Required for my stats class.

Rental in good shape. Easy rent and return procedure. Subject matter sucked! Lol! For webassign course, all quizzes, tests, and home works came from book practice questions. Values often changed. Only some answers in the book.

The book goes out of it's way to be horribly confusing.

It's high on fluff, and low on substance. Tries to teach via a plethora of examples, but ultimately comes off as clumsy and crowded. The book forgets that you need to properly cement the mechanics of the subject before dancing around with unnecessary analogies.

Get it if you need to for a class, but if you want to learn statistics, I highly advise you look for a secondary source.

It's easy to read and Dr.P outlines each of her chapters and gives plenty of clear and consise examples to help anyone learn statistics! If anyone is looking to take this class on their own or is taking the class anywhere else besides pitt, her website provides other resources to go with the book.

This Cengage Higher Education volume is a good, contemporary reference that highlights daily themes and concepts prevalent in gathering statistical data. The pages are colorful and provide thought-provoking questions that challenge the mathematical specialist's ability to distinguish what constitutes reliable information apart from that which is relegated to biased sampling. The breakdown from one broad topic to its several distinctive subcategories with its highly detailed examples and definitions reveals that the author is very knowledgeable and analytical. For instance, we go from statistics as a whole to its various subdivisions, such as nominal statistics, inferential statistics, and ordinal statistics. Each classification is meticulously described in a way that can keep the reader engaged.

However, what is perhaps the book's greatest strength is, ironically, also its weakness. As described in the aforementioned statements, Elementary Statistics: Looking at the Big Picture is arguably a page turner for the novice who wants to gain insight regarding how his/her daily life is affected by, say, standard deviations, measures of central tendency, and the notorious albeit ubiquitous bell curves. Nonetheless, those, like myself, who want to see the concise summaries of these mathematical realities, or the perceptions thereof, in the form of equations are often finding themselves thumbing through the chapters with many difficulties finding algorithms that they could expound on. To me, the presentation of the formula followed by laid out examples at the introductory level, first, followed by the intermediate, second, have been tried and true though not always foolproof.

In spite of this observation, I find the publication to be well-written. As an educator, I find it a refreshing break from the boring, rote materials that are laden with bullet points and can only admire the narrative approach that Nancy Pfenning continually utilizes throughout.

All in all, Cengage Learning, I believe, wants to deliver the highest quality educational tools for both instructors and students, and this work of Pfenning is, no doubt, an asset in carrying out this overall mission.