# Statistics: The Story of Numbers

*Robert G. Franklin, Jr.*

*2017-09-25*

# Preface

This book has three purposes:

Purpose 1: Remove any fear of statistics

When I tell people I teach psychology, I get one of two responses. One response is “that’s interesting” and we talk about something fascinating about behavior or the mind. Another response is “I have a [insert relative] who you really need to talk to”, followed to some allusion to clinical psychology. Either way, they ask what I teach and I say, proudly, “Statistics”! (Yes, with the exclamation point).

It won’t surprise you that the response is usually disgust. Or fear. People are afraid of statistics and those who practice it. If it weren’t for lawyers, statisticians would be the most hated profession. There are quotes like “don’t you know 90% of statistics are made up.” (Really, it’s 79.2% of statistics that are made up, but who is counting).

People associate statistics with lies and so they’re afraid of statistics. It’s no coincidence the best known book about Statistics is called *How to Lie with Statistics*. The reason for this is that we don’t understand where the lies come from.

Statistics can be used in two ways. One way is to twist numbers to fit the facts that we want to believe. The other way is that statistics can tell us hidden truths about the world. Statistics tell stories to those who want to put the effort into finding out the answers. Once we know this, I think statistics becomes a lot more interesting.

Purpose 2: Teach you how to consume statistics

It’s important to note that there are a lot of bad statistics out there. One thing which might be even worse than statisticians twisting numbers to fit their own story is when people take good statistics and make bad conclusions with them.

If you are pursuing a psychology degree, you’re going to read a lot of psychology papers. Each of these papers will have statistics buried within them. Most of the students who review papers will skip most of these sections and just accept the conclusions the authors gave. But you, the student who completes this class, will have the power to do more than this. You will be able to go behind the curtain and find out what these numbers really mean.

And you will be able to go to these numbers and actually use them. For instance, a paper may tell you that there is a link between meditating and increasing meditating. You might want to decide, “should I start meditating”, especially if you’re the type of person who doesn’t like sitting still to meditate. The question will be: does meditating improve my happiness enough to make it worth the effort? With what we learn in this class, you can answer that.

Purpose 3: Teach you how to conduct statistics

This section has two parts. The first is the ability to graphically present data. Well after you have graduated and decided that you would rather make money in the real world rather than trying to make school your career, you may have to do a presentation where you show statistics using graphs.

You might be tempted to make the mistake of using bad charts, such as 3d bar graphs. But then you will remember this class and how awful those charts are. And you will make simple and elegant graphs which convey all the relevant information in a way that will make your colleagues proud and more importantly, your boss happy.

The second part is to actually conduct statistics. In a research methods class, or perhaps pursuing a masters or dissertation, or at some other point in your life, you may want to analyze data. This part will teach you how to do this, how to find out the true story of your data, and how to avoid the biases and mistakes which are lurking around to snatch the unsuspecting statistician. You will be able to find the truth.

How this book is structured

This book is more practical than math-heavy. It has many examples and will talk about what you should do, why you should do it, and how you should do it. It will try to explain which techniques you do and what situations you do them.

I will also teach this using the statistical language R. Computers make stats easy, but the computers are not very easy to use. Many of the software packages are very expensive, but R is free. That’s why I use it. It’s not the easiest thing to use, but once you use it, it becomes very powerful. In fact, R is so powerful, I’m using it to write this book! R can be used to do almost anything in statistics and data science, because it is open-source and thousands of wonderful people have written free extensions, called packages, which allow R to do thousands of things.