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Feb 17

## Review of Bock, Velleman, De Veaux

### Who is this book for

Once I asked my students to apply regression. They had to choose whatever problem they liked, find the data on the Internet, run the software and interpret the result. So, one student finds data with an unusual layout. Usually, data labels run across the top, while along columns you have observations. In his case, data labels are at the top and on the left. He arbitrarily selects the columns of data, runs the regression, comes to me and asks: Could you tell me what my variables are? He may have read this book which on p.15 says what a data table is: An arrangement of data in which each row represents a case and each column represents a variable.

There is a category of students I call open-minded. Their brains are unencumbered by prejudices. Their minds are open to whatever they are taught, provided that it is fun. To their tastes, a book is good if it can be productively read while lying on the couch. Most importantly, they prefer verbal explanations to equations. A real-life application of every piece of theory is a must.

If you are this type, go ahead and read this book. The authors did their best to get to you. If, after reading the book, you think "Statistics is an impressive science", you will be right, except that you will know little about it. Or, perhaps, you will know a lot, depending on the definition of intuition and how much of it you absorb. If you are more mathematically oriented, you can even find occasional food for thought, like the derivation of the standard error for a predicted mean value on p.668. By the way, that's where the authors say that the Central Limit Theorem tells us that the standard deviation of $\bar{y}$ is $\frac{\sigma}{\sqrt{n}}$. No, the CLT is a little bit more complex than that, and I'm sure the authors are aware of that; they just want you to understand and be happy.

### Conclusion

Most of praises and criticism I said about Agresti and Franklin apply to this book too, including the one about photos that have nothing to do with the subject matter. However, this book seems to me a little more rigorous, although the same level. You have more choice in terms of using statistical software. Appendix B (Guide to Statistical Software) contains directions about using Data Desk, Excel, JMP, MINITAB, SPSS, TI-89 and TI-NSPIRE.

### Word of caution

The exposition is highly informal. For example, normal distributions (called normal models in the book) are never formally defined. All you learn about them is manipulations with the z-score and visualization of the distribution shape. If you move to a higher level, you will be surprised by the fact that you need to study everything anew. For those who are serious about their studies, I want to share my opinion about the progression through introductory to intermediate and advanced courses. The introductory level is a game for kids. Since they don't know much about science, they usually believe that it is the true science. The intermediate level is not much better, as I came to know when I studied Economics at Oregon State University. At the advanced level of a curriculum is where students become experts in the field.

To me, the introductory and intermediate levels are artificial barriers on the way to professionalism, invented in order to extract more money from students. When I was giving intermediate Econometrics in the US, the deputy head of the department expressly asked me to be lenient with bachelor students because they provided funds for master's and PhD programs. Since most university courses are intermediate at best, a university graduate is usually not considered a specialist and is forced to take a master's or PhD program. From a societal point of view, this is a huge waste of time and money.