# Archive | Improve Phase ## Logistic Regression with SigmaXL

What is Logistic Regression? Logistic regression is a statistical method to predict the probability of an event occurring by fitting the data to a logistic curve using logistic function. The regression analysis used for predicting the outcome of a categorical dependent variable, based on one or more predictor variables. The logistic function used to model […] ## Box Cox Transformation with SigmaXL

Box Cox Transformation Box Cox Transformation Formula The formula of the Box Cox transformation is: Where: Use SigmaXL to Perform a Box-Cox Transformation SigmaXL provides the best Box-Cox transformation with an optimal λ that minimizes the model SSE (sum of squared error). Here is an example of how we transform the non-normally distributed response to […] ## Multiple Linear Regression

What is Multiple Linear Regression? Multiple linear regression is a statistical technique to model the relationship between one dependent variable and two or more independent variables by fitting the data set into a linear equation. The difference between simple linear regression and multiple linear regression: Multiple Linear Regression Equation Where: Both dependent and independent variables […] ## Correlation Coefficient with SigmaXL

Pearson’s Correlation Coefficient Pearson’s correlation coefficient is also called Pearson’s r or coefficient of correlation and Pearson’s product moment correlation coefficient (r), where r is a statistic measuring the linear relationship between two variables. What is Correlation? Correlation is a statistical technique that describes whether and how strongly two or more variables are related. Correlation […] ## Simple Linear Regression

What is Simple Linear Regression? Simple linear regression is a statistical technique to fit a straight line through the data points. It models the quantitative relationship between two variables. It is simple because only one predictor variable is involved. It describes how one variable changes according to the change of another variable. Both variables need […]