Join Joseph Schmuller for an in-depth discussion in this video Need to know, part of Statistics with Excel Part Two.
- [Voiceover] As a prerequisite for this course, it's a good idea to have been through Statistics with Excel Part One, but at least some knowledge of statistics, as this course is geared toward intermediate level students with a bit of statistics under their belts. In many of the examples, I use data from published studies, and you might not be able to get your hands on those studies unless you have access to a university library. You can still work with the data in the exercise files of course. In chapter three, analysis of variance, the example features an equal number of scores per group.
This isn't necessary in analysis of variance in general, or in Excel in particular. I did that for ease of calculation and post-analysis tests. Also in chapter three, the post-analysis tests are applicable to repeated measures ANOVA if you change mean square within to mean square error in the formulas, and degrees of freedom for within to degrees of freedom for error. In chapter four, to simply the analysis, I considered the eight groups to be independent samples, and the numbers within each group to be independent measurements.
In a few of the examples, I provide data that I took from graphs. To do this, I used the web-based application called WebPlotDigitizer. Now you'll need Excel 2016 to follow along with 3D mapping, statistical charts, and one-click forecasting, but otherwise Excel 2013 will be okay. Throughout the course, I advise taking notes, so have a physical notebook or a digital notebook handy.
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