The Between-Groups Two-Way ANOVA enables you to assess the effects of two independent variables in just one study. In this design, each sample experiences a different combination of the levels of the independent variables. Joe shows you the concepts behind this technique and how to use Excel's Tool Pak to analyze the data for two-variable studies.
- View Offline
- [Voiceover] Now I'm going to tell you how to analyze…two independent variables at once.…This is called a two-factor ANOVA,…also known as a two-way ANOVA.…It's important to know how to do this…because you can save a lot of time…by setting up a study that looks…at two variables rather than one.…Another important point is that the two variables…might interact in ways that produce interesting effects,…effects you wouldn't know about if you…studied each variable separately.…Here's an example.…Assess the protection provided…by four kinds of lacrosse helmets.…Each helmet was dropped 10 times…from a height of 152 centimeters to take a hit in the front,…and also dropped 10 times to take a hit in the rear.…
Two of the helmets have contemporary design,…and two follow traditional design.…So we have two independent variables,…or factors, helmet and hit location.…We have four helmets so helmet is said…to have four levels, and hit location,…front versus rear, has two levels.…So we can call this a two by four design.…I labeled these helmets A through D.…
He explains how to organize and present data and how to draw conclusions using Excel's functions, charts, and 3D maps and the Solver and Analysis ToolPak add-ons. Learn to calculate mean, variance, standard deviation, and correlation; visualize sampling distributions; and test differences with analysis of variance (ANOVA). Then find out how to use linear, multiple, and nonlinear regression testing to analyze relationships between variables and make predictions. Joseph also shows how to perform advanced correlations, variable frequency testing, and simulations.
By the end of this course, you should have the foundational knowledge you need to take other statistics-related courses and perform basic analysis in the workplace.
- Using Excel's statistical functions and 3D charts
- Visualizing sampling distributions
- Performing comparisons with ANOVA
- Performing two-way analysis with ANOVA
- Analyzing linear regression
- Performing multiple regression and nonlinear regression analysis
- Making advanced correlations
- Testing variable frequencies
- Running simulations