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Author: Kanda Data

Comparison Test

Understanding the Difference Between Paired T-Test and Wilcoxon Test in Statistics

By Kanda Data / Date Mar 15.2024

In the realm of statistics, associative tests play a crucial role in examining differences, relationships, and influences between variables. One common form of associative test is the test for differences, which aims to compare the means of two or more sample groups.

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Assumptions of Linear Regression

The data that cannot be transformed using natural logarithm (Ln)

By Kanda Data / Date Mar 11.2024

In quantitative data analysis, to ensure unbiased and consistent estimations, it’s important to meet several assumptions required in the conducted tests. However, sometimes, the test results may not meet the desired expectations.

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Profit Analysis

Calculation Method of Net Present Value (NPV) in Project Feasibility Studies

By Kanda Data / Date Mar 08.2024

One of the indicators to evaluate the profit potential of an investment project is Net Present Value (NPV). The calculation of NPV forms a strong foundation in project feasibility analysis, enabling business owners to determine whether a project is feasible to pursue or not.

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Multiple Linear Regression

How to Determine the F-Table Value (F Critical Value) in Excel

By Kanda Data / Date Feb 09.2024

In assessing the fit of a linear regression model, researchers need to find the critical values from the F-distribution (F-table). Typically, researchers often use these tables to evaluate the results of regression analysis. However, with technological advancements, determining the F-table value can easily be obtained using Excel.

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Multiple Linear Regression

How to Determine the T-table (T critical value) in Excel for Linear Regression Analysis

By Kanda Data / Date Feb 07.2024

In linear regression analysis, to determine the significance of the regression coefficients, researchers need to find the critical values from the t-student distribution (T-table). Typically, researchers often use these tables to evaluate the results of regression analysis. However, with technological advancements, determining the T-table value can easily be obtained using a spreadsheet, such as Excel.

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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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