Author: Kanda Data
Correlation Test for Ratio Scale Variables
Correlation analysis is an associative test to determine the relationship between variables. Correlation tests for parametric variables and non-parametric variables are different. Therefore you need to understand how to choose a correlation test according to statistical rules.
How to Write and Test Statistical Hypotheses in Simple Linear Regression
We need to develop hypotheses when conducting research. A hypothesis is a provisional assumption or statement of the research. The hypothesis needs to be proven, whether true or false, through the research process.
How to Reverse Natural Logarithm to Initial Data in Excel
Researchers often use the natural logarithm form (Ln) transformation. In the previous article, I have written about How to Transform Data into Natural Logarithm (Ln) in Excel.
How to Transform Data into Natural Logarithm (Ln) in Excel
You may have seen research data transformed into other forms in analyzing research data. The data transformation is determined by changing the measurement scale of the original data into another form.
Create Residual and Y Predicted in Excel
Residual and predicted Y have an important role in linear regression analysis using the Ordinary Least Square (OLS) method. Several OLS linear regression method assumptions were conducted to test the residuals, including normally distributed residuals and constant residual variance.
Multiple Linear Regression Analysis and Interpreting the Output in Excel
We can use multiple linear regression analysis to estimate the effect of the independent variable on the dependent variable. Multiple linear regression using at least two independent variables.
The Fundamental Differences of Pearson Correlation, Spearman Rank, Kendall tau, and Chi-Square
The associative correlation test between variables is currently the most frequently chosen by researchers, lecturers, and students to answer research hypotheses. There are several choices of correlation tests that can be chosen, but the selection of correlation tests must follow statistical rules.
How to Calculate Variance, Standard Error, and T-Value in Multiple Linear Regression
Finding variance, standard error, and t-value was an important stage to test the research hypothesis. The formula used in multiple linear regression is different from simple linear regression. On this occasion, I will discuss calculating the multiple linear regression with two independent variables.