Please send suggestions/additions to Nancy Campbell,
`ncampbell@jcvaxa.jcu.edu`

- Textbooks for Introductory Statistics
- Textbooks for the Probability / Mathematical Statistics Sequence
- Textbooks for Introductory Biostatistics

- Moore,
*The Basic Practice of Statistics*Comments:

- By Bret Larget: I think that this textbook should be easy to read for students and contains excellent problems that ask for statistical reasoning and interpretation. It does a good job of stressing concepts instead of procedures and computation. My only complaint is that the subject matter for many of the homework problems and examples is not as intrinsically interesting for students as other recent textbooks I have seen. A rather substantial percentage of my students did not feel that explanations of concepts in the textbook were clear. My guess is that they would have felt this way about any statistics textbook, but I'm curious to hear what others who've used this textbook have found.

- Rice,
*Mathematical Statistics and Data Analysis*Comments:

- By Bret Larget: This textbook does a very good job in connecting probability to the modeling of real-world applications, gets to statistics and data analysis relatively quickly, and presents an accurate view of modern statistics practice by incorporating techniques such as the bootstrap and simulation. There is a lack of simple problems for beginning to students to master basic concepts. Students learning statistics for the first time from this textbook will struggle, since introductory ideas are not as clear as might be hoped. Weaker students will have difficulty in reading the textbook.

- Daniels,
*Biostatistics: A Foundation for Analysis In the Health Sciences*Comments:

- By Bret Larget: I use this textbook for a course taken mainly by lower-division students majoring in the health sciences (athletic training, occupational therapy, physician's assistant, physical therapy). Since these programs are very competitive, most students in this course are very good in comparison to typical students in our other introductory statistics service course. Strengths of the book include explicit statements of model assumptions and problems that contain good set-up information and real data. Weaknesses are that the book seems to be written mainly as a step-by-step guide for applying various procedures, with emphasis on how to make computations. Essentially all problems follow the format: describe medical situation, give data, ask for computation or result of statistical procedure. There is a great lack of questions that ask students to reason or interpret. If you wish to use computers, someone needs to enter in the data. With few exceptions, students find the textbook difficult to read. (We have multiple sections of this course and other instructors feel more positively about the text.)

- Samuels,
*Statistics for the Life Sciences*(publ. by Dellen)Comments:

- By Jeff Witmer: I use this textbook for a one-semester
introduction to statistics for biology and neuroscience majors.
The book contains lots of real data and presents a nice treatment
of the standard topics for introductory statistics, with a couple
of non-parametric procedures thrown in; the mix of homework
problems is adequate. Samuels spent a lot of time as a practicing
statistician before she wrote her book and it shows in her writing.
For example, although she presents confidence intervals
for a single mean, she does not present hypothesis testing until getting
to the two-sample setting, presumably because in real life
statisticians rarely test a single mean, but often compare two
means with a hypothesis test. There is a chapter on design (which I
wish were longer) and discussion throughout the book of basic
principles and assumptions. Most of my students are reasonably happy
with the book.

Last modified: June 3, 1996 - By Jeff Witmer: I use this textbook for a one-semester
introduction to statistics for biology and neuroscience majors.
The book contains lots of real data and presents a nice treatment
of the standard topics for introductory statistics, with a couple
of non-parametric procedures thrown in; the mix of homework
problems is adequate. Samuels spent a lot of time as a practicing
statistician before she wrote her book and it shows in her writing.
For example, although she presents confidence intervals
for a single mean, she does not present hypothesis testing until getting
to the two-sample setting, presumably because in real life
statisticians rarely test a single mean, but often compare two
means with a hypothesis test. There is a chapter on design (which I
wish were longer) and discussion throughout the book of basic
principles and assumptions. Most of my students are reasonably happy
with the book.