Practical Statistics for Data Scientists, 2nd Edition

Index

A

• A/B testing, A/B Testing-Further Reading
  • benefits of using a control group, Why Have a Control Group?
  • epsilon-greedy algorithm for, Multi-Arm Bandit Algorithm
  • examples of, A/B Testing
  • hypotheses in, Hypothesis Tests
  • importance of obtaining permissions, Why Just A/B? Why Not C, D,…?
  • multi-arm bandits versus, Multi-Arm Bandit Algorithm
  • traditional, shortcoming of, Why Just A/B? Why Not C, D,…?
• accuracy, Evaluating Classification Models
• Adaboost, Boosting
  • boosting algorithm, The Boosting Algorithm
• adjusted R-squared, Assessing the Model
• adjustment of p-values, Multiple Testing
• agglomerative algorithm, The Agglomerative Algorithm
• AIC (Akaike's Information Criteria), Model Selection and Stepwise Regression, Selecting the Number of Clusters
• AICc, Model Selection and Stepwise Regression
• all subset regression, Model Selection and Stepwise Regression
• alpha, Statistical Significance and p-Values, Alpha
  • alpha inflation, Multiple Testing
• alternative hypothesis, Hypothesis Tests, Alternative Hypothesis
• American Statistical Association (ASA), statement on use of p-values, p-value controversy
• analysis of variance (ANOVA), F-Distribution, ANOVA-Further Reading
  • decomposition of variance, F-Statistic
  • F-statistic, F-Statistic
  • two-way ANOVA, Two-Way ANOVA
• anomaly detection, Regression and Prediction
  • outliers and, Outliers
• arms (multi-arm bandits), Multi-Arm Bandit Algorithm
• AUC (area under the ROC curve), AUC-AUC
• average linkage metric, Measures of Dissimilarity
• average value (see mean)

B

• b-spline (basis spline), Splines