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R Statistics Essential Training

Course Summary

 Use R to model statistical relationships using its graphs, calculations, tests, and other analysis tools.


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    Course Syllabus

    •  Introduction
      • Welcome
      • Using the exercise files
      • Using the challenges
    • Getting Started
      • Installing R on your computer
      • Using RStudio
      • Taking a first look at the interface
      • Installing and managing packages
      • Using built-in datasets in R
      • Entering data manually
      • Importing data
      • Converting tabular data to row data
      • Working with color in R
      • Exploring color with Colorbrewer
      • Challenge: Creating color palettes in R
      • Solution: Creating color palettes in R
    • Charts for One Variable
      • Creating bar charts for categorical variables
      • Creating pie charts for categorical variables
      • Creating histograms for quantitative variables
      • Creating box plots for quantitative variables
      • Overlaying plots
      • Saving images
      • Challenge: Layering plots
      • Solution: Layering plots
    • Statistics for One Variable
      • Calculating frequencies
      • Calculating descriptives
      • Using a single proportion: Hypothesis test and confidence interval
      • Using a single mean: Hypothesis test and confidence interval
      • Using a single categorical variable: One sample chi-square test
      • Examining robust statistics for univariate analyses
      • Challenge: Calculating descriptive statistics
      • Solution: Calculating descriptive statistics
    • Modifying Data
      • Examining outliers
      • Transforming variables
      • Computing composite variables
      • Coding missing data
      • Challenge: Transforming skewed data to pull in outliers
      • Solution: Transforming skewed data to pull in outliers
    • Working with the Data File
      • Selecting cases
      • Analyzing by subgroup
      • Merging files
      • Challenge: Analyzing guinea pig data subgroups
      • Solution: Analyzing guinea pig data subgroups
    • Charts for Associations
      • Creating bar charts of group means
      • Creating grouped box plots
      • Creating scatter plots
      • Challenge: Creating your own grouped box plots
      • Solution: Creating your own grouped box plots
    • Statistics for Associations
      • Calculating correlation
      • Computing a bivariate regression
      • Comparing means with the t-test
      • Comparing paired means: Paired t-test
      • Comparing means with a one-factor analysis of variance (ANOVA)
      • Comparing proportions
      • Creating cross tabs for categorical variables
      • Computing robust statistics for bivariate associations
      • Challenge: Comparing proportions across several different groups
      • Solution: Comparing proportions across several different groups
    • Charts for Three or More Variables
      • Creating clustered bar charts for means
      • Creating scatter plots for grouped data
      • Creating scatter plot matrices
      • Creating 3D scatter plots
      • Challenge: Creating your own scatter plot matrix
      • Solution: Creating your own scatter plot matrix
    • Statistics for Three or More Variables
      • Computing a multiple regression
      • Comparing means with a two-factor ANOVA
      • Conducting a cluster analysis
      • Conducting a principal components/factor analysis
      • Challenge: Creating a cluster analysis of states in the US
      • Solution: Creating a cluster analysis of states in the US
    • Conclusion
      • Next steps


Course Fee:
USD 25

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 5 hours / week

This course is listed under Development & Implementations and Data & Information Management Community

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