Example 8.1: Digits of Pi
Example 8.2: Digits of Pi, redux
Example 8.3: pyramid plots
Example 8.4: Including subsetting conditions in output
Example 8.5: bubble plots part 3
Example 8.6: Changing the reference category for categorical variables
Example 8.7: Hosmer and Lemeshow goodness-of-fit
Example 8.8: more Hosmer and Lemeshow
Example 8.9: Contrasts
Example 8.10: Combination dotplot/boxplot (teaching graphic in honor of World Statistics Day)
Example 8.11: violin plots
Example 8.12: Bike ride plot, part 1
Example 8.13: Bike ride plot, part 2
Example 8.14: generating standardized regression coefficients
Example 8.15: Firth logistic regression
Example 8.16: Exact logistic regression
Example 8.17: Logistic regression via MCMC
Example 8.18: A Monte Carlo experiment
Example 8.19: Referencing lists of variables
Example 8.20: Referencing lists of variables, part 2
Example 8.21: latent class analysis
Example 8.22: latent class modeling using randomLCA
Example 8.23: expanding latent class model results
Example 8.24: MplusAutomation and Mplus
Example 8.25: more latent class models (plus a graphical display)
Example 8.26: reading data with variable number of words in a field
Example 8.27: using regular expressions to read data with variable number of words in a field
Example 8.28: should we buy snowstorm insurance?
Example 8.29: risk ratios and odds ratios
Example 8.30: Compare Poisson and negative binomial count models
Example 8.31: Choropleth maps
Example 8.32: The HistData package, sunflower plots, and getting data from R into SAS
Example 8.33: Merging data sets one-to-many
Example 8.34: Robustness of the t test with small n
Example 8.35: True random numbers and using API URLs
Example 8.36: Quadratic equations with real roots
Example 8.37: Read sheets from an Excel file
Example 8.38: Create Excel spreadsheets
Example 8.39: Calculating Cramer's V
Example 8.40: Side-by-side histograms
Example 8.41: Scatterplot with marginal Histogram
Example 8.42: Skewness and kurtosis and more moments