Course Outline
-
segmentGetting Started (Don't Skip This Part)
-
segmentStatistics and Data Science: A Modeling Approach
-
segmentPART I: EXPLORING VARIATION
-
segmentChapter 1 - Welcome to Statistics: A Modeling Approach
-
segmentChapter 2 - Understanding Data
-
segmentChapter 3 - Examining Distributions
-
segmentChapter 4 - Explaining Variation
-
segmentPART II: MODELING VARIATION
-
segmentChapter 5 - A Simple Model
-
segmentChapter 6 - Quantifying Error
-
segmentChapter 7 - Adding an Explanatory Variable to the Model
-
segmentChapter 8 - Models with a Quantitative Explanatory Variable
-
segmentPART III: EVALUATING MODELS
-
segmentChapter 9 - The Logic of Inference
-
segmentChapter 10 - Model Comparison with F
-
segmentChapter 11 - Parameter Estimation and Confidence Intervals
-
segmentChapter 12 - What You Have Learned
-
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