Author: Kanda Data
Understanding the Essence of Assumption Testing in Linear Regression Analysis: Prominent Differences between Cross-Sectional Data and Time Series Data
Linear regression analysis has become one of the primary tools for researchers to explore the influence of independent variables on dependent variables. The Ordinary Least Squares (OLS) method has been a mainstay in conducting this linear regression analysis.
Understanding the Difference Between Paired T-Test and Wilcoxon Test in Statistics
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.
The data that cannot be transformed using natural logarithm (Ln)
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.
Calculation Method of Net Present Value (NPV) in Project Feasibility Studies
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.
How to Determine the F-Table Value (F Critical Value) in Excel
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.
How to Determine the T-table (T critical value) in Excel for Linear Regression Analysis
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.
How to Analyze Correlation between Ratio and Ordinal Scale Variables (Different Measurement Scales)
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.
Tutorial on How to Calculate Residual Values in Excel
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.