Lynda R Statistics Essential Training
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Torrent File Content (202 files)
Lynda. R Statistics Essential Training
9. Statistics for Three or More Variables
03. Conducting a cluster analysis.mp4 -
9. Statistics for Three or More Variables
03. Conducting a cluster analysis.mp4 -
46.59 MB
0. Introduction
02. Using the exercise files.mp4 -
02. Using the exercise files.mp4 -
1.07 MB
03. Using the challenges.mp4 -
5.41 MB
1. Getting Started
01. Installing R on your computer.mp4 -
01. Installing R on your computer.mp4 -
10.99 MB
02. Using RStudio.mp4 -
12.01 MB
03. Taking a first look at the interface.mp4 -
29.22 MB
04. Installing and managing packages.mp4 -
38.41 MB
05. Using built-in datasets in R.mp4 -
17.77 MB
06. Entering data manually.mp4 -
13.06 MB
07. Importing data.mp4 -
24.25 MB
08. Converting tabular data to row data.mp4 -
39.55 MB
09. Working with color in R.mp4 -
31.66 MB
10. Exploring color with Colorbrewer.mp4 -
21.1 MB
11. Challenge Creating color palettes in R.mp4 -
3.91 MB
12. Solution Creating color palettes in R.mp4 -
10.37 MB
2. Charts for One Variable
01. Creating bar charts for categorical variables.mp4 -
01. Creating bar charts for categorical variables.mp4 -
25.39 MB
02. Creating pie charts for categorical variables.mp4 -
21.56 MB
03. Creating histograms for quantitative variables.mp4 -
17.72 MB
04. Creating box plots for quantitative variables.mp4 -
22.87 MB
05. Overlaying plots.mp4 -
21.48 MB
06. Saving images.mp4 -
17.26 MB
07. Challenge Layering plots.mp4 -
1.22 MB
08. Solution Layering plots.mp4 -
5.74 MB
3. Statistics for One Variable
01. Calculating frequencies.mp4 -
01. Calculating frequencies.mp4 -
9.72 MB
02. Calculating descriptives.mp4 -
17.18 MB
03. Using a single proportion Hypothesis test and confidence interval.mp4 -
9.93 MB
04. Using a single mean Hypothesis test and confidence interval.mp4 -
11.75 MB
05. Using a single categorical variable One sample chi-square test.mp4 -
15.59 MB
06. Examining robust statistics for univariate analyses.mp4 -
23.13 MB
07. Challenge Calculating descriptive statistics.mp4 -
1.18 MB
08. Solution Calculating descriptive statistics.mp4 -
6.35 MB
4. Modifying Data
01. Examining outliers.mp4 -
01. Examining outliers.mp4 -
16.94 MB
02. Transforming variables.mp4 -
28.82 MB
03. Computing composite variables.mp4 -
17.55 MB
04. Coding missing data.mp4 -
15.18 MB
05. Challenge Transforming skewed data to pull in outliers.mp4 -
1.49 MB
06. Solution Transforming skewed data to pull in outliers.mp4 -
6.64 MB
5. Working with the Data File
01. Selecting cases.mp4 -
01. Selecting cases.mp4 -
17.69 MB
02. Analyzing by subgroup.mp4 -
10.26 MB
03. Merging files.mp4 -
16.65 MB
04. Challenge Analyzing guinea pig data subgroups.mp4 -
1.17 MB
05. Solution Analyzing guinea pig data subgroups.mp4 -
4.12 MB
6. Charts for Associations
01. Creating bar charts of group means.mp4 -
01. Creating bar charts of group means.mp4 -
12.17 MB
02. Creating grouped box plots.mp4 -
16.07 MB
03. Creating scatter plots.mp4 -
13.76 MB
04. Challenge Creating your own grouped box plots.mp4 -
1.59 MB
05. Solution Creating your own grouped box plots.mp4 -
12.42 MB
7. Statistics for Associations
01. Calculating correlation.mp4 -
01. Calculating correlation.mp4 -
12.5 MB
010 .Solution Comparing proportions across several different groups.mp4 -
11.91 MB
02. Computing a bivariate regression.mp4 -
+ Show all torrent content...19.24 MB
Description
Miscellaneous
R is the language of big data—a statistical programming language that helps describe, mine, and test relationships between large amounts of data. Author Barton Poulson shows how to use R to model statistical relationships using graphs, calculations, tests, and other analysis tools. Learn how to enter and modify data; create charts, scatter plots, and histograms; examine outliers; calculate correlations; and compute regressions, bivariate associations, and statistics for three or more variables. Challenge exercises with step-by-step solutions allow you to test your skills as you progress.
Topics include:
Installing R on your computer
Using the built-in datasets
Importing data
Creating bar and pie charts for categorical variables
Creating histograms and box plots for quantitative variables
Calculating frequencies and descriptives
Transforming variables
Coding missing data
Analyzing by subgroups
Creating charts for associations
Calculating correlations
Creating charts and statistics for three or more variables
Creating crosstabs for categorical variables
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