Course Outline
- 
        segmentGetting Started (Don't Skip This Part)
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        segmentStatistics and Data Science: A Modeling Approach
- 
        segmentPART I: EXPLORING VARIATION
- 
        segmentChapter 1 - Welcome to Statistics: A Modeling Approach
- 
        segmentChapter 2 - Understanding Data
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        segmentChapter 3 - Examining Distributions
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        segmentChapter 4 - Explaining Variation
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        segmentPART II: MODELING VARIATION
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        segmentChapter 5 - A Simple Model
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        segmentChapter 6 - Quantifying Error
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        segmentChapter 7 - Adding an Explanatory Variable to the Model
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        segmentChapter 8 - Digging Deeper into Group Models
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        segmentChapter 9 - Models with a Quantitative Explanatory Variable
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        segmentPART III: EVALUATING MODELS
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        segmentChapter 10 - The Logic of Inference
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        segmentChapter 11 - Model Comparison with F
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        segmentChapter 12 - Parameter Estimation and Confidence Intervals
- 
        segmentChapter 13 - What You Have Learned
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        segmentFinishing Up (Don't Skip This Part!)
- 
        segmentResources
list High School / Advanced Statistics and Data Science I (ABC)
      
        
        
          
Book          
        
        
      
      
        
      
      
    
    
  R Sandbox
require(coursekata)
set.seed(22)
x <- round(rnorm(1000, mean=15, sd=10), digits=1)
y <- x[x > 5 & x < 30]
TipPct <- sample(y, 44)
TipExperiment$Check <- (TipExperiment$Tip / TipPct) * 100
set.seed(NULL)
# You can use any of the code you have used in the book hereCK Code: code-sandbox