Our Books

Fairly Nerdy Books

I’ve written several books on engineering, computer science, and data analysis. The goal of this page is to help you find any that match what you are interested in and would like to learn.   So this page gives an overview of the books I’ve written and shows you where you can get them (usually on Amazon).   Typically the books are priced between 99 cents and \$3 (U.S.), depending mostly on the length.

If you are looking at some of these books, are interested in them, but don’t want to purchase them, then send me an email at

I would be happy to send you a PDF copy of one or more of the books if you would leave an honest, unbiased review of them on their Amazon pages after you read them.

Thanks for browsing!

~Scott

Books On Statistics, Probability, & General Math

• Linear Regression and Correlation Regression is a way of turning a bunch of data into a single equation.  Correlation is a way of showing how related two different sets of numbers are to each other.  This book demonstrates how to calculate both, including how to do regression analysis when you have multiple different independent variables.
• Bayes Theorem Examples  Bayes theorem describes the probability of an event based on other information that might be relevant. Essentially, you are estimating a probability, but then updating that estimate based on other things that you know. This book is designed to give you an intuitive understanding of how to use Bayes Theorem. It starts with the definition of what Bayes Theorem is, but the focus of the book is on providing examples that you can follow and duplicate. Most of the examples are calculated in Excel, which is useful for updating probability if you have dozens or hundreds of data points to roll in.
• Hypothesis Testing Examples   This book gives worked examples for the main different types of hypothesis testing.   It shows you how to either solve the hypothesis tests by hand, including all the equations and tables that you need,  or how you can quickly solve the hypothesis in Excel.           The examples make it easy to know when you should be using a Z-Test, or when you should be using the different types of T-Tests, and the Excel functions make it a matter of a few seconds to confirm or reject your hypothesis.
• Probability With Permutations and Combinations      This book gives examples of how to understand using permutations and combinations, which are a central part of many probability problems.   The focus of this book is on understanding why the permutation and combination equations are what they are, which ends up making them a lot easier to understand, remember, and expand than simply memorizing the equations.
• Probability With The Binomial Theorem and Pascal’s Triangle  The binomial theorem is a way of calculating the probability of certain outcome after a number of discrete events.  For instance you would use it to calculate the odds of getting 7 or more heads in 10 flips of a coin, or calculate the odds of a team that has a 45% chance of winning any given game to win at least 4 in a 7 game series.  The binomial distribution shows up in a lot of different places, so this is some fundamental knowledge.

Books On Programming & Machine Learning

• Machine Learning With Random Forests And Decision Trees:  Random Forests are one type of machine learning algorithm. They are typically used to categorize something based on other data that you have. The purpose of this book is to help you understand how Random Forests work, as well as the different options that you have when using them to analyze a problem. Additionally, since Decision Trees are a fundamental part of Random Forests, this book explains how they work.      This book is focused on understanding Random Forests at the conceptual level. Knowing how they work, why they work the way that they do, and what options are available to improve results. This book covers how Random Forests work in an intuitive way, and also explains the equations behind many of the functions

• Machine Learning With Boosting: The book above shows how Random Forests take a large number of decision trees run in parallel and average them together to get a comprehensive analysis that avoids many of the drawbacks to decision trees.  This book shows how decision trees can be run one after the other so that each one is correcting the error that was left behind by previous iterations.  Gradient Boosted Trees, as it is called, has become one of the most winning algorithms on data competition sites such as Kaggle, so it is something worth knowing about.

Excel Books

This next section of books goes over some key things to know to use Excel effectively for data analysis.   I have used Excel at my job daily for over a decade, and during that time have asked people “how did you do that” whenever I saw them use an interesting function that I didn’t understand.   These books all focus on walking you through a specific function is useful for data analysis, and the different tips and tricks associated with it.

All of these Excel books are focused on a single topic, and leave out any extraneous information

• Excel Pivot Tables –    This book goes over how to get started with Pivot tables in Excel, and many of the most important options that pivot tables have. This book is focused on the most important features of Pivot Tables, but it doesn’t deep dive into the details of every single different thing that can be done with them. This book goes over how to create pivot tables, different ways that they can be set up in rows, columns or tables, how to show the values in the pivot tables as counts, summations, products, percentages or other useful values, how to filter and sort pivot tables, how to format them and a few other tips and tricks.
• Excel Conditional Formatting –   Conditional formatting is very useful for many different functions. You can use it to spot trends in data, make outliers visible, or make intuitive tables. Conditional formatting allows you do to all the formats that you would want to do if you could manually go through and examine all your data, but that you typically don’t have time for. This book walks you through how to set up different types of conditional formatting in Excel, including applying it to a full table of numbers, or just targeting specific cells.
• Excel Data Filters – Data filters are one of the things that I use most frequently in Excel. They are almost as powerful as Pivot Tables, but are much more intuitive and easier to use.  This book will walk through how to set them up, how to use them to sort data, and how to filter data. Finally the book will give some of the tricks to be aware of when using data filters, such as how to copy data into or out of filtered columns, or how to quickly tell if a filter has been applied.
• Excel Importing & Exporting Text Data–  This book shows how to import and export different types of data from Excel.  Most Excel users will be familiar with using CVS format, or using the Text to columns feature to import data, but this book goes over some tricks that even advanced Excel users may not have seen, such as how to copy data out of a PDF cleanly, or copy text from an image.
• Excel Random Numbers – Random numbers have a lot of useful and fun properties. Not the least of which is that if you run into a problem that is too hard for a closed form solution, simulating it with random numbers is almost always easier.    Excel has a fairly easy to use pseudo-random number generator. Coupled with Excel’s other good functions, it is very useful for generating a moderate quantity of random numbers for small to medium simulations. This book walks you through how to generate random numbers in Excel, and some variations you can use them for such as sorting, or making a normal distribution.
• FreeExcel Tips & Settings – This book will show you the best tips and settings that I have found in years of using Excel and asking people “How did you do that”.  It shows how to make formulas easier to use, hotkeys to speed up excel, and tips to fix the annoyances Excel has.  Available on Fairly Nerdy.com – For Free

Other Books

• Graduate College Early!   I got a bachelors degree in Aerospace Engineering in 3 years, and my Masters degree in the 4th years.  Yet I noticed that many of my classmates who I entered college with as a Freshman ended up going back for year 5 or even 6 just to get their undergraduate degree.  This book is intended to help students graduate college in 3 years or less. Instead of taking the average of 5 years to graduate college and spending 10’s of thousands of dollars on tuition and room and board every year, it is easy for students to accumulate tons of credits from AP exams, CLEP exams, and other methods that will cut semesters from the time they have to spend in college. Instead of over \$400 per credit, plus room and board at the average in state college, it can cost as little as \$25 to get that exact same credit from the AP exam.