Tag: statistics
How to Easily Activate Data Analysis Tools in Excel for Statistical Analysis
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.
Assumptions Required in Multiple Linear Regression Analysis Using Ordinary Least Squares (OLS) Method
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.
How to Convert Data Transformed with Natural Logarithm (Ln) Back to its Original Form
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.
How to Use Natural Logarithm Transformation in Excel and Interpret the Results
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.
Understanding Normality Test in Ordinary Least Squares Linear Regression
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.
Understanding the t-test for non-normally distributed data
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.
How to Detect Multicollinearity in Multiple Linear Regression Equations Using the OLS Method
Multicollinearity testing is one of the assumptions in the least squares method of multiple linear regression. This test is conducted to determine whether there is a strong correlation between independent variables.
Definition and Purpose of Determining Residual Values in Linear Regression Analysis
In linear regression analysis, residual values play a crucial role. The residual value is the difference between the actual and predicted Y values. The actual Y value can be obtained from observations or samples of the dependent variable.