Difference between revisions of "De Veaux Map"
From Sean_Carver
(→Chapter 6: Scatterplots, Association, and Correlation) |
(→Chapter 6: Scatterplots, Association, and Correlation) |
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::::"Quantitative variables condition," | ::::"Quantitative variables condition," | ||
::::"Straight enough condition," | ::::"Straight enough condition," | ||
− | ::::" | + | ::::"No outliers condition" |
* 6.3: Warning: Correlation Does Not Equal Causation | * 6.3: Warning: Correlation Does Not Equal Causation | ||
* 6.4: Straightening Scatterplots | * 6.4: Straightening Scatterplots |
Revision as of 17:58, 17 November 2018
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
Part II: Exploring Relationships Between Variables
Chapter 6: Scatterplots, Association, and Correlation
- 6.1: Scatterplots
- Direction (negative or positive)
- Form
- Strength
- Outliers
- Explanatory and response variables
- 6.2: Correlation
- Formula
- Assumptions and conditions for correlation, including...
- "Quantitative variables condition,"
- "Straight enough condition,"
- "No outliers condition"
- 6.3: Warning: Correlation Does Not Equal Causation
- 6.4: Straightening Scatterplots