R Graphics

this would appeal to the applications oriented user. In a small class this can be used but I think additional material is required to explain concepts. One cannot expect a text that combines so much material to easily cover everything. There are few areas that were not emphasized that one might emphasize more in teaching. For example, there is too much emphasis on μ and not enough on ε. Analysis of assumptions is discussed in one section for simple linear regression but not for multiple regression or analysis of variance. I found some material to be well explained and the explanation of other material to be a bit brief. For example, the four types of residual plots are discussed, include one to assess independence. The explanation of the lack of independence is discussed (in one paragraph) without describing potential causes of dependence or giving examples of when it might occur. The lag plot code is given with little comment on what is actually done. I doubt that many students would understand what plot(tmp[-n], tmp[-n]) actually does without further comment. Additional description of the idea of a lag plot is in an earlier section of the text, but as part of a problem. Referring to the problem number would help as would additional details on what the code actually does. I think that texts which have a large number of programs should write them in a comment verbose fashion rather than a comment terse fashion. Introducing students to programming who have never programmed need as many reminders as possible to help understand the steps in the program. More comments would greatly improve the books purpose as an R aid.