variable. In this analysis, we can understand and measure how much the independent variable explains the variation in the dependent variable.

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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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  • How to Sort Values from Highest to Lowest in Excel
  • How to Perform Descriptive Statistics in Excel in Under 1 Minute
  • How to Tabulate Data Using Pivot Table for Your Research Results
  • Dummy Variables: A Solution for Categorical Variables in OLS Linear Regression
  • The Difference Between Residual and Error in Statistics
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