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Home/Archive for: September 2023

Month: September 2023

Nonparametric Statistics

How to Analyze Correlation and Interpret for Variables Measured Using the Likert Scale

By Kanda Data / Date Sep 30.2023

Researchers can choose correlation analysis to examine the relationship between variables. The selection of correlation analysis techniques depends on the scale of measurement used for the data. In statistics, the data measurement scale of a variable consists of nominal, ordinal, interval, and ratio scales.

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Econometrics

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

By Kanda Data / Date Sep 28.2023

The coefficient of determination (R-squared) is a statistical metric used in linear regression analysis to measure how well independent variables explain the dependent variable. It indicates the quality of the linear regression model created in a research study.

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Excel Tutorial for Statistics

How to Easily Activate Data Analysis Tools in Excel for Statistical Analysis

By Kanda Data / Date Sep 27.2023

Microsoft Excel is widely popular among researchers for assisting in various data tabulations and analyses. Excel provides a range of basic statistical functions such as mean, median, mode, standard deviation, and other functions for descriptive statistical analysis.

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Econometrics

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

By Kanda Data / Date Sep 26.2023

Multiple linear regression with the Ordinary Least Squares (OLS) method is one of the statistical techniques used to assess the influence of two or more independent variables on a dependent variable. The OLS method is carried out by minimizing the sum of squared errors between the model’s predictions and the actual values of the dependent variable.

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Excel Tutorial for Statistics

How to Convert Data Transformed with Natural Logarithm (Ln) Back to its Original Form

By Kanda Data / Date Sep 25.2023

Natural logarithm transformation is a commonly used method in the data analysis process. In this transformation, we utilize the natural logarithm (ln) with the constant value ‘e’ to change the original data into a different form, aiming to meet the assumptions required for the selected statistical tests.

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Excel Tutorial for Statistics

How to Use Natural Logarithm Transformation in Excel and Interpret the Results

By Kanda Data / Date Sep 24.2023

Data transformation is an effort to change the measurement scale of raw data into another form so that the data can meet the assumptions required for the chosen statistical test. One form of data transformation is the use of natural logarithm transformation.

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Assumptions of Linear Regression

Understanding Normality Test in Ordinary Least Squares Linear Regression

By Kanda Data / Date Sep 19.2023

Linear regression analysis examines the influence of independent variables on dependent variables. This analysis can take the form of simple linear regression or multiple linear regression. Most linear regression analyses utilize the Ordinary Least Squares (OLS) method.

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Comparison Test

Understanding the t-test for non-normally distributed data

By Kanda Data / Date Sep 18.2023

For researchers aiming to explore the differences between two sample groups, the t-test is a viable option. According to theory, the t-test can determine differences between two sample groups, whether they are paired or independent.

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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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