Lynda - R Statistics Essential Training

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leechers: 7
Added on October 12, 2013 by Zilch01in Other > Tutorials
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Lynda - R Statistics Essential Training (Size: 1.05 GB)
 8.Converting tabular data to row data.mp439.55 MB
 4.Installing and managing packages.mp438.41 MB
 9.Working with color in R.mp431.66 MB
 3.Taking a first look at the interface.mp429.22 MB
 7.Importing data.mp424.25 MB
 10.Exploring color with Colorbrewer.mp421.1 MB
 5.Using built-in datasets in R.mp417.77 MB
 6.Entering data manually.mp413.06 MB
 2.Using RStudio.mp412.01 MB
 1.Installing R on your computer.mp410.99 MB
 1.Creating bar charts for categorical variables.mp425.39 MB
 4.Creating box plots for quantitative variables.mp422.87 MB
 2.Creating pie charts for categorical variables.mp421.56 MB
 5.Overlaying plots.mp421.48 MB
 3.Creating histograms for quantitative variables.mp417.72 MB
 6.Saving images.mp417.26 MB
 8.Solution Layering plots.mp45.74 MB
 7.Challenge Layering plots.mp41.22 MB
 6.Examining robust statistics for univariate analyses.mp423.13 MB
 2.Calculating descriptives.mp417.18 MB
 5.Using a single categorical variable One sample chi-square test.mp415.59 MB
 4.Using a single mean Hypothesis test and confidence interval.mp411.75 MB
 3.Using a single proportion Hypothesis test and confidence interval.mp49.93 MB
 1.Calculating frequencies.mp49.72 MB
 8.Solution Calculating descriptive statistics.mp46.35 MB
 7.Challenge Calculating descriptive statistics.mp41.18 MB
 2.Transforming variables.mp428.82 MB
 3.Computing composite variables.mp417.55 MB
 1.Examining outliers.mp416.94 MB
 4.Coding missing data.mp415.18 MB
 6.Solution Transforming skewed data to pull in outliers.mp46.64 MB
 5.Challenge Transforming skewed data to pull in outliers.mp41.49 MB
 1.Selecting cases.mp417.69 MB
 3.Merging files.mp416.65 MB
 2.Analyzing by subgroup.mp410.26 MB
 5.Solution Analyzing guinea pig data subgroups.mp44.12 MB
 4.Challenge Analyzing guinea pig data subgroups.mp41.17 MB
 2.Creating grouped box plots.mp416.07 MB
 3.Creating scatter plots.mp413.76 MB
 5.Solution Creating your own grouped box plots.mp412.42 MB
 1.Creating bar charts of group means.mp412.17 MB
 4.Challenge Creating your own grouped box plots.mp41.59 MB
 8.Computing robust statistics for bivariate associations.mp427.5 MB
 5.Comparing means with a one-factor analysis of variance (ANOVA).mp426.12 MB
 2.Computing a bivariate regression.mp419.24 MB
 3.Comparing means with the t-test.mp418.87 MB
 4.Comparing paired means Paired t-test.mp418.8 MB
 7.Creating cross tabs for categorical variables.mp416.43 MB
 1.Calculating correlation.mp412.5 MB
 10.Solution Comparing proportions across several different groups.mp411.91 MB
 6.Comparing proportions.mp48.69 MB
 9.Challenge Comparing proportions across several different groups.mp42.21 MB
 3.Creating scatter plot matrices.mp419.42 MB
 4.Creating 3D scatter plots.mp416.5 MB
 6.Solution Creating your own scatter plot matrix.mp415.02 MB
 1.Creating clustered bar charts for means.mp410.39 MB
 2.Creating scatter plots for grouped data.mp47.77 MB
 5.Challenge Creating your own scatter plot matrix.mp41.54 MB
 3.Conducting a cluster analysis.mp446.59 MB
 4.Conducting a principal componentsfactor analysis.mp434.12 MB
 1.Computing a multiple regression.mp430.65 MB
 2.Comparing means with a two-factor ANOVA.mp415.83 MB
 6.Solution Creating a cluster analysis of states in the US.mp414.25 MB
 5.Challenge Creating a cluster analysis of states in the US.mp41.39 MB
 1.Next steps.mp412.14 MB
 Ex_Files_RStats_EssT.zip413.41 KB
 1.welcome.mp49.47 MB
 3.Using the challenges.mp45.41 MB
 2.Using the exercise files.mp41.07 MB


Description

R is the language of big data 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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seeders:24
leechers:7
Lynda - R Statistics Essential Training

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