How do you check the condition of homogeneity of variance (homoscedasticity) for the linear regression model in R and SPSS?
Definition Multicollinearity is a condition where there is a strong correlation between the independent variables in a statistical model. This can occur in a linear regression model when there are multiple independent variables that correlate with each other, creating a type of redundancy in the data. The problem with multicollinearity is that it can affect the...Read More
How to perform a T-test in R: A comprehensive guide
Statistical tests are an indispensable tool in data analysis for testing hypotheses and drawing conclusions from data sets. One of the most commonly used tests is the T-test, which helps to assess whether the mean values of two groups differ statistically significantly from each other. R, a language and environment for statistical computing and graphics, provides...Read More
How to check the condition of normal distribution of residuals for the linear regression model in R and SPSS?
Definition In a linear regression, an attempt is made to model a linear dependence between a dependent variable y and one or more independent variables x. An important assumption here is that the residuals (the difference between the observed values of y and the predicted values of y) are normally distributed. A normal distribution of the...Read More
How do you check the multicollinearity requirement for the linear regression model in R and SPSS?
Definition Multicollinearity is a condition where there is a strong correlation between the independent variables in a statistical model. This can occur in a linear regression model when there are multiple independent variables that correlate with each other, creating a type of redundancy in the data. The problem with multicollinearity is that it can affect the...Read More
How to check the condition of linearity for the linear regression model in R and SPSS?
If you carry out a linear regression, you should also check whether the requirements for this are met. The significance values (p-values) that you obtain in the regression are only accurate if the prerequisites for the regression are met. If the requirements are not met, the correct interpretation of the p-values may be problematic. In...Read More