Author: Kanda Data
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.
How to Determine ANOVA Table in Multiple Linear Regression
The statistical software will also display an ANOVA table in multiple linear regression. To understand well, you need to learn how to determine the ANOVA table manually. In this tutorial, I will use Excel.
How to Find Y Predicted, Residual, and Sum of Squares in Multiple Linear Regression
In the previous article, we have determined the value of the predicted Y value, residual value, and sum of squares in simple linear regression. As researchers, we must understand how to find it in multiple linear regression. So, in this article, I will convey a tutorial on how to find the predicted Y value, residual value, and sum of squares in multiple linear regression.
Nominal, ordinal, interval, and ratio scales | Types of Data Measurement
Types of data measurement scales are fundamental to understand well for researchers. Types of data measurement scales in statistics consist of nominal, ordinal, interval, and ratio scales. This article will discuss the different types of data measurement scales.
How to Determine R Square (Coefficient of determination) in Multiple Linear Regression
R Square (coefficient of determination) can be used to test the goodness of fit of a regression model. The value of R Square shows how big the independent variable’s ability to explain the dependent variable is. Because of the high benefit of the R Square value, various statistical software outputs will usually display the R Square value.
How to Calculate bo, b1, and b2 Coefficient Manually in Multiple Linear Regression
It is essential to understand the calculation of the estimated Coefficient of multiple linear regression. Completing these calculations requires an understanding of how to calculate using a mathematical equation formula. But for most people, the manual calculation method is quite difficult.
Multicollinearity Test using Variance Inflation Factor (VIF) in SPSS
Multicollinearity detection is one of the assumption tests that must be performed on multiple linear regression. This assumption test was conducted to obtain the best linear unbiased estimator.
How to Activate and Load the Data Analysis Toolpak in Excel
Until now, Excel has been an office application with many users. Excel can help manage data and process it to produce the required information. But did you know that excel can also perform statistical data processing?