Join Conrad Carlberg for an in-depth discussion in this video Basic descriptive statistics in DescTools, part of R for Excel Users.
- View Offline
- [Voiceover] Now what do these mean?…Well the length of the pizza data frame is 1,2090 records.…There are that many records in it.…Of those records we find 39 not applicables…so subtracting the non applicables from…the total length of the data set…and we wind up with 1,170 useful records…for the variable temperature.…There are 375 unique different values for temperature.…We have zero zeros in the data set…and now we get into the more distributional information…arithmetic mean, that is the total of all…of the temperature values divided by 1,170.…
It is 47.937.…MeanSE refers to the standard error of the mean.…If you're not familiar with that.…Here's a brief tour.…Suppose that we took repeated samples,…many repeated samples.…Hundreds or even thousands of repeated samples…from the population that this data came from,…and each time we took a sample of 1,170 valid records,…and we calculated the mean of that sample.…
Now we do that hundreds or even thousands of times…and all of those means will have a standard deviation…
Much of the course focuses on how crucial statistical tasks and operations are done in R—often with the DescTools package—as contrasted with Excel's functions and Data Analysis add-in, and then scales up from there, showing R's more powerful features. Conrad Carlberg will help you effectively toggle between both programs, moving data back and forth so you can get the best of both worlds. Start by learning how to install R and the DescTools package, and the data files used in all the hands-on exercises. Then learn about calculating descriptive statistics on numeric and nominal variables, and running bivariate analyses in both Excel and R. In the "Next steps" video, Conrad breaks down the pros and cons of Excel vs. R and provides tips for learning more about statistics in each application.
- Installing R and DescTools
- Descriptive statistics in Excel and DescTools
- Moving data between R and Excel
- Running the Desc function
- Bivariate analysis in R and Excel