"Molecular Driving Forces: Statistical Thermodynamics in Chemistry and Biology" is a moderately good book. It really depends on your purposes and expectations whether you should choose this book or not.

This book covers an impressive amount of material on statistical thermodynamics in both chemistry and biochemistry areas. The material that Ken and Sarina try to present in this book is a little overwhelming for a one semester course. They have gone over most of the classical concepts that need to develop the statistical mechanics understanding vary from easy to difficult level. On the top of that, they apply the statistical thermodynamics onto biological systems such as proteins and nucleic acids, which is tremendously helpful for people who are interested in studying the physical properties of biological systems. However, the book is too spread out since it tries to combine two large areas into one. I would think if they split one good book into two better books, one is focusing on the statistical thermodynamics concepts and theories itself and one is focusing on the applications particularly in biological systems, they can discuss both subjects at a more thoroughly detailed level. Another thing that bother me just as much is the book completely ignores the quantum mechanics and quantum statistics, not even mention them in introductions or reviews sections. The idea of quantum statistics might be frightening to me as well as many students, but in order for students to have a better appreciation, a better understanding of a bigger picture, I suppose they should dedicate a chapter to discuss about quantum mechanics and quantum statistic. The last thing that I dislike about this book is the problems set at the end of each chapter. The problems are ranging from easy "plug in numbers and get answers" problems to extreme difficult derivations problems. I didn't find many intermediate levels problems. A lots of the problems are just testing whether one can interpret a plot or figures. Some of the questions are almost helpless in trying to inspire you develop your critical thinking skills.

On the bright side, I have found the book of Ken and Sarina to be a very good book for self-study. It has some very well done reviews on mathematical tools that help you develop mathematical skill in studying statistical mechanics. Chapter 1 is called "principles of probability", which goes over the fundamental of probability concepts and thus lead to the foundation of entropy. Chapter 4 is another math review on series and approximations. Follow by chapter 5, which is a review on multivariate calculus. Chapter 17 is a vector calculus reviews and Gauss's theorem. These chapters makes the books qualify to be a very suitable self-study book. I am very grateful for these so called reviews; a lots of them were new to the students. The chapter about Boltzmann Distribution Law (chapter 10) was done very nicely. The detailed, well put and very organized explanations and derivations about Boltzmann Distribution Law and Partition Function was impressively presented. This chapter is one of  many of the chapters in this book where statistical thermodynamics concepts are explained and derived slowly and clearly and easily to understand. Overall, I like the book. It is a moderately good book like I said in the beginning. It has the potential to be a great book. I was just slightly upset because there was so much material was mentioned in the book and that make it hard for learners to keep up; it was a little crowded and overwhelming.