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Hypothesis Testing: A Visual Introduction To Statistical Significance
Hypothesis Testing & Statistical Significance
If you are looking for a short beginners guide packed with visual examples, this booklet is for you.
Statistical significance is a way of determining if an outcome occurred by random chance, or did something cause that outcome to be different than the expected baseline. Statistical significance calculations find their way into scientific and engineering tests of all kinds, from medical tests with control group and a testing group, to the analysis of how strong a newly made batch of parts is. Those same calculations are also used in investment decisions.
This book goes through all the major types of statistical significance calculations, and works through an example using them, and explains when you would use that specific type instead of one of the others. Just as importantly, this book is loaded with visual examples of what exactly statistical significance is, and the book doesn't assume that you have prior in depth knowledge of statistics or that you regularly use an advanced statistics software package. If you know what an average is and can use Excel, this book will build the rest of the knowledge, and do so in an intuitive way. For instance did you know that
Statistical Significance Can Be Easily Understood By Rolling A Few Dice?In fact, you probably already know this key concept in statistical significance, although you might not have made the connection. The concept is this. Roll a single die. Is any number more likely to come up than another ? No, they are all equally likely. Now roll 2 dice and take their sum. Suddenly the number 7 is the most likely sum (which is why casinos win on it in craps). The probability of the outcome of any single die didn't change, but the probability of the outcome of the average of all the dice rolled became more predictable. If you keep increasing the number of dice rolled, the outcome of the average gets more and more predictable. This is the exact same effect that is at the heart of all the statistical significance equations (and is explained in more detail in the book)
You Are Looking At Revision 2 Of This BookThe book that you are looking at on Amazon right now is the second revision of the book. Earlier I said that you might have missed the intuitive connections to statistical significance that you already knew. Well that is because I missed them in the first release of this book. The first release included examples for the major types of statistical significance
A Z-TestA 1 Sample T-TestA Paired T TestA 2 Sample T-Test with equal varianceA 2 Sample T-test with unequal varianceDescriptions of how to use a T-table and a Z-tableAnd those examples were good for what they were, but were frankly not significantly different than you could find in many statistics textbooks or on Wikipedia. However this revision builds on those examples, draws connections between them, and most importantly explains concepts such as the normal curve or statistical significance in a way that will stick with you even if you don't remember the exact equation.
If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you.
If you are looking for a short beginners guide packed with visual examples, this booklet is for you.
Statistical significance is a way of determining if an outcome occurred by random chance, or did something cause that outcome to be different than the expected baseline. Statistical significance calculations find their way into scientific and engineering tests of all kinds, from medical tests with control group and a testing group, to the analysis of how strong a newly made batch of parts is. Those same calculations are also used in investment decisions.
This book goes through all the major types of statistical significance calculations, and works through an example using them, and explains when you would use that specific type instead of one of the others. Just as importantly, this book is loaded with visual examples of what exactly statistical significance is, and the book doesn't assume that you have prior in depth knowledge of statistics or that you regularly use an advanced statistics software package. If you know what an average is and can use Excel, this book will build the rest of the knowledge, and do so in an intuitive way. For instance did you know that
Statistical Significance Can Be Easily Understood By Rolling A Few Dice?In fact, you probably already know this key concept in statistical significance, although you might not have made the connection. The concept is this. Roll a single die. Is any number more likely to come up than another ? No, they are all equally likely. Now roll 2 dice and take their sum. Suddenly the number 7 is the most likely sum (which is why casinos win on it in craps). The probability of the outcome of any single die didn't change, but the probability of the outcome of the average of all the dice rolled became more predictable. If you keep increasing the number of dice rolled, the outcome of the average gets more and more predictable. This is the exact same effect that is at the heart of all the statistical significance equations (and is explained in more detail in the book)
You Are Looking At Revision 2 Of This BookThe book that you are looking at on Amazon right now is the second revision of the book. Earlier I said that you might have missed the intuitive connections to statistical significance that you already knew. Well that is because I missed them in the first release of this book. The first release included examples for the major types of statistical significance
A Z-TestA 1 Sample T-TestA Paired T TestA 2 Sample T-Test with equal varianceA 2 Sample T-test with unequal varianceDescriptions of how to use a T-table and a Z-tableAnd those examples were good for what they were, but were frankly not significantly different than you could find in many statistics textbooks or on Wikipedia. However this revision builds on those examples, draws connections between them, and most importantly explains concepts such as the normal curve or statistical significance in a way that will stick with you even if you don't remember the exact equation.
If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you.
108 pages, Kindle Edition
Published December 20, 2015
378 people are currently reading
129 people want to read
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Displaying 1 - 11 of 11 reviews
October 24, 2022
Easy insightful read
Well structured in terms of steps for hypothesis testing process and explanation of the formulas by breaking them down.
Gives equivalent Excel formulas and covers the low level details which might be missed by more advanced books.
Visual examples help understanding the concepts better.
It gives the stuff that you will need to know just before you run the tests.
The examples give better understanding of the concepts.
Well structured in terms of steps for hypothesis testing process and explanation of the formulas by breaking them down.
Gives equivalent Excel formulas and covers the low level details which might be missed by more advanced books.
Visual examples help understanding the concepts better.
It gives the stuff that you will need to know just before you run the tests.
The examples give better understanding of the concepts.
July 7, 2017
A Great Refresher for long ago Statistics students...
But I bought the book to help my college-bound daughter prepare for stats. I also bought Scott's book on probability and will begin that shortly.
But I bought the book to help my college-bound daughter prepare for stats. I also bought Scott's book on probability and will begin that shortly.
December 30, 2017
Excellent book to quickly understand the Hypothesis testing with examples. Better start with the knowledge of central limit theorem and confidence interval. It also covers the MS excel functions for hypothesis testing, which really helps.
August 26, 2018
A fast overview
This a nice review with enough detail to be a good for a novice as a starting point or a gentle reminder for those of us who have been dabbling in biostats/publishing for some years. I bought it to help refresh my excel pivot table skills.
Nice job.
This a nice review with enough detail to be a good for a novice as a starting point or a gentle reminder for those of us who have been dabbling in biostats/publishing for some years. I bought it to help refresh my excel pivot table skills.
Nice job.
March 8, 2023
Great book on statistical hypothesis testing
This is a great book to understand the principles of hypothesis testing.
Easy to follow examples bring the theory down to earth.
Great work!
This is a great book to understand the principles of hypothesis testing.
Easy to follow examples bring the theory down to earth.
Great work!
March 26, 2018
Good book
Good book
Hyphothesis has been learnt in a good way will refer to friends and others and will keep helping
Good book
Hyphothesis has been learnt in a good way will refer to friends and others and will keep helping
June 10, 2019
A good one.
Good book about hypothesis testing but it requires some previous knowledge. If so, go for it. This is a good book for intermediate students.
Good book about hypothesis testing but it requires some previous knowledge. If so, go for it. This is a good book for intermediate students.
August 10, 2022
Very clear examples
Very clear examples that shows you how hypothesis testing works. I recommend this book for everyone that is starting to learn statistics
Very clear examples that shows you how hypothesis testing works. I recommend this book for everyone that is starting to learn statistics
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May 9, 2024very basic
this is more a collection of a few examples than anything else. it is a quick read and a good refresher, though.
this is more a collection of a few examples than anything else. it is a quick read and a good refresher, though.
August 6, 2018
Excellent introduction and review
I purchased to have a quick review of hypothesis testing. I found the book to be perfect for this use.
I purchased to have a quick review of hypothesis testing. I found the book to be perfect for this use.
February 14, 2023
Well worth the price
This is a nicely explained, concise description of the uses of z- and t-tests for hypothesis testing.by the end, the reader should be able to both properly set up Excel functions for these tests and also reach solutions manually.
This is a nicely explained, concise description of the uses of z- and t-tests for hypothesis testing.by the end, the reader should be able to both properly set up Excel functions for these tests and also reach solutions manually.
Displaying 1 - 11 of 11 reviews