Numerical Methods for Describing Data Distributions
Section 3.3 — Describing Center and Variability for Data Distributions That Are Skewed or Have Outliers
STAT C1000
Welcome!
Collecting Data in Reasonable Ways
Section 1.2 — Statistical Studies: Observation and Experimentation
Section 1.3 — Collecting Data: Planning an Observational Study
Section 1.4 — Collecting Data: Planning an Experiment
Section 1.5 — The Importance of Random Selection and Random Assignment: What Types of Conclusions Are Reasonable?
Graphical Methods for Describing Data Distributions
Section 2.1 — Selecting an Appropriate Graphical Display
Section 2.2 — Displaying Categorical Data: Bar Charts and Comparative Bar Charts
Section 2.3 — Displaying Numerical Data: Dotplots, Stem-and-Leaf Displays, and Histograms
Section 2.4 — Displaying Bivariate Numerical Data: Scatterplots and Time Series Plots
Section 2.5 — Graphical Displays in the Media
Section 2.6 — Bivariate and Multivariable Graphical Displays
Numerical Methods for Describing Data Distributions
Section 3.1 — Selecting Appropriate Numerical Summaries
Section 3.2 — Describing Center and Variability for Data Distributions That Are Approximately Symmetric
Section 3.3 — Describing Center and Variability for Data Distributions That Are Skewed or Have Outliers
Section 3.4 — Summarizing a Data Set: Boxplots
Section 3.5 — Measures of Relative Standing: z-scores and Percentiles
Numerical Methods for Describing Data Distributions
Section 3.3 — Describing Center and Variability for Data Distributions That Are Skewed or Have Outliers
Section 3.3 — Describing Center and Variability for Data Distributions That Are Skewed or Have Outliers