Introduction to RegressionRegression analysis is a statistical process for estimating relationships between variables. It includes many techniques for modeling and analyzing multiple variables, where the focus is on the relationship between a dependent variable and one or more independent variables. Regression analysis helps understand how the typical value of the dependent variable changes when one of the independent variables varies, while the other independent variables remain fixed. Most often, regression analysis estimates the conditional expectation of the dependent variable given the independent variables, that is, the average value of the dependent variable when the independent variables are fixed. More rarely, the emphasis is placed on a quintile or other parameter for locating the conditional distribution of the dependent variable given the independent variables. In all cases, the estimation target is a function of the independent variables called the regression function. In regression analysis, it is also interesting to characterize the variation of the dependent variable around the regression function which can be described by a probability distribution. (Wikipedia, 2014) Simple vs. MultipleSimple regression analysis is a very useful technique for examining the relationship between two variables. This is not as useful as multiple regression analysis. Multiple regression uses a linear function of two or more independent variables to explain variation in a dependent variable. Unlike simple regression where we predict the observed values ​​of the dependent variable, but in multiple regression we can predict the observed values ​​of two or more independent variables. R-squared is a measure of how cl...... middle of paper .... ...t listing each team and the variables. When the data was collected there, value was already added in each team, so the data was also added to see how wrong the model was. Once all this data was entered, the regression was implemented. From the Excel spreadsheet, you can navigate to “Data” and then to “Data Analysis”. Once done, click regression and enter “Y range” and “X range”. To keep things organized, click the labels button and set the confidence level to 95%. Clicking on a new worksheet simply cycles through each worksheet instead of working on a single worksheet. Once everything is finished, click OK and the regression will be completed. This would give you the coefficients, standard error and T statistics. When setting up the regression one can click to have the residual output and see the predicted value as well as the residuals.