Multiple regression is a modeling technique with a wide range of applications. Multiple regression is one of the most widely used modeling techniques in the business world. The insights that multiple regression analysis can provide in almost any business situation and the availability of relevant tools such as spreadsheets and crystal ball simulation software make it a very valuable skill set.
Regression analysis is a modeling technique used to analyze the relationship between a continuous dependent variable Y and one or more independent variables X1, X2, X3...... Multiple regression has the word multiple in it because it evaluates many independent variables as against the simple linear regression that evaluates only one variable X1.
Regression analysis is used for a wide variety of purposes. The application of regression analysis can be classified generally into analysis of data and prediction of variables. Other regression analysis techniques include but are not limited to simple linear regression modeling, curvilinear regression models, polynomial regression models, discriminant analysis models..........(a really long list!).
Graduate Tutor's Statistics Tutor Group is well equipped to tutor you in the various multiple regression analysis models and techniques. Work with our tutors online and learn the concepts underlying the multiple regression analysis techniques. Apply the multiple regression analysis technique on sample data from a wide variety of industries to consolidate your reinforce what you learn. Use commonly available multiple regression analysis tools including microsoft excel or crystal ball software. See a sample of the multiple regression analysis topics, methods and tools you can learn with Graduate Tutor's Statistics Tutor Group below. Please email us if you do not find what a multiple regression analysis topic you are looking for below and we will be happy to assist you in finding what you need.
Multiple Regression Analysis Topics
Introduction to Multiple Regression
Examples of Multiple Regression Applications in Business
Types of Regression Models
Multiple Regression Analysis
Defining "Best Fit" of a Multiple Regression Analysis Model
Solving the Multiple Regression Analysis Model Using Solver
Solving the Regression Model Using the Regression Tool in Microsoft Excel
Evaluating the Fit of the Multiple Regression Analysis Model
Interpreting the R Statistic in a Multiple Regression Model Output
Making Predictions using the Multiple Regression Model
Interpreting the Standard Error in the Multiple Regression Model Output
Prediction Intervals for New Values of Y using the Multiple Regression Model
Confidence Intervals for Mean Values of Y in the Multiple Regression Model
A Note about Extrapolation
Statistical Tests for Population Parameters
Assumptions for the Statistical Tests
A Note about Statistical Tests
Summary of Multiple Regression Analysis
Polynomial Regression Models
Other operations research and statistics topics that Graduate Tutor's Statistics Tutor Group tutor include:
Simple Linear Regression
Time Series Forecasting using Microsoft Excel or Crystal Ball Software
Simulation using Crystal Ball Software
Financial Modeling using Microsoft Excel