- Statistics Without Tears – A Primer for Non-Mathematicians
- by Derek Rowntree
- Charles Scribner’s Sons
- Copyright 1981
- 190 pages
Rating (for pages 1-62) – 7 out of 10
As a rule, I’m not much of a re-reader. The lure of the new, the unexplored always seems to draw me when it comes time to choose a book.
But there are exceptions. About ten years ago, I found a copy of Derek Rowntree’s Statistics Without Tears at Goodwill. With little to lose, I bought the copy and read it. Sometimes you get lucky. I thought that Tears was an amazing book.
Though I got my doctorate with a minor in statistics, I always found stats to be intimidating – so much to learn and so many “squigglies,” those Greek letters that never made made much sense to me. But Rowntree has a gift; by explaining the concepts behind stats and not dwelling on the calculations, he makes the reader understand.
My copy of Statistics Without Tears is long gone. (It’s probably back at Goodwill, waiting for its next home). But, when I was at the University library last week, I checked out their copy. I began to read it again Thursday.
Chapter 1 (pp. 13-26)
Rowntree’s opening is strong. He discusses the fact that we make statistical inferences all of the time, without recognizing that we are doing so. He states that the two main concerns of statistics are 1) summarizing experience, and 2) making predictions based on those summaries. He also does a terrific job of explaining how a sample should mirror the population from which it is drawn (on page 24).
Chapter 2 (pp. 28-37)
Unfortunately, Chapter 2 gets deeper in the weeds. Rowntree discusses the differences in continuous and discrete variables. Also, he differentiates between counting phenomena and measuring phenomena. I think that Rowntree does a good job with this material, but the material is complex and not easy to understand.
Chapter 3 (pp. 38-56)
Chapter 3 discusses measures of central tendency and measures of dispersion. For me, some of this material was a little too basic; I didn’t feel that I learned that much. However, Rowntree’s explanations are often much clearer than have been any I that read before. He discusses the meaning of standard deviation in a way that is intuitive and even gets into some esoteric measures such as the inter-quartile range (and why it matters).
Chapter 4 (pp. 57-62)
Thursday I managed just a few pages in Chapter 4 before I flaked out. Rowntree begins with promise, discussing skewed distributions and their implications for the statistician.
After the first sixty-plus pages, I am enjoying re-reading Statistics Without Tears. Readers seeking an easy-to-understand introduction to statistics will enjoy Rowntree’s clear prose.
However, the book is not quite as good as I had remembered it being. Perhaps I haven’t gone far enough yet. One thing that I can remember from the first reading is that Rowntree has an amazing discussion on the normal curve.
I look forward to reading the next few chapters.