When a Two-Way ANOVA produces significant results, you compare sample means in order to focus on intergroup differences. You plan these comparisons before you gather the data. Because the Two-Way ANOVA assesses two independent variables, post-analysis testing requires more steps than the single-variable Between-Groups ANOVA. This video shows you how to perform these post-ANOVA comparisons to fully understand the source of the significance in the ANOVA.
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- [Voiceover] Now I'll show you what to do…after a significant two-factor analysis of variance.…A significant ANOVA isn't really an end.…It's a beginning.…It just tells you that you have a difference…somewhere in your set of means.…To better understand your data,…you have to do some post-analysis tests…to zero in on where those differences are.…And this is especially true when you have an interaction.…Here are the results from a two-factor study…of the protection provided…by four kinds of lacrosse helmets.…Each helmet was dropped ten times from 152 centimeters…to take impact in the front,…and ten times to take impact in the rear.…
The dependent variable is called GSI,…and a lower value indicates more protection.…The ANOVA table indicates two main effects.…The F ratios in cells E25 and E26,…and significant interaction,…the F ratio in cell E27.…When you have an interaction, you have to be careful…about interpreting main effects.…For example, we can't just say we have a main effect…of hit location, greater protection against front hits…
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