My new book, Stats with Kittens, Growing up with data, charts, surveys, correlations, and other floofy playthings, is now available on Amazon.

Everybody needs to understand statistics. It’s an essential part of everyday life in America, more so than any other type of higher math. Statistics isn’t just mathematics, it’s inductive reasoning with numbers. It’s a fundamental component of modern literacy.

Stats with Kittens is aimed at readers who want to understand statistics well enough to avoid misleading data analyses and the media articles about them. It describes the many ways in which they can be misleading and shows how to identify those issues so you become an informed consumer of statistics. It explains why many students have to take an introductory course in statistics to get their degree or professional certification.

Stats with Kittens has an average Flesch-Kincaid Grade Level of 11.5 (11th grade), which is considered suitable for 16 year olds and above. Its readability ranges from 9.6 (Chapter 2 on Probability) to 12.6 (Chapter 8 on Data Models). In its 524 pages, Stats with Kittens has 75 technical figures, 41 tables, and over 500 pictures of kittens. The kittens are provided to ease math anxiety and make your reading experience tolerable if not enjoyable. The book uses metaphors and analogies, real-life examples, and step-by-step approaches to explain how to understand presentations about statistical analyses. It also has a Glossary of over a thousand definitions to facilitate comprehension.

Stats with Kittens explains how you can deal with the jargon you’ll hear in presentations involving statistics. Some of the jargon involves repurposed words, that is, English words with alternative meanings. These may be difficult to identify because you have to consider the context in which the words appear. The easiest to spot are eponyms (terms named after a person) and special words (unique words used exclusively in statistics). These are less common, at least until you get to more advanced levels of statistics.

Stats with Kittens discusses a variety of fundamental questions individuals new to statistics may have. Examples include:

• How is statistics used to analyze data?
  There are five approaches—describing, classifying, testing, predicting, and explaining (Chapter 1).
• Where do probabilities come from?
  Probabilities come from four sources—logic, data, models, and oracles (Chapter 2).
• How are data measured?
  Data measurement involves three elements—benchmark, process, and judgment (Chapter 3).
• How is data variability controlled in statistics?
  Variance control involves the three Rs—Reference, Replication, and Randomization (Chapter 3).
• What is important to look for in statistical graphics?
  Statistical graphics are defined by the three Fs—Foundation, Framework, and Facade (Chapter 4).
• Why do people often incorrectly criticize polls?
  Six reasons people criticize polls are too few participants, they didn’t ask me, only landline users were interviewed, they asked the wrong questions, the results were predetermined, and the results were wrong (Chapter 5).
• Are there different kinds of data relationships?
  There are at least nine types of data relationships: direct, feedback, common-cause, mediated, stimulated, suppressed, inverse, threshold, and complex (Chapter 7).
• What is important to look for in data relationships?
  Look for trends (temporal, spatial, categorical, hidden, and multivariate), patterns (shocks, steps, shifts, cycles, and clusters), and anomalies (censoring, unequal variances, and outliers) (Chapter 7).

It also provides steps for how to approach a variety of challenges in understanding data, including: what to look for in statistical surveys; how to decide if correlation implies causation; how to evaluate statistical presentations; and how to become a critical thinker.

Stats with Kittens consists of nine chapters that describe what you’ll need to know to be an informed consumer of statistics. Included are traditional topics like probability, descriptive statistics, graphing, hypothesis testing, and regression, as well as topics taught less often, such as the history of statistics, causality, critical thinking, evidence, fallacies, and bad science. The Chapters are:

• Chapter 1. Introduction. Why you should learn about statistics and what you should know before starting.
• Chapter 2. Probability. What probability and odds are, where they come from, and how they influence our lives.
• Chapter 3. Description. How describing datasets is easier than describing people once you know what to look for.
• Chapter 4. Graphs. What you need to know about statistical graphics to assess their validity. It’s much more than you were taught in HS.
• Chapter 5. Surveys. How to measure intangible, changing opinions. Everybody thinks surveys are easy to conduct but they are, in fact, the most difficult type of statistical analysis to get right.
• Chapter 6. Comparisons. How to find significant and meaningful differences between populations represented by data. Statistical testing has been used for centuries but tests are complicated and easy to get wrong.
• Chapter 7. Relationships. How data metrics can be related and why it’s hard to tell when correlation implies causation.
• Chapter 8. Models. How statistical models of a data relationship are created and how to spot common faults that others may overlook.
• Chapter 9. Literacy. How to recognize possible issues in data and statistical analyses to assess the validity of information and arguments presented in technical reports and media stories.

Stats with Kittens is not a textbook, but it is still a valuable resource for students, professionals, and everyone in between. It provides help for comprehending the data-driven analytics you might encounter in sports, social media, the news, and most anything you follow in life. It is an asset for those looking to expand their knowledge of the world.

Read a sample of Stats with Kittens and get your own copy at https://www.amazon.com/Stats-Kittens-Growing-correlations-playthings/dp/B0FSCFF9YD