Statistics 101: From Data Analysis and Predictive Modeling to Measuring Distribution and Determining Probability, Your Essential Guide to Statistics

Adams 101

by David Borman

A comprehensive guide to statistics—with information on collecting, measuring, analyzing, and presenting statistical data—continuing the popular 101 series.

Data is everywhere. In the age of the internet and social media, we’re responsible for consuming, evaluating, and analyzing data on a daily basis. From understanding the percentage probability that it will rain later today, to evaluating your risk of a health problem, or the fluctuations in the stock market, statistics impact our lives in a variety of ways, and are vital to a variety of careers and fields of practice.

Unfortunately, most statistics text books just make us want to take a snooze, but with Statistics 101 , you’ll learn the basics of statistics in a way that is both easy-to-understand and apply. From learning the theory of probability and different kinds of distribution concepts, to identifying data patterns and graphing and presenting precise findings, this essential guide can help turn statistical math from scary and complicated, to easy and fun.

Whether you are a student looking to supplement your learning, a worker hoping to better understand how statistics works for your job, or a lifelong learner looking to improve your grasp of the world, Statistics 101 has you covered.

Genres: Nonfiction, Mathematics, Science, Economics, Business, Reference

240 pages, Hardcover

First published December 1, 2018

Reviews

[Daniel Whelan · Rating 2 out of 5]

A very shallow introduction to statistics and sloppily edited at that. Lots of errors in the mathematical calculation examples. Spend your time reading a better text.

[Ashok Krishna · Rating 3 out of 5]

This book is filled with informative nuggets, but they are few and far between. A little incoherent. Dull. Tad boring too. Have read better books on this daunting topic.

[Daniel Siegel · Rating 1 out of 5]

Many errors in this, how did it get published? An early example is the definition of the set of numbers [25, 28, 30, 32, 37], the declaration that the middle number is "28", and then a few (incorrect) calculations.

DNF! Don't read this!

[Lia (areaderswords) · Rating 2 out of 5]

There are errors in the book.

[Naomi · Rating 3 out of 5]

no comment

[Dmytro · Rating 1 out of 5]

There are a lot of errors in the book. Some examples are very confusing and don't make sense.

[Hussain Abbas · Rating 2 out of 5]

The idea of this book was very promising: a quick primer on Statistics that would help me take a small step towards understanding data science. I got tired of it eventually.

I am either missing large parts of mathematical understanding or the book has been carelessly written and edited. In many sections, I faced a complete disconnect between two paragraphs and I couldn’t resolve that even on multiple re-reads. And then there were errors in numbers (typos, but repeated often) that would completely throw me off in understanding the data the author is trying to describe. I doubted myself in the beginning but I saw that this was a repeated pattern in the book.

I eventually gave it up and will look out for another book on this topic.

[Jake Ignatowicz · Rating 2 out of 5]

Going into this I didn’t know a thing about statistics. Coming out I feel I know more than I did. That is a big positive for not just this book, but this series as a whole. I always feel that I learn something. However, I found myself zoning out in some parts, some parts were so complicated and not thoroughly enough covered, and other parts were almost unreadable. I give this book 2 stars, I’m glad I read it, but I don’t need to again.

[Hallie · Rating 1 out of 5]

Would not recommend. I'd started this looking for a refresher for someone who is already versed in the basics of statistics, and even then I found this book not entirely helpful - basic concept descriptions and real-life application scenarios are there, but the description of charts and the unnecessary plugging of specific software/application suites was disappointing.

[Alex Brooks · Rating 2 out of 5]

This offered a good understanding of the necessary basics in stats. I do research in the humanities and had to learn how to do stats. I gained a good enough understanding to help me before I started making decisions on my project. That said, I do have a few qualms with the book.

1) many of the scenarios or examples weren't the best choice to increase understanding of the subject (ex. using the example about car racing when many readers likely don't know anything about the subject and should not have to in order to comprehend the case scenario, this is for beginners afterall), 2) there are some places where visuals would have been more helpful than descriptive imagery (ex. the chapter on different types of graphs, I ended up having to Google examples to understand), 3) some areas where specific terms are explained were so convoluted, I had to google them and all it would have taken is 3 simple sentences of an explanation to understand properly, and 4) the author clearly highlights the importance of objective statistics or research, then makes subjective statements but phrases them as though it is objective (ex. he states that gambling is irrational and while I don't disagree this is not an appropriate way to make the statement as it's foundation is opinionated rather than fact based, a more appropriate statement would have been to state that the likelihood or probability of winning the lottery was low so the risk does not outweigh the means or something along those line).

Then again, i am also in the line of egotistical and nit-picky academics so it's possible I am thinking too hard about it.

[Joe · Rating 1 out of 5]

I’m normally a pretty generous reviewer. I’ve never given a one star review. Unfortunately I have to do that here. There are so many errors in this book, it’s likely to mislead you.

Don’t waste your time or money with this book. I abandoned the book after the chapter on mean deviation and variance. At best the wording is very clumsy, but in many places it’s just plain wrong.

The book title and table of contents seemed to be very promising. I got the book as a refresher on statistics and probability. Here’s an example of how poorly the book is written:

“In essence, variance is the sum of the square of the value of the data points and the mean of the data points, divided by the number of data points.”

That’s incorrect. The key concept missing is “minus the mean”” and not “and the mean”. It should be worded something like:

“In essence, variance measures the average of the squared differences between each data point and the mean.”

Because I bought this book as a stats review and it’s so full of errors, I had to stop reading it. That’s a shame because it seemed to be promising at first. I really wanted to use this book as a learning tool.

Like other reviewers have pointed out, there’s so many errors I’m not sure how this book got published. I wished I’d checked the reviews first. Perhaps the author could get some help revising the book to fix the errors? If so, I’d give it another chance. In the meantime, skip this one. I’ll be looking for something else to help with my statistics review.

[William Schram · Rating 4 out of 5]

Statistics 101: a Crash Course in Statistics is a book by David Borman. Like the other books in the series, it covers the key ideas of Statistics or the subject that is being covered. It contains equations galore and tons of definitions of terms. In that sense, it works as an introduction to the field of Statistics or as a way to refresh your memory.

The book covers the past of Statistics with its humble beginnings and speculates on its future. It is agreed that Statistics really took off when computers became both small enough and cheap enough to belong to a household rather than a large University or a giant Corporation. This is probably because statistics requires a massive amount of data to carry out. We’re talking millions of data points in some cases.

As the blurb on the book says, it is quite accessible and easy to understand. It doesn’t have any problems to solve, but it does have a number of examples to follow. I really enjoyed this one, as I did with the other books that I have read in this series. They are really easy to digest and take in.

[Reynaldo Ted II (Trewaldo) Peñas · Rating 3 out of 5]

For its conciseness and simplicity in the choice of terms to bring down the level of statistics learning to the beginner, this is good book to start with. The relatable examples are also simple enough to be understood by a non-mathematically inclined person willing to learn the subject.
But the non-mathematical approach in some of the key theories that make up what we now know as data science and analytics, it's not a good book to help you understand such concepts. To understand statistics is to bear through the intimidating theories and formulas that help define how it is very useful in our modern-day data-driven lives.

[Ramesh Naidu · Rating 4 out of 5]

• Chicago Public Library: www.chipublib.org/
• New York Public Library: www.nypl.org/
• The British Library: www.bl.uk/
• US Library of Congress: https://loc.gov/
• World Bank open database: https://data.worldbank.org/
• International Monetary Fund database portal: www.imf.org/en/
Data•Bank for International Settlements statistics portal: www.bis.org/ statistics/
• World central banks guide website listing: www.centralbanksguide
.com/central+banks+list/
• US Census Bureau database: www.census.gov/

[Vy Lê · Rating 2 out of 5]

I wouldn't recommend this book to anyone due to its shallow content and negligent details. To author & editors, if you see example on page 34, it is not correct in result. Some page even has spell issue that annoy readers much.
The only plus point of this book in my view is the overview process of designing survey and working with data after that.

[Daniel Hendrason · Rating 1 out of 5]

This is not a 101 on statistics. This is like a note of basic statistics for people who actually know statistics and want to refresh their memory. So it shouldn't be a 101. For me personally, the book lacks one whole research example that will summarize all the book's explanation on how to apply statistics.

[Zach Stewart · Rating 2 out of 5]

I read this book as a quick refresher for an interview. I already knew all concepts, just needed to knock the cobwebs off my stats. This book has good real life examples, but is full of miscalculations and/or typos. I don’t know if this would be a great book for someone learning the concepts for the first time.

[Tri Nguyen · Rating 3 out of 5]

It was an ok read from my view point. Although I have to say that it's a bit dry, it wasn't good enough as a teaching material unfortunately. I do like the cover, so that's probably why I chose it to begin with.

[Nikki · Rating 2 out of 5]

I read this as a refresher to prepare for teaching high school stats, and all it really did was remind me of the names of concepts that I once learned and definitely need to review more in-depth. This book is only helpful if you already know the basics of statistics.

[Adrian Pedroza · Rating 4 out of 5]

concise book with a pretty good overview of the field of statistics. pretty surface level but that’s the point. it gives a good foundation for tying together what can be taught in the classroom. the book helped strengthen my conceptual understanding of various topics.

[Mike Moses · Rating 1 out of 5]

So not read this book. It is poorly edited and contains substantive errors that lead to confusion.

[Ew Lake · Rating 4 out of 5]

Very practical book, written in a language a non-mathematician or scientist can understand. Will be a well-used reference book on my shelf.

[Sweemeng Ng · Rating 3 out of 5]

A bit shallow and not exactly enough for intro. But I would pass this to people before they decide to become a data scientists or take on a data project

[Edwin · Rating 2 out of 5]

Good start information.

Good information to begin to understand something about statistics, but it has zero explanation on how to use the math to understand the subject.

[Issacks · Rating 4 out of 5]

Less charts

I think more charts to demonstrates some terms and concepts, tables and so on. It's good if you want general information about the topic.

[Ravi Naidu · Rating 1 out of 5]

The books seems to be published in rush, it says look at the graphs and there are no graphs and the concepts are written / explained in a rush