De Veaux Map
From Sean_Carver
Contents
Part I: Exploring and Understanding Data
Chapter 1: Exploring and Understanding Data =
- 1.1: What is Statistics?
- 1.2: Data
- 1.3: Variables
- Types of Variables: Categorical, Quantitative, Identifier, Ordinal
Chapter 2: Displaying and Describing Categorical Data
- 2.1: Summarizing and Displaying a Single Categorical Variable
- The area principle
- Frequency tables
- Bar charts
- Pie charts
- 2.2: Exploring the Relationship Between Two Categorical Variables
- Contingency tables
- Conditional distributions
- Independence
- Plotting conditional distributions (with pie charts, bar charts and segmented bar charts)
Chapter 3: Displaying and Displaying Quantitative Data
- 3.1: Displaying Quantitative Variables
- Histograms
- Stem and leaf displays
- Dotplots
- 3.2: Shape
- Unimodal, bimodal or multimodal
- Symmetric or skewed
- Outliers
- 3.3: Center
- Median
- 3.4: Spread
- Range, min, max
- Interquartile range, Q1, Q3
- 3.5: Boxplots and 5-Number Summaries
- 3.6: The Center of a Symmetric Distribution: The Mean
- Mean or Median?
- 3.7: The Spread of a Symmetric Distribution: The Standard Deviation
- 3.8: Summary---What to Tell About a Quantitative Variable
Chapter 4: Understanding and Comparing Distributions
- 4.1: Comparing Groups with Histograms
- 4.2: Comparing Groups with Boxplots
- 4.3: Outliers
- 4.4: Timeplots
- 4.5: Re-Expressing Data: A First Look
- ...To improve symmetry
- ...To equalize spread across groups
Chapter 5: The Standard Deviation as a Ruler and the Normal Model
- 5.1: Standardizing with z-Scores
- 5.2: Shifting and Scaling
- Shifting to adjust the center
- Rescaling to adjust the scale
- Shifting, scaling and z-Scores
- 5.3: Normal Models
- The "nearly normal condition"
- The 68-95-99.7 Rule
- 5.4: Finding Normal Percentiles
- Normal percentiles
- From percentiles to scores: z in reverse
- 5.5: Normal Probability Plots