I took geometry in 9th grade, in a class that only did Euclidean proofs. This book covers alot of measuring, and gets into the very basics of analyticI took geometry in 9th grade, in a class that only did Euclidean proofs. This book covers alot of measuring, and gets into the very basics of analytic geometry and trigonometry. Those were both full classes that I had in high school. So I'm wondering what makes this for college students? Anyway, the presentation was clear.

In the Meno, Plato argues that knowledge is a form of memory, and he uses math to illustrate the point. I was reminded of the Meno here because everything in this book was calling up distant memories. The funny thing is that at one point, I had to fill out my address on a form, and I caught myself giving my childhood street address. So, returning to this stuff has had a different kind of effect on the memory, subconsciously transporting me back to my youth....more

Mostly really simple stuff, with the addition of brief introductions to linear algebra, probability and series, and conics. The approach was easy to fMostly really simple stuff, with the addition of brief introductions to linear algebra, probability and series, and conics. The approach was easy to follow, but at the expense of not including proofs for almost anything that has any complexity to it. It's hard for me to believe that this is really college level stuff....more

Even for a textbook I thought this was bad. I haven't ever taken statistics before, and almost everything I know is stuff I've picked up either from sEven for a textbook I thought this was bad. I haven't ever taken statistics before, and almost everything I know is stuff I've picked up either from studying trading, or from trying to figure out the meaning of scientific studies. I had hoped that a textbook would clear up some of the things I've always found confusing. No such luck.

I would have liked the book to explain the formulas, give some insight into how they were developed, and discuss why they were needed. Instead, the book typically presents a fairly complicated formula, without anything in the way of prior explanation. Sometimes it will present the formula before it even defines the terms that the formula contains, a practice that makes me want to shove needles into my eyes.

Then, the book will go straight into examples of how to use the formula. Most of the time, this means a few pages of examples where the only engagement by the reader is going to a table and looking up a number from rows and columns. Sometimes you go to Table 6 in Appendix B. Other times you go to Table 8. And that's about the depth of the insight you get. I really did not need to have extensive instruction in how to look something up in a stupid table. And frankly, the table look-up is pretty pointless nowadays, because anyone with access to a computer and the internet can probably do better than the tables here.

Then there are the ideas that I always found mystifying when reading statistics, like "degrees of freedom." There are many formulas presented here that contain an entry where you apply the appropriate degrees of freedom. But nowhere is there even a word about what a degree of freedom is, why it might be needed in a formula, or anything else to give a person an inkling of what is really going on with any formula involving a degree of freedom. (In my frustration I did some looking on google to get some idea. It involves n-dimensional vector spaces and constraints along some dimensions within that space. This is a pretty advanced mathematical idea, and I understand why the book doesn't go into any detail. But it wouldn't be too hard to at least mention the idea. It wouldn't be that hard even to explain what happens if you take an object in 3 dimensional space and limit it to motion on a flat plane. What you have done is removed one of the "degrees of freedom" of that object. There! Was that really so hard that it wouldn't even deserve a mention.

Then, even with ideas that are pretty simple, the book offers no explanation for how it gets to the formulas a person is to apply. For example, late in the book we get the Sign Test for a population median. Here's how the book presents it without any other explanation. Someone claims that X is the median for some population. Take a sample and assign + signs when the sample datum is greater than X and a - sign when its less than X. Count the number of + and - signs. If the sample size is 25 or less, then choose the lower count. If greater than 25, then calculate (x+.5) - .5n/(square root n/2). Then do a table lookup depending on the level of significance important to you, but you go to different tables depending on whether the sample size is less than or greater than 25 (without explaining why). Then you compare your sample calculation with the number from the table. The examples then walk you through the procedures of the algorithm. Even on its own, this method depends almost entirely on rote, and doesn't give any understanding about what's going on.

But in the case above, its even worse because it would be very simple to explain what's going on with the sign test. First, remind people of what a median is. It's the number in the population where half the population lies above the number and half lies below it. This means that if you take a random sample of one from the population, there's a 50/50 chance of him falling above or below the median. For any random sample, it's a coin toss. Thus, the derivation of the formula should be really simple. Thus, this problem can be reduced to a simple probability problem involving throwing a coin. If the results deviate too much from 50/50, that suggests that the stated median is probably incorrect. This book doesn't even attempt this, or any other, sort of explanation.

If anyone knows of a good book on probability and statistics, I would welcome the suggestion. This ain't it....more

Very nice and very clear for the most part. This is pretty much the opposite of the dreadful statistics textbook I recently read. Here, you have to doVery nice and very clear for the most part. This is pretty much the opposite of the dreadful statistics textbook I recently read. Here, you have to do quite a bit of the work for yourself. This means that Clark will fairly often present a theorem and then immediately leave the proof as an exercise. This procedure basically requires an understanding of the material -- otherwise, within a few pages the reader will become hopelessly lost. Thus, while the book is very short, it's way more dense than the other math texts I've recently read. All in all, I prefer this approach, but its definitely not for the lazy reader.

As far as I know, this book is available only as a download from the author's website. He has made it available for free, and its easily worth the price. ...more

This was much better than the last book on statistics I read. At least it would either prove something, or state that the math involved was beyond theThis was much better than the last book on statistics I read. At least it would either prove something, or state that the math involved was beyond the scope of the book and leave a proposition unproven. It also talked some about the limitations of the ideas and approximations that were being used. It even made an attempt to explain "degrees of freedom."

I like this all the way through the basic hypothesis testing chapters. I liked the approach taken here to non-parametric testing. But that's about the point where things started to get fuzzy. And it was bit fuzzier with Chi squared distributions. And by the time we got to F Distributions, it happened again: I felt like bees were living in my head.

What I take away from this is that I pretty much dislike statistics. It all seems like a huge house of cards to me: alot of very elegant math built on what may or may not be some pretty shady assumptions. That said, I did take away some very useful ideas that might have some application to testing trading systems....more