Introduction1
Free Resources for this Book7
Cognitive Foundation9
Cognitive Biases12
Confirmation Bias14
Availability Heuristic18
Representativeness Heuristic21
Anchoring Bias26
Framing Effect28
Hindsight Bias31
Dunning-Kruger Effect34
Closing Thoughts38
Probability Mindset43
Probability Overview45
Calculations46
Monty Hall Problem49
Birthday Problem54
Linear vs. Exponential Thinking58
False Positive Paradox58
Base Rate Fallacy62
Conjunction Fallacy66
Gambler's Fallacy70
Law of Large Numbers73
Independent vs. Dependent Events73
Closing Thoughts75
Data Quality: Sampling77
Descriptive Statistics: The Simplest Case79
Inferential Statistics: More Useful but Complicated80
Representative Samples80
Evaluating Representativeness83
Sampling Precision and Bias85
Reducing Random Error to Increase Precision88
Sampling Bias90
What Are Sampling Methods?93
Probability vs Non-Probability Sampling Methods93
Probability Sampling Methods95
Simple Random Sampling (SRS)95
Systematic Sampling98
Stratified Sampling99
Cluster Sampling100
Non-Probability Sampling Methods100
Convenience Sampling101
Example: Early Hormone Replacement Studies103
Example: Colonoscopy Interval105
Other Bias Sources106
Survivorship Bias107
Nonresponse Bias112
Undercoverage Bias115
Attrition Bias119
Symptom Based Sampling122
Advertising Bias122
Avoiding Sampling Bias122
Closing Thoughts124
Data Quality: Measurements127
Accuracy and Precision128
Random Error vs. Systematic Error133
Assessing Accuracy and Precision139
Example: Measuring U.S. GDP142
Good Data is Difficult: Early On-The-Job Learning!146
Closing Thoughts153
Experimental Design155
What is Experimental Design?157
Assigning Subjects to Experimental Groups161
Correlation versus Causation167
Confounding Variables172
Randomized Controlled Trials (RCTs)179
Observational Study: In-Depth Vitamin Example183
Prospective vs. Retrospective Studies186
Internal and External Validity188
Example: Coffee and Cancer Studies195
Anecdotal Evidence197
Closing Thoughts199
Analytics: Basics205
Outliers207
Missing Data214
Aggregated Data223
Simpson's Paradox227
Cautions About Graphing232
Hypothesis Testing Overview235
P-Hacking237
Closing Thoughts245
Analytics: Variability and Signal vs. Noise249
Sample Size: The Foundation of Reliable Statistics255
Sampling Distributions258
Confidence Intervals and Margins of Error266
Statistical Significance268
Benefits of a Large Sample Size269
Limits of Larger Sample Sizes271
Examples: Small Sample Size Problems272
Sample Size Summary275
Regression to the Mean276
Variability Over Time282
Control Charts283
Example: Using a Control Chart in My Study288
Adjusting a Mean is Easier than Reducing Variation289
Closing Thoughts291
Analytics: Multivariate Complexities295
Confounding Variables296
Curvature297
Interaction Effects303
Overfitting and Chance Correlations308
AI Apex311
Closing Thoughts315
My Other Books323
Introduction to Statistics: An Intuitive Guide323
Hypothesis Testing: An Intuitive Guide324
Regression Analysis: An Intuitive Guide326
References327
Recommended Citation for This Book329
Index331
About the Author335