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
-
5.12 Chapter 5 Review Questions 2
-
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
-
segmentPART IV: MULTIVARIATE MODELS
-
segmentChapter 12 - Introduction to Multivariate Models
-
segmentChapter 13 - Multivariate Model Comparisons
-
segmentFinishing Up (Don't Skip This Part!)
-
segmentResources
list College / Advanced Statistics and Data Science (ABCD)
Book
5.12 Chapter 5 Review Questions 2
require(coursekata)
# run your code here
CK Code: B1_Code_Review2_01
require(coursekata)
# run your code here
CK Code: B1_Code_Review2_02
require(coursekata)
# run your code here
CK Code: B1_Code_Review2_03
require(coursekata)
# run your code here
CK Code: B1_Code_Review2_04
require(coursekata)
# run your code here
CK Code: B1_Code_Review2_05
require(coursekata)
# run your code here
CK Code: B1_Code_Review2_06
require(coursekata)
# run your code here
CK Code: B1_Code_Review2_07