Cannon Gray 

A combination of methods is required for most projects.  The research objectives and data guide their selection and simplicity is preferred to complexity whenever possible.

Some visitors may wish to know what's in the toolbox, so shown below are some of the approaches, tools and resources Cannon Gray utilizes.

• Experimental and Quasi-Experimental Designs
• Statistical Sampling, Power and Sample Size Estimation
• Descriptive Statistics, Data Visualization
  
• ANOVA, MANOVA, Regression, Nonparametric Methods
• Conjoint Analysis, Choice Modeling, MaxDiff Analysis
• Methods for Categorical, Ordinal and Count Data, Metaheuristics
  
• Correspondence Analysis, PCA, Factor Analysis, ICA, NMF
  
• Path Analysis, PLS, SEM, Growth Models, IRT
• Brand and User Mapping, Social Network Analysis
• Survival Analysis, Propensity Score Analysis, Meta-Analysis
• Epidemiological, Biostatistical and QC Methods, LOF
• Jackknife, Bootstrap, Exact Statistics
• Multiple Imputation, Monte Carlo Simulations
• Fractional Polynomials, Quantile Regression, LOESS
• Panel and Multilevel Mixed Effects Modeling
• IV Regression, 3SLS, GMM, Arellano-Bond, SUR
• Tobit, Interval Regression, Heckit, Hurdle Regression 
• Exponential Smoothing, ARIMA, ARFIMA
• Dynamic Regression, PDL, Prais-Winston
• Cointegrating, Threshold and Switching Regression
• Dynamic Factor Models, VAR, VECM, GARCH
• State-Space, UCM, Spatial Modeling
• Mixture and Latent Class Modeling
• Markov Switching, Mover-Stayer Models
• Bayesian Methods, Bayesian Networks
• AHC, K-means, X-means, PAM, SVC, Canonical Clustering, Co-Clustering
• Latent Class and Bayesian Clustering, SEMM, Cobweb, DBSCAN, OPTICS
• Ridge Regression, LASSO, LARS, Elastic Net, Shapley Value
• Naive Bayes, KNN, Apriori, FP-Growth, CHAID, CART
• Random Forests, CatBoost, LightGBM, XGBoost
• Artificial Neural Networks, Support Vector Machines, GAM, MARS

Cannon Gray Company Library: Some Books and Other Resources

Marketing, Marketing Research and Related

- Journal of Marketing Research (AMA)

- Journal of Marketing (AMA)

- Journal of International Marketing (AMA)

- Journal of Public Policy & Marketing (AMA)

- Journal of Interactive Marketing (AMA)

- International Journal of Market Research (SAGE)

- Journal of Consumer Psychology (Wiley)

- Journal of Consumer Research (Oxford)

- International Journal of Research in Marketing (EMA)

- Journal of Consumer Behavior (Wiley)

- Journal of Advertising Research (ARF)

- Marketing Science (INFORMS)

- Critical Thinking for Marketers (Grapentine et al.)

- Marketing Research (Kinnear and Taylor)

- Essentials of Marketing Research (Zikmund and Babin)

- Handbook of Market Research (Homburg)

- Handbook of Marketing Analytics (Mizik and Hanssens)

- Marketing Management (Kotler and Keller)

- Marketing: Theory, Evidence, Practice (Sharp)

- Marketing Metrics (Farris et al.)

- The Marketing Plan Handbook (Chernev)

- How Not To Plan: 66 Ways To Screw It Up (Binet and Carter)

- Principles of Retailing (Fernie et al.)

- 52 Things About Customer Analytics (Sherman and Sherman)

- Customer Relationship Management (Buttle and Maklan)

- Customer Centricity (Fader)

- The Customer Centricity Playbook (Fader and Toms)

- The High Performance Customer Insight Professional (Smith)

- Digital Marketing (Kaufman and Horton)

- Digital Marketing (Diamond)

- Aaker on Branding (Aaker)

- Building Distinctive Brand Assets (Romaniuk)

- Beloved Brands (Robertson)

- Empirical Generalizations about Marketing Impact (Hanssens)

- Persuasive Advertising (Armstrong)

- The Long and the Short of it (Binet and Field)

- How Brands Grow (Sharp)

- How Brands Grow: Part 2 (Romaniuk and Sharp)

- The Future of Branding (Srivastava and Thomas)

- Eat Your Greens (Snijders)

- Cultures and Organizations (Hofstede et al.)

- The Geography of Thought (Nisbett)

- Asian Brand Strategy (Roll)

- The Halo Effect (Rosenzweig)

- Absolute Value (Simonson and Rosen)

- Contagious: Why Things Catch On (Berger)

- Pre-Suasion (Cialdini)

- Influence (Cialdini)

- Wanting: The Power of Mimetic Desire in Everyday Life (Burgis)

- Inside the Box (Boyd and Goldenberg)

- Seeing What Others Don't (Klein)

- How To Predict Trends and Win The Future (Bhargava)

- UX Strategy (Levy)

- Brand esSense (Gains)

- Advertising In A Digital Age (Taylor)

- The Ad Contrarian (Hoffman)

- Advertising For Skeptics (Hoffman)

- Macroeconomics (Dornbusch et al.)

- Das Kapital (Marx and Engels)

- Human Action (von Mises)

- The Clash of Economic Ideas (White)

- Basic Economics (Sowell)

- Cognition and Chance (Nickerson)

- An Introduction to Decision Theory (Peterson)

- Algorithms to Live By (Christian and Griffiths)

- Simple Heuristics That Make Us Smart (Gigerenzer et al.)

- Risk Savvy: How to Make Good Decisions (Gigerenzer)

- Freakonomics (Levitt and Dubner)

- Everybody Lies (Stephens-Davidowitz)

- Thinking, Fast and Slow (Kahneman)

- Noise: A Flaw in Human Judgment (Kahneman et al.)

- Predictably Irrational (Ariely)

- Behavioural Economics for Business (Williams)

- Herd: How to Change Mass Behaviour (Earls)

- Decoded: The Science Behind Why We Buy (Barden)

- The Choice Factory (Shotton)

- The Behavior Business (Chataway)

- Marketers Are From Mars, Consumers Are From New Jersey (Hoffman)

- Is Behavioral Economics Doomed? (Levine)

- Consumer Behavior: Buying, Having, and Being (Solomon)

- Handbook of Research Methods for Studying Daily Life (Mehl and Conner)

- The Handbook of Behavior Change (Hagger et al.)

- Personality Theories (Ellis et al.)

- Cognitive Psychology (Sternberg and Sternberg)
- The Cognitive Neurosciences (Poeppel et al.)

- Cognitive Neuroscience: The Biology of the Mind (Gazzaniga et al.)

- Brain & Behavior (Garrett)

- Great Myths of the Brain (Jarrett)

- Introduction to Sociology (Griffiths et al.)

- Social Psychology (Richardson)

- The Psychology of Interpersonal Relations (Heider)

- Evolutionary Psychology: The New Science of the Mind (Buss)

- The Secret of Our Success (Henrich)

- Genesis: The Deep Origin of Societies (Wilson)

- The Internet of Things (Greengard)
- The Internet of Things (Miller)

- Big Data, Big Dupe (Few)

- laughing@big data (Jones)

Data Mining and Predictive Analytics

- Statistical Analysis and Data Mining (ASA)

- Analytics Journal (DMA)

- Exploratory Data Analysis (Tukey)

- Recommender Systems Handbook (Ricci et al.)

- Recommender Systems: The Textbook (Aggarwal)

- Statistical Methods for Recommender Systems (Agarwal and Chen)

- Practical Recommender Systems (Falk)

- Introduction to Algorithmic Marketing (Katsov)

- Digital Marketing Analytics (Hartman)

- Automated Machine Learning (Hutter et al.)

- AI for Marketing and Product Innovation (Pradeep et al.)

- Data Matching (Christen)

- Methodological Developments in Data Linkage (Harron et al.)

- A Practitioner's Guide to Business Analytics (Bartlett)
- Introduction to Data Science (Stanton and De Graaf)
- Field Guide to Data Science (Booz Allen Hamilton)
- Data Mining Techniques (Linoff and Berry)
- Handbook of Statistical Analysis and Data Mining Applications (Nisbet et al.)
- Data Mining (Whitten et al.)
- Applied Predictive Modeling (Kuhn and Johnson)

- Statistical and Machine-Learning Data Mining (Ratner)

- Statistical Learning Theory (Vapnik)

- The Nature of Statistical Learning Theory (Vapnik)
- An Introduction to Statistical Learning (James et al.)
- Elements of Statistical Learning (Hastie et al.)

- Behavioral Data Analysis with R and Python (Buisson)
- Data Mining: The Textbook (Aggarwal)

- Essentials of Business Analytics (Pochiraju and Seshadri)

- Data Analytics Using Open-Source Tools (Strickland)

- Practical Machine Learning (Dunning and Friedman)

- Machine Learning: A Probabilistic Perspective (Murphy)

- Pattern Recognition and Machine Learning (Bishop)
- Machine Learning: An Algorithmic Perspective (Marsland)

- Automated Machine Learning (Hutter et al.)

- Machine Learning - The Complete Guide (Wikipedia)

- Statistical Learning with Sparsity (Hastie et al.)
- Neural Networks (Abdi et al.)
- Neural Network Design (Hagan et al.)
- Deep Learning and Neural Networks (Heaton)

- Deep Learning (Goodfellow et al.)

- Neural Networks and Deep Learning: A Textbook (Aggarwal)

- Deep Learning Illustrated (Krohn et al.)

- Dive into Deep Learning (Zhang et al.)

- Deep Learning: A Visual Approach (Glassner)

- Support Vector Machines Applications (Ma and Guo)
- Boosting: Foundations and Algorithms (Schapire and Freund)
- Elementary Applied Topology (Ghrist)

- Independent Component Analysis (Hyvärinen et al.)

- Advances in Independent Component Analysis (Bingham et al.)

- Nonnegative Matrix and Tensor Factorizations (Cichocki et al.)

- Non-negative Matrix Factorization Techniques (Naik)

- Matrix and Tensor Factorization Techniques (Symeonidis and Zioupos)

- RapidMiner (Hofmann and Klinkenberg)
- Exploring Data with RapidMiner (Chisholm)
- Data Mining with Rattle and R (Williams)
- Market Segmentation (Wedel and Kamakura)
- Market Segmentation (McDonald and Dunbar)
- Foundations of Computational Linguistics (Hausser)
- The Handbook of Computational Linguistics (Clark et al.)
- Introduction to Information Retrieval (Manning et al.)
- T-Lab User's Manual: Tools for Text Analysis (Lancia)
- Mining of Massive Datasets (Rajaraman et al.)

- Machine Learning for Text (Aggarwal)

- Practical Text Analytics (Struhl)
- Sentiment Analysis: Mining Opinions, Sentiments, and Emotions (Liu)

- Neural Network Methods in Natural Language Processing (Goldberg)

- TensorFlow for Machine Intelligence (Abrahams et al.)

- Social Media Intelligence (Moe and Schweidel)

- Social Media Marketing (Zimmerman and Ng)

- Natural Language Processing for Social Media (Farzindar and Inkpen)

- Machine Translation (Poibeau)

- Social Network Analysis (Knoke and Yang)

- Network Science (Barabási)

- Analyzing Social Networks (Borgatti et al.)

- Exponential Random Graph Models for Social Networks (Lusher et al.)

- Predictive HR Analytics (Edwards and Edwards)

- Credit-Risk Modelling (Bolder)

- Advances in Financial Machine Learning (Lopez de Prado)

- Intelligent Credit Scoring (Siddiqi)

- Process Mining in Action (Reinkemeyer et al.)  

General Statistical

- The American Statistician (ASA)

- Journal of the American Statistical Association (ASA)

- Statistics in Biopharmaceutical Research (ASA)

- Journal of Agricultural, Biological, and Environmental Statistics (ASA)

- Journal of Statistics Education (ASA)

- Statistics and Public Policy (ASA)

- Journal of Nonparametric Statistics (ASA)

- Journal of Classification (Springer)

- Statistics Surveys (IMS)

- Stata Journal (StataCorp)

- The R Journal (R Project)

- Stata Documentation (StataCorp)

- The Cambridge Dictionary of Statistics (Everitt and Skrondal)

- The Princeton Companion to Applied Mathematics (Higham et al.)

- The HarperCollins Dictionary of Mathematics (Borowski and Borwein)

- The Concise Oxford Dictionary of Mathematics (Clapham and Nicholson)

- NIST Handbook of Mathematical Functions (Olver et al.)

- Numerical Recipes (Press et al.)

- Introduction to Actuarial and Financial Mathematical Methods (Garrett)

- The Magic of Math: Solving for x and Figuring Out Why (Benjamin)

- The Joy of Statistics (Selvin)

- Number Theory (Andrews)
- Essential Mathematics (Gill)

- Mathematics for Machine Learning (Deisenroth et al.)

- Matrix Algebra (Namboodiri)

- Applied Matrix Algebra in the Statistical Sciences (Basilevsky)

- Discrete Mathematics (Gallier)

- A Book of Abstract Algebra (Pinter)
- Multivariable Calculus (Bray)

- Differential Geometry (Kreyszig)

- Splines and Variational Methods (Prenter)

- Methods of Statistical Model Estimation (Hilbe and Robinson)

- Maximum Likelihood Estimation (Eliason)

- Maximum Likelihood Estimation with Stata (Gould et al.)

- Generalized Least Squares (Kariya and Kurata)

- Probability, Statistics and Truth (von Mises)

- Probability Theory: The Logic of Science (Jaynes)

- Introduction to Probability (Bertsekas and Tsitsiklis)

- Introduction to Probability Models (Ross)

- Essentials of Probability Theory for Statisticians (Proschan and Shaw)

- Probability and Stochastics (Çınlar)

- Uncertainty: The Soul of Modeling, Probability & Statistics (Briggs)

- Handbook of Statistical Distributions (Krishnamoorthy)

- Statistical Distributions (Forbes et al.)

- Distributions for Modeling Location, Scale, and Shape (Rigby et al.)

- The Improbability Principle (Hand)

- Apollo’s Arrow (Orrell)

- The Model Thinker (Page)

- Information Theory (Stone)

- Principles of Uncertainty (Kadane)

- Entropy and Information Theory (Gray)

- Silent Risk (Taleb)

- Statistical Consequences of Fat Tails (Taleb)

- Statistical Inference as Severe Testing (Mayo)

- Bernoulli's Fallacy (Clayton)

- Willful Ignorance: The Mismeasure of Uncertainty (Weisberg)

- The Phantom Pattern Problem: The Mirage Of Big Data (Smith and Cordes)

- Game Theory (Spaniel)

- Handbook in Monte Carlo Simulation (Brandimarte)

- Monte Carlo Simulation and Resampling Methods (Carsey and Harden)

- Optimization (Guenin et al.)

- Essentials of Metaheuristics (Luke)

- Clever Algorithms (Brownlee)

- Statistical Quality Control (Montgomery)

- Introduction to Statistical Process Control (Qiu)

- Principles of Risk Analysis (Yoe)

- Risk Management: Concepts and Guidance (Pritchard)

- Extreme Value Modeling and Risk Analysis (Dey and Yan)

- Introduction To Operations Research (Hillier)

- Operations, Logistics and Supply Chain Management (Zijm et al.)

- Supply Chain Analytics Concepts, Techniques and Applications (Liu)

- Statistics Done Wrong (Reinhart)

- John E. Freund's Mathematical Statistics (Miller and Miller)

- All of Statistics (Wasserman)

- Statistics in Plain English (Urdan)

- Introduction to Mathematical Statistics (Hogg et al.)

- Mathematical Statistics and Data Analysis (Rice) 

- Core Statistics (Wood)

- Statistical Inference (Casella and Berger)

- Foundations of Statistics for Data Scientists: With R and Python (Agresti)  

- Statistical Analysis in Psychology and Education (Ferguson and Takane)

- Elementary Business Statistics (Freund et al.)

- 100 Statistical Tests (Kanji)

- Nonparametric Statistical Methods (Hollander et al.)

- Nonparametric Statistics for The Behavioral Sciences (Siegel and Castellan)

- Practical Nonparametric Statistics (Conover)

- Resampling (Simon)

- Bootstrapping (Mooney and Duval)

- Statistical Hypothesis Testing in Context (Fay and Brittain)

- Introduction to Robust Estimation and Hypothesis Testing (Wilcox)

- Applied Missing Data Analysis (Enders)

- Handbook of Missing Data Methodology (Molenberghs et al.)

- Flexible Imputation of Missing Data (van Buuren)

- Outlier Analysis (Aggarwal)

- Information Criteria and Statistical Modeling (Konishi and Kitagawa)

- Data Visualization (Grant)

- Storytelling with Data (Nussbaumer Knaflic)

- Data Visualization: A Practical Introduction (Healy)

- A Visual Guide to Stata Graphics (Mitchell)

- A History of Data Visualization and Graphic Communication (Friendly)

- The Invention of Science: A New History of the Scientific Revolution (Wootton)

- The Scientific Method: A Guide to Finding Useful Knowledge (Armstrong)

- Method in Social Science (Sayer)

- Realism and Complexity in Social Science (Williams)

- The Seven Pillars of Statistical Wisdom (Stigler)

- Philosophy of Social Science (Rosenberg)

- Conjectures and Refutations: The Growth of Scientific Knowledge (Popper)

- The Logic of Scientific Discovery (Popper)

- The Structure of Scientific Revolutions (Kuhn)

- Physics And Philosophy (Heisenberg)

- Schrodinger's Kittens and the Search for Reality (Gribbin)

- The Grand Design (Hawking and Mlodinow)

- Quantum Reality (Baggott)

Bayesian Methods

- Doing Bayesian Data Analysis (Kruschke)

- Bayesian Analysis Made Simple (Woodward)

- The BUGS Book (Lunn et al.)

- Bayesian Methods (Gill)

- Bayesian Ideas and Data Analysis (Christensen et al.)

- Bayesian Data Analysis (Gelman et al.)

- Statistical Rethinking: A Bayesian Course (McElreath)

- Bayesian Thinking in Biostatistics (Rosner et al.)

- Bayesian Statistics and Marketing (Rossi et al.)

- Introduction to Bayesian Econometrics (Greenberg)

- Bayesian Econometric Methods (Koop et al.)

- Bayesian Econometric Methods (Chan et al.)

- Bayesian Forecasting and Dynamic Models (West and Harrison)

- Bayesian Psychometric Modeling (Levy and Mislevy)

- Bayesian Structural Equation Modeling (Depaoli)

- Bayesian Models for Astrophysical Data (Hilbe et al.)

- Bayesian Regression Modeling with INLA (Wang et al.)

- Large-Scale Inference: Empirical Bayes Methods (Efron)

- Handbook of Markov Chain Monte Carlo (Brooks et al.)

- Handbook of Approximate Bayesian Computation (Sisson et al.)

- Fundamentals of Nonparametric Bayesian Inference (Ghosal and van der Vaart)

- Bayesian Time Series Learning with Gaussian Processes (Frigola-Alcalde)

- Gaussian Process Modeling, Design, and Optimization (Gramacy)

- Inference in Bayesian Time-Series Models (Bracegirdle)

- Bayesian Inference of State Space Models (Triantafyllopoulos)

- Risk Assessment and Decision Analysis (Fenton and Neil)

- Bayesian Reasoning and Machine Learning (Barber)

- Bayesian Networks in Educational Assessment (Almond et al.)

- Bayesian Networks (Scutari and Denis)

- Probabilistic Graphical Models (Koller and Friedman)

Research Design and Causal Analysis

- Encyclopedia of Research Design (Salkind)

- Theory Construction and Model-Building (Jaccard and Jacoby)

- Experimental and Quasi-Experimental Designs (Shadish et al.)

- Natural Experiments in the Social Sciences (Dunning)

- Field Experiments Design, Analysis, and Interpretation (Gerber and Green)

- The Oxford Handbook of Causation (Beebee et al.)

- Design of Observational Studies (Rosenbaum)

- Statistical Mediation and Moderation (Jose)

- Introduction to Statistical Mediation Analysis (MacKinnon)

- Mediation, Moderation, and Conditional Process Analysis (Hayes)

- Explanation in Causal Inference (VanderWeele)

- Causality in a Social World (Hong)

- Regression And Mediation Analysis (Muthén et al.)

- Construction of Optimal Stated Choice Experiments (Street and Burgess)

- Experimental Design: Procedures for the Behavioral Sciences (Kirk)

- Design and Analysis of Experiments (Montgomery)

- Design of Experiments for Engineers and Scientists (Antony)

- Design and Analysis (Keppel and Wickens)

- Statistics for Experimenters (Box and Hunter)
- Statistical Analysis of Designed Experiments (Toutenburg and Shalabh)

- Design and Analysis of Experiments (Dean et al.)

- The Design and Analysis of Computer Experiments (Santner et al.)

- Statistical Power Analysis (Murphy et al.)

- The Essential Guide to Effect Sizes (Ellis) 

- Clinical Trials (Brody)

- Principles of Clinical Pharmacology (Atkinson et al.)

- Fundamentals of Clinical Trials (Friedman et al.)

- Bayesian Designs for Phase I-II Clinical Trials (Nguyen et al.)

- Clinical Prediction Models (Steyerberg)

- Case-Control Studies (Keogh and Cox)

- Handbook of Statistical Methods for Case-Control Studies (Borgan et al.)

- Adaptive Design Theory and Implementation (Chang)

- Introduction to Statistical Methods for Clinical Trials (Cook and DeMets) 

- Observation and Experiment (Rosenbaum)

- Mastering 'Metrics (Angrist and Pischke)

- Mostly Harmless Econometrics (Angrist and Pischke)

- Causality: Models, Reasoning and Inference (Pearl)

- The Book of Why: The New Science of Cause and Effect (Pearl and Mackenzie)

- Elements of Causal Inference (Peters et al.) 

- Causal Inference (Imbens and Rubin)

- Counterfactuals and Causal Inference (Morgan and Winship)

- Causal Inference: What If (Hernán and Robins)

- Causal Inference: The Mixtape (Cunningham)

- Causal Inference for Complex Longitudinal Studies (van der Laan and Rose)

- Bit by Bit: Social Research in the Digital Age (Salganik)

- Using Propensity Scores in Quasi-Experimental Designs (Holmes)

- Propensity Score Analysis (Guo and Fraser)

- Propensity Score Analysis (Pan and Bai)

- Practical Propensity Score Methods Using R (Leite)

- Applying Quantitative Bias Analysis to Epidemiologic Data (Fox et al.)

- Introduction to Meta-Analysis (Borenstein et al.)

- Methods of Meta-Analysis (Schmidt and Hunter)

- Meta-Analysis in Stata (Palmer and Sterne)

Sampling 
- Survey Sampling (Kish)
- Sampling Techniques (Cochran)
- Model Assisted Survey Sampling (Särndal et al.)
- Sampling: Design and Analysis (Lohr)
- Practical Tools for Designing and Weighting Survey Samples (Valliant et al.)

- Survey Weights: A Step-by-step Guide to Calculation (Valliant and Dever)

- Complex Surveys (Lumley)
- Hard-to-Survey Populations (Tourangeau et al.)

- Small Area Estimation (Rao and Molina)

Survey Research

- Standards for Educational and Psychological Testing (AERA, APA, NCME)

- Survey Methods and Practices (Statistics Canada)

- Public Opinion Quarterly (AAPOR)

- Survey Practice (AAPOR)

- The Survey Statistician (IASS)

- Journal of Survey Statistics and Methodology (AAPOR and ASA)

- Journal of Educational and Behavioral Statistics (ASA)

- British Journal of Mathematical and Statistical Psychology (Wiley)

- Multivariate Behavioral Research (T&F)

- The Palgrave Handbook of Survey Research (Vannette and Krosnick)

- Online Panel Research (Callegaro et al.)
- The Science of Web Surveys (Tourangeau et al.)
- Web Survey Methodology (Callegaro et al.)
- Internet, Phone, Mail, and Mixed-Mode Surveys (Dillman et al.)
- The Handbook of Mobile Market Research (Poynter et al.)

- The Complete Guide to Writing Questionnaires (Harris)

- Questionnaire Design (Brace)

- Asking Questions (Bradburn et al.)

- Improving Surveys with Paradata (Kreuter et al.)

- Adaptive Survey Design (Schouten et al.)

- Computerized Adaptive and Multistage Testing (Magis et al.)

- Advances in Computer-based Educational Measurement (Veldkamp et al.)

- Games and Gamification in Market Research (Adamou)

- Marketing Scales Handbook (Bruner)

- Handbook of Marketing Scales (Bearden et al.)
- The Psychology of Survey Response (Tourangeau et al.)

- Psychological Statistics and Psychometrics (Baldwin)

- Introduction to Psychometric Theory (Raykov and Marcoulides)
- Psychometrics: An Introduction (Furr)

- Measurement Theory and Applications for the Social Sciences (Bandalos)

- Psychometric Methods: Theory into Practice (Price)

- Modern Psychometrics with R (Mair)

- Thurstonian Models: Categorical Decision Making (Ennis)

- Applied Survey Data Analysis (Heeringa et al.)

- Statistical Approaches to Measurement Invariance (Millsap)

- Psychophysics (Kingdom and Prins)

- Test Equating, Scaling, and Linking (Kolen and Brennan)

- Generalizability Theory (Brennan)

- Handbook of Inter-Rater Reliability (Gwet)

- Handbook of Personality Assessment (Weiner and Greene)

- Measures of Personality and Social Psychological Constructs (Boyle et al.)

- Tests in Print (Buros)
- Reliability and Validity Assessment (Carmines and Zeller)
- Summated Rating Scale Construction (Spector)

- A Course in Rasch Measurement Theory (Andrich and Marais)
- Handbook of Item Response Theory Modeling (Reise and Revicki)

- Handbook of Item Response Theory (van der Linden)

- The Theory and Practice of Item Response Theory (de Ayala)

- Item Response Theory and Modeling (Raykov and Marcoulides)

- Ordinal Item Response Theory: Mokken Scale Analysis (van Schuur)

- Polytomous Item Response Theory Models (Ostini and Nering)

- Handbook of Polytomous Item Response Theory Models (Nering and Ostini)

- Multidimensional Item Response Theory (Reckase)

- Cross-Cultural Analysis: Methods and Applications (Davidov et al.)

- Adapting Psychological Tests for Cross-Cultural Research (Hedrih)

- Latent Class Analysis of Survey Error (Biemer)

- Total Survey Error in Practice (Biemer et al.)

Qualitative Methods 

- Designing Social Inquiry (King et al.)

- Qualitative Inquiry and Research Design (Creswell and Poth)

- Qualitative Research from Start to Finish (Yin)

- Applied Qualitative Research Design (Roller and Lavrakas)
- Qual-Online: The Essential Guide (Dale and Abbott)

- 30 Essential Skills for the Qualitative Researcher (Creswell)
- Content Analysis: An Introduction to Its Methodology (Krippendorff)

- The Coding Manual for Qualitative Researchers (Saldana)

- An Introduction to Language (Fromkin et al.)

- Semiotics: The Basics (Chandler)

- Using Semiotics in Marketing (Lawes)

- Quantitative Semiotic Analysis (Compagno)

- Discourse Analysis: Putting Our Worlds into Words (Strauss and Feiz)

- Discourse Analysis (Johnstone)

- Doing Anthropology in Consumer Research (Sunderland and Denny)

- Practical Ethnography (Ladner)

- Ethnographic Methods (O'Reilly)

- Grounded Theory (Garson)

- Case Study Research and Applications: Design and Methods (Yin)

- Case Study Analysis & QCA (Garson)

Multivariate Analysis

- Quantitative Applications in the Social Sciences Series (SAGE series)

- Intermediate Statistical Methods and Applications (Berenson et al.)

- Analysis of Variance, Design, and Regression (Christensen)

- Multiple Regression in Behavioral Research (Pedhazur)

- Statistical Methods For The Social Sciences (Agresti)

- Regression and Other Stories (Gelman et al.) 

- Generalized Linear Models and Extensions (Hardin and Hilbe)

- Generalized Linear Models With Examples in R (Dunn and Smyth)

- Generalized Linear Models & Generalized Estimating Equations (Garson)

- Linear and Generalized Linear Mixed Models (Jiang and Nguyen)

- Vector Generalized Linear and Additive Models (Yee)

- Flexible Regression and Smoothing (Stasinopoulos et al.)

- Generalized Additive Models: An Introduction with R (Wood)

- Quantile Regression (Koenker)

- Handbook of Quantile Regression (Koenker et al.)

- Regression Modeling Strategies (Harrell)

- Understanding Regression Assumptions (Berry)

- Regression Diagnostics (Fox)

- Applied Multivariate Statistical Analysis (Johnson and Wichern)

- Applied Multivariate Statistical Analysis (Härdle and Simar)

- Multivariate Analysis for the Behavioral Sciences (Vehkalahti and Everitt) 

- Computer Age Statistical Inference (Efron and Hastie)

- Multivariate Analysis of Variance (Bray and Maxwell)

- Multiple Comparison Procedures (Toothaker)

- Principal Component Analysis (Jolliffe)

- Principal Components Analysis (Dunteman)

- Foundations of Factor Analysis (Mulaik)

- Correspondence Analysis in Practice (Greenacre)

- Correspondence Analysis (Beh and Lombardo)

- Modern Multidimensional Scaling (Borg and Groenen)

- High-Dimensional Data Analysis with Low-Dimensional Models (Wright and Ma)

- The Easy Guide to Repertory Grids (Jankowicz)

- Cluster Analysis (Everitt et al.)

- Data Clustering (Aggarwal and Reddy)

- Handbook of Cluster Analysis (Hennig et al.)

- Applied Biclustering Methods (Kasim et al.)

- Finite Mixture and Markov Switching Models (Frühwirth-Schnatter)

- Handbook of Mixture Analysis (Frühwirth-Schnatter et al.)

- Model-based Clustering and Classification (Bouveyron et al.)

- Latent Class and Latent Transition Analysis (Collins and Lanza)

- Advances in Latent Class Analysis (Hancock et al.)

- Model-Based Clustering and Classification (Bouveyron et al.)

- Latent GOLD Manual (Vermunt and Magidson)

- Getting Started with Conjoint Analysis (Orme)

- Becoming an Expert in Conjoint Analysis (Orme and Chrzan)

- Discrete Choice Methods with Simulation (Train)

- Applied Choice Analysis (Hensher et al.)

- Best-Worst Scaling: Theory, Methods and Applications (Louviere et al.)

- Applied MaxDiff (Chrzan and Orme) 

- Sawtooth Software Conference Proceedings (Sawtooth Software)

- Discriminant Analysis (Klecka)

- Discriminant Analysis and Statistical Pattern Recognition (McLachlan)

- Applied Logistic Regression (Hosmer and Lemeshow)

- Logistic Regression Models (Hilbe)

- Analysis of Ordinal Categorical Data (Agresti)

- Applied Ordinal Logistic Regression (Liu)

- Ordered Regression Models (Fullerton and Xu)

- Modeling Count Data (Hilbe)

- Regression Analysis of Count Data (Cameron and Trivedi)

- Negative Binomial Regression (Hilbe) 

- Categorical Data Analysis (Agresti)

- Analyzing Categorical Data (Simonoff)

- Regression Models for Categorical Dependent Variables (Long and Freese)

- Biostatistics for Biomedical Research (Harrell and Slaughter)

- Primer of Biostatistics (Glantz)

- Statistical Remedies For Medical Researchers (Thall)

- Applied Survival Analysis Regression Modeling (Hosmer et al.)

- An Introduction to Survival Analysis Using Stata (Cleves et al.)

- Event History Analysis With Stata (Blossfeld et al.)

- Handbook of Survival Analysis (Klein et al.)

- Survival Analysis: A Self-Learning Text (Kleinbaum and Klein)

- Multistate Models for the Analysis of Life History Data (Cook and Lawless)

- Statistical Analysis of Epidemiologic Data (Selvin)

- Analysis Of Incidence Rates (Cummings)

- Modern Epidemiology (Lash et al.)

- Epidemiology: Study Design and Data Analysis (Woodward)

- Epidemiology by Design (Westreich)

- Mathematical Structures of Epidemic Systems (Capasso)

- Dynamical Modeling and Analysis of Epidemics (Ma and Li)

- Handbook of Infectious Disease Data Analysis (Held et al.)

- Fenner and White’s Medical Virology (Burrell et al.)

- Viruses: From Understanding to Investigation (Payne)

- Nonlinear System Identification (Nelles)

- Introduction to Functional Data Analysis (Kokoszka et al.)

- EEG Methods for the Psychological Sciences (Dickter and Kieffaber)

- The Statistical Analysis of Functional MRI Data (Lazar)

- Handbook of Neuroimaging Data Analysis (Ombao et al.)

- Eye Tracking Methodology (Duchowski)

Structural Equation Modeling and PLS

- Structural Equation Modeling: A Multidisciplinary Journal (Routledge)

- Mplus User's Guide (Muthén and Muthén)

- Covariance Structure Models (Long)

- Principles and Practice of Structural Equation Modeling (Kline)

- Linear Causal Modeling with Structural Equations (Mulaik)

- Structural Equations with Latent Variables (Bollen)

- Cause and Correlation in Biology (Shipley) 

- New Developments and Techniques in SEM (Marcoulides and Schumacker)

- Handbook of Structural Equation Modeling (Hoyle)

- Longitudinal Structural Equation Modeling (Newsom)

- Longitudinal Structural Equation Modeling (Little)

- Longitudinal Structural Equation Modeling with Mplus (Geiser)

- Growth Modeling (Grimm et al.)

- Higher-order Growth Curves and Mixture Modeling (Wickrama et al.)

- Structural Equation Modeling Applications Using Mplus (Wang and Wang)

- Structural Equation Modeling with AMOS (Byrne)

- Structural Equation Modeling with EQS (Byrne)

- EQS Structural Equations Program Manual (Bentler)

- A Primer on Partial Least Squares Structural Equation Modeling (Hair et al.)

- Partial Least Squares Regression and Structural Equation Models (Garson)

- Generalized Structured Component Analysis (Hwang and Takane)

- Meta-Analysis: A Structural Equation Modeling Approach (Cheung)

Multilevel and Longitudinal Modeling

- Data Analysis Using Regression and Multilevel/Hierarchical Models (Gelman)

- Richly Parameterized Linear Models (Hodges)

- Analysis of Longitudinal Data (Diggle et al.)

- Multilevel and Longitudinal Modeling (Rabe-Hesketh and Skrondal)

- Multilevel Analysis (Snijders and Bosker)

- Multilevel Analysis (Hox et al.)

- Multilevel Modeling (Garson)

- An Introduction to Multilevel Modeling Techniques (Heck and Thomas)

- Multilevel Modeling Using Mplus (Finch and Bolin)

- Cluster Randomised Trials (Hayes and Moulton)

- Longitudinal Analysis (Hoffman)

- Longitudinal Analysis (Garson)

- Applied Longitudinal Data Analysis for Epidemiology (Twisk)

- Intensive Longitudinal Methods (Bolger and Laurenceau)

- Econometric Analysis of Cross Section and Panel Data (Wooldridge)

- Panel Data Econometrics (Arellano)

- Econometric Analysis of Panel Data (Baltagi)

- Analysis of Panel Data (Hsiao)

- Longitudinal and Panel Data (Frees)

- Age-Period-Cohort Analysis (Yang and Land)

- A Practical Guide to Age-Period-Cohort Analysis (Fu)

- Generalized Method of Moments (Hall)

- Generalized Estimating Equations (Hardin and Hilbe)

- Quasi-Least Squares Regression (Shults and Hilbe)

- Applied Bayesian Hierarchical Methods (Congdon)

- Handbook of Spatial Statistics (Gelfand et al.)

- Hierarchical Modeling and Analysis for Spatial Data (Banerjee et al.)

- Statistical Methods in the Atmospheric Sciences (Wilks)

- A Primer for Spatial Econometrics (Arbia)

- Spatio-Temporal Methods in Environmental Epidemiology (Shaddick and Zidek)

- Handbook of Spatial Epidemiology (Lawson et al.)

- Statistical Detection and Surveillance of Geographic Clusters (Rogerson)

- Statistics for Spatio-Temporal Data (Cressie and Wikle)

Time Series Analysis and Marketing ROI

- Journal of Business & Economic Statistics (ASA)

- Journal of Time Series Analysis (Wiley)

- Journal of Forecasting (Wiley)

- Principles of Forecasting (Armstrong et al.)

- Forecasting (Hyndman and Athanasopoulos)

- Forecasting with Dynamic Regression Models (Pankratz)

- Time Series Analysis (Hamilton)

- Time Series Analysis (Box et al.)

- Time Series Analysis and Its Applications (Shumway and Stoffer)

- Time Series Analysis (Wei)

- An Introduction to Time Series Analysis and Forecasting (Yaffee and McGee) 

- A Course in Time Series Analysis (Rao)

- Time Series Analysis: Regression Techniques (Ostrom)

- Multiple Time Series Models (Brandt and Williams)

- Multiple Time-Series Analysis (Lütkepohl)

- Multivariate Time Series Analysis (Tsay)

- Multivariate Time Series Analysis and its Applications (Wei)

- The Cointegrated VAR Model Methodology and Applications (Juselius)

- Structural Vector Autoregressive Analysis (Kilian and Lütkepohl)

- Forecasting, Structural Time Series Models and the Kalman Filter (Harvey)

- Time Series Analysis by State Space Methods (Durbin and Koopman)

- Time Series Modelling with Unobserved Components (Pelagatti)

- Hidden Markov Models for Time Series (Zucchini)

- GARCH Models (Francq and Zakoïan)

- Handbook of Volatility Models and Their Applications (Bauwens et al.)

- Handbook of Modeling High-Frequency Data in Finance (Viens et al.)

- Introduction to Econometrics (Watson and Stock) 

- Introductory Econometrics (Wooldridge)

- Econometric Analysis (Greene)

- Basic Econometrics (Gujarati)

- Econometric Theory and Methods (Davidson and MacKinnon)

- Applied Econometric Time Series (Enders)

- A Practitioner's Guide to Stochastic Frontier Analysis (Kumbhakar et al.)

- Instrumental Variables & 2SLS Regression (Garson)

- Handbook of Discrete-Valued Time Series (Davis et al.)

- Nonlinear Time Series Analysis (Tsay and Chen)

- Nonparametric Econometrics (Li and Racine)

- Applied Nonparametric Econometrics (Henderson and Parmeter)

- The Oxford Handbook of Applied Nonparametric Econometrics (Racine et al.)

- Continuous Time Modeling (van Montfort et al.)

- The Illustrated Wavelet Transform Handbook (Addison)

- Univariate Tests for Time Series Models (Cromwell et al.)

- Multivariate Tests for Time Series Models (Cromwell et al.)

- Time Series Data Analysis Using EViews (Agung)

- Using EViews for Principles of Econometrics (Griffiths et al.)

- EViews Illustrated (Startz)

- EViews User's Guide (IHS Global Inc.)

- Microeconometrics Using Stata (Cameron and Trivedi)

- Introduction to Time Series Using Stata (Becketti)

- Financial Econometrics Using Stata (Boffelli and Urga)

- Economic and Financial Modelling with EViews (Aljandali and Tatahi)

- Structural Econometric Modelling Methodology and Tools (Brillet)

- Environmental Econometrics Using Stata (Baum and Hurn)

- Market-Share Analysis (Cooper and Nakanishi)

- Market Response Models (Hanssens et al.)

- Modeling Dynamic Relations (Pauwels)

- Market Response and Marketing Mix Models (Bowman and Gatignon)

- Digital Marketing Analytics (Hemann and Burbary)

- Marketing Calculator (Powell)

- Maths and Stats for Web Analytics and Conversion Optimization (Sharma)

- Google Analytics Demystified (Mokalis)

- It's Not The Size Of The Data - It's How You Use It (Pauwels)

- Marketing Analytics Data-Driven Techniques with Microsoft Excel (Winston)

- Practical Guide to Business Forecasting (Malehorn and Jain)

- Superforecasting: The Art and Science of Prediction (Tetlock and Gardner)

Computer Science

- Journal of Computational and Graphical Statistics (ASA)

- Journal of Artificial General Intelligence (AGIS)

- How Computers Work (White and Downs)

- Structure and Interpretation of Computer Programs (Abelson et al.)

- Concepts of Programming Languages (Sebesta)

- Algorithms (Sedgewick and Wayne)

- Algorithms for Decision Making (Kochenderfer et al.)

- C Programming (Perry and Miller)
- C Programming (Wikibooks)
- Teach Yourself C++ (Rao)
- A Smarter Way to Learn JavaScript (Myers)
- Java: A Beginner's Guide (Schildt)
- Perl by Example (Quigley)
- The Well-Grounded Rubyist (Black)
- VBA and Macros for Microsoft Excel (Jelen and Syrstad)

- Teach Yourself SQL (Forta)

- Learn SQL (Schulz)

- Tableau For Dummies (Monsey and Sochan)

- Matlab: A Practical Introduction (Attaway)
- Clojure for Data Science (Garner)

- Julia for Data Science (Voulgaris)

- Programming in Scala (Odersky et al.)

- Handbook of Computational Statistics (Gentle et al.)

- An Introduction to Stata Programming (Baum)

- The Mata Book: A Book for Serious Programmers (Gould)

- Blockchain Basics (Drescher)

- The Data Warehouse Toolkit (Kimball and Ross)
- Data Architecture: A Primer for the Data Scientist (Inmon and Linstedt)

- Building a Scalable Data Warehouse with Data Vault 2.0 (Linstedt)

- Big Data: Principles and best practices (Marz and Warren)
- Hadoop: The Definitive Guide (White)

- Data Mesh Delivering Data-Driven Value at Scale (Dehghani)
- Advanced Analytics with Spark (Ryza et al.)

- Big Data Analytics with Spark (Guller)

- Storm Applied: Strategies for real-time event processing (Allen et al.)

- Streaming Integration (Wilkes and Pareek)

- Designing Data-Intensive Applications (Kleppmann)

- Designing Machine Learning Systems (Huyen)

- Cloud Computing for Complete Beginners (Hawramani)

- Cloud Computing (Ruparelia)

- Cloud Computing (Bhowmik)

- Introduction to Parallel Computing (Trobec et al.)

- Building the Internet of Things (Kranz)

- Precision: Principles, Practices and Solutions for the Internet of Things (Chou)

- Agent-Based Models (Gilbert)
- An Introduction to Agent-Based Modeling (Wilensky and Rand)

- Introduction to Agent-Based Economics (Gallegati et al.)

- Introduction to Evolutionary Computing (Eiben and Smith)

- Reinforcement Learning: State-of-the-Art (Wiering and van Otterlo)

- Reinforcement Learning and Optimal Control (Bertsekas)

- Reinforcement Learning: An Introduction (Sutton and Barto)

- Decision Making Under Uncertainty (Kochenderfer et al.)

- Human Compatible: Artificial Intelligence and the Problem of Control (Russell) 

- How to Stay Smart in a Smart World (Gigerenzer)

- Artificial Intelligence (Russell and Norvig) 

Books on R

- The R Book (Crawley)
- R Cookbook (Teetor)
- The Art of R Programming (Matloff)
- Advanced R (Wickham)
- Using R for Numerical Analysis (Bloomfield)
- Matrix Algebra for Statistics with R (Fieller)
- Modern Optimization with R (Cortez)
- A User's Guide to Network Analysis in R (Luke)

- Statistical Analysis of Network Data with R (Kolaczyk and Csárdi)
- A Handbook of Statistical Analyses Using R (Hothorn and Everitt)

- An Introduction to Clustering with R (Giordani et al.)

- Applied Time Series Analysis with R (Woodward et al.)

- Spatio-Temporal Statistics with R (Wikle et al.)
- Computational Actuarial Science with R (Charpentier et al.)

- Applied Survival Analysis Using R (Moore)

- Using R for Introductory Econometrics (Heiss)

- Principles of Econometrics with R (Colonescu)

- Nonlinear Time Series Analysis with R (Huffaker et al.)

- R for Marketing Research and Analytics (Chapman and McDonnell Feit)

- Using the R Commander (Fox)

- Design and Analysis of Experiments with R (Lawson)

- A Practical Guide to Cluster Analysis in R (Kassambara) 

- Multiple Factor Analysis by Example Using R (Pagès)

- Text Mining in Practice with R (Kwartler)

- Supervised Machine Learning for Text Analysis in R (Hvitfeldt and Silge)

- Data Science in R (Nolan and Lang)

- R for Data Science (Wickham and Grolemund)

- Big Data Analytics with R (Walkowiak)

- 92 Applied Predictive Modeling Techniques in R (Lewis)

- Deep Learning with R (Chollet and Allaire)

- Probabilistic and Statistical Modeling in Computer Science (Matloff)

- Introduction to Scientific Programming and Simulation Using R (Jones et al.)

- Meta-Analysis with R (Schwarzer et al.)

- Applied Meta-Analysis with R and Stata (Chen and Peace)

- Bayesian Essentials with R (Marin and Robert)

- Elements of Copula Modeling with R (Hofert et al.)

- Financial Analytics with R (Bennett and Hugen)


Books on Python

- A Primer on Scientific Programming with Python (Langtangen)

- Python for Data Analysis (McKinney)

- Python Data Science Essentials (Boschetti and Massaron)

- Machine Learning in Python (Bowles)

- Hands-On Predictive Analytics with Python (Fuentes)

- Data Science for Marketing Analytics (Blanchard et al.)

- Bayesian Analysis with Python (Martin)

- Web Scraping with Python (Lawson)

Books on History and Culture

- Origins: The Scientific Story of Creation (Baggott)

- The Neanderthals Rediscovered (Papagianni and Morse)

- A Brief History of Everyone Who Ever Lived (Rutherford)

- Prehistory Decoded (Sweatman)

- The Neolithic of Europe (Bickle et al.)

- The Penguin History of the World (Roberts and Westad)

- Perceptions of the World in Pre-Modern Societies (Raaflaub and Talbert)

- The Mythology Book (Wilkinson et al.)

- An Anthology of Ancient Mesopotamian Texts (Franke)

- Money Changes Everything (Goetzmann)

- The Silk Roads: A New History of the World (Frankopan)

- India: A History (Keay)

- China: A History (Keay)

- Against the Grain (Scott)

- Mesopotamia: The Invention of the City (Leick)

- Sumerians: A History From Beginning to End (Freeman)

- Babylon: Mesopotamia and the Birth of Civilization (Kriwaczek)

- Forgotten Peoples of the Ancient World (Matyszak)

- Philosophy before the Greeks (Van De Mieroop)

- The Cambridge Companion to the Aegean Bronze Age (Shelmerdine)

- The Oxford Handbook of the Bronze Age Aegean (Cline)

- From Hittite to Homer (Bachvarova)

- Ancient Egypt: Everyday Life in the Land of the Nile (Brier and Hobbs)

- Phoenician Secrets: Exploring the Ancient Mediterranean (Holst)

- The Carthaginians (Hoyos)

- 1177 B.C.: The Year Civilization Collapsed (Cline)

- The Scythians: Nomad Warriors of the Steppe (Cunliffe)

- Daily Life of the Ancient Greeks (Garland)

- Thebes: The Forgotten City of Ancient Greece (Cartledge)

- Empire of the Black Sea: The Rise and Fall of the Mithridatic World (Roller)

- Popular Culture in Ancient Rome (Toner)

- Gladius: The World of the Roman Soldier (de la Bédoyère)

- Ancient Persia (Wiesehöfer)

- History of Africa (Shillington)

- The Ancient Celts (Cunliffe)

- The Maya (Coe and Houston)

- The Inca Empire (Jones)

- Everyday Life in the Aztec World (Berdan and Smith)

- The North American Indian (Curtis)  

- Byzantium: The Surprising Life of a Medieval Empire (Herrin)

- Osman's Dream: The History of the Ottoman Empire (Caroline Finkel)

- The Anglo-Saxons: A History of the Beginnings of England (Morris)

- Scotland: A History from Earliest Times (Moffat)

- A History of Ulster (Bardon)

- The Horde: How the Mongols Changed the World (Favereau)

- The Middle Ages: Everyday Life in Medieval Europe (Singman)

- Viking Age: Everyday Life During the Extraordinary Era of the Norsemen (Wolf)

- The Italian Renaissance: Culture and Society in Italy (Burke)

- Popular Culture in Early Modern Europe (Burke)

- The Complete Musashi (Musashi and Bennett)

- Russia: A Short History (Ascher)

- The Shakespeare Book (Wells)

- The World We Have Lost: England Before the Industrial Age (Laslett)

- The Birth of the Modern: World Society 1815-30 (Johnson)

- The Romantic Revolution (Blanning)

- The Art Book (Bugler et al.)

- History of Beauty (Eco)

- A Little History of Poetry (Carey)

- The Philosophy Book (Buckingham et al.)

- World Religions (Robinson and Rodrigues)

- Christian Socialism: The Promise of an Almost Forgotten Tradition (Turner)

- A Conflict of Visions (Sowell)

- The Meaning of Human Existence (Wilson)

Also see our Box archive 

Current Professional Memberships: American Statistical Association,

American Marketing Association

Past Professional Memberships: Institute of Business Forecasting, ESOMAR, AAPOR, Association for Institutional Research 

"I would rather have questions that can’t be answered than answers that can’t be questioned."

- Richard Feynman

"The best thing about being a statistician is that you get to play in everyone's backyard."

- John Tukey

"But what a weak barrier is truth when it stands in the way of an hypothesis!" 

- Mary Wollstonecraft

"The whole of science is nothing more than a refinement of everyday thinking." 

- Albert Einstein

"It's easy to lie with statistics.  But it is easier to lie without them."

- Frederick Mosteller

"Facts do not cease to exist because they are ignored."

- Aldous Huxley

"Knowing a great deal is not the same as being smart; intelligence is not information alone but also judgment, the manner in which information is collected and used."

- Carl Sagan

"Data analysis is an aid to thinking and not a replacement for it."

- Richard Shillington

"Details are not meaning; they are just a list of things that happened."

- Sam Ladner

"Essentially, all models are wrong, but some are useful."

- George E. P. Box

"An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem." 

- John Tukey

"A big computer, a complex algorithm and a long time does not equal science."

- Robert Gentleman

"Statistics is the grammar of science."

 - Karl Pearson

"I think it is much more interesting to live with uncertainty than to live with answers that might be wrong."

- Richard Feynman

"...the theory of probabilities is basically just common sense reduced to calculus..."

- Pierre-Simon Laplace 

"Probability is expectation founded upon partial knowledge."

- George Boole

"...probability theory is more fundamentally concerned with the structure of reasoning and causation than with numbers."  

- Glenn Shafer and Judea Pearl

"The perfect is the enemy of the good."

- Voltaire