Lynda - R for Excel Users 2016 TUTORiAL | 193 MB

Data scientists who use Excel realize that R is emerging as the new standard for statistical wrangling (especially for larger data sets). This course serves as the perfect bridge for the many Excel-reliant data analysts and business users who need to update their data science skills by learning R.

Data scientists who use Excel realize that R is emerging as the new standard for statistical wrangling (especially for larger data sets). This course serves as the perfect bridge for the many Excel-reliant data analysts and business users who need to update their data science skills by learning R.

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.

Introduction
1m 46s
Welcome
1m 15s
Exercise files
31s
1. Install R
5m 43s
Download and install R's base package
5m 43s
2. Descriptive Statistics in Excel
15m 48s
Excel's Data Analysis add-in
6m 38s
Descriptive statistics in Excel
9m 10s
3. Working between R and Excel
14m 56s
Install DescTools in R
3m 59s
Move data from Excel to R
6m 27s
Move data from R to Excel
4m 30s
4. Introduction to DescTools
10m 41s
Control the numeric format of output in R
4m 57s
Basic descriptive statistics in DescTools
5m 44s
5. DescTools Output
4m 51s
Run the Desc function on numeric variables
2m 44s
Run the Desc function on nominal variables
2m 7s
6. Bivariate Analysis in R
16m 42s
Analyze one numeric variable by another in R
5m 18s
Analyze a numeric variable against a factor in R
4m 36s
Analyze one factor by another in R
6m 48s
7. Bivariate Analysis in Excel
15m 39s
Analyze one numeric variable by another in Excel
6m 30s
Analyze a numeric variable against a factor in Excel
5m 16s
Analyze one factor by another in Excel
3m 53s
Conclusion
1m 1s
Next steps
1m 1s

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