Reviews for Mind on statistics

The average rating for Mind on statistics based on 4 reviews is 2 stars.

Review # 1 was written on 2021-02-06 00:00:00 C Huhn 1/10. It was boring. The print was too small for convenient reading. I thought it was a good example of how not to write a book. At one point in my notes, I wrote "worst book ever."

Review # 2 was written on 2013-06-30 00:00:00 Eric Castellani Dense, but also very basic. Not all of it was known stuff, but a lot of it was and the coverage was highly superficial - though this could not possibly be avoided given the page count. The number of topics covered is high due to the format, which seems quite problematic in the specific context; it seems quite likely that people reading a book like this will end up thinking they know a lot more statistics than they actually do, and so become overconfident when evaluating research or conducting data analyses of their own. Some questionable assumptions and approaches are occasionally seen in the book in specific contexts, but I'm not sure I consider this to be a major problem as the question of how to optimize the level of precision is likely quite difficult when writing books like this one, which is presumably in part aimed at people with limited knowledge of quantitative methods. A big problem is that the scope of the book is too wide, in my opinion; if a book finds that it is necessary to tell people how to calculate the mean value of a sample, that same book should not be telling you stuff about things like proportional hazard models. The guy who needs to read the first part will get only an illusory knowledge of the latter, and the guy who's only interested in the latter will do a lot better by just reading a specific text dealing with the sub-topic of interest, instead of limiting himself to the 3 pages the book might devote to the relevant topic. I think the 'at a glance' concept is questionable when dealing with topics such as those covered in this book; either that or the authors failed in their application. It's not a terrible book, but it's also not very good. I liked Fletcher and Fletcher, which sort of deals with similar stuff even though there are also some substantial differences in terms of topics covered, better.

Review # 3 was written on 2021-02-06 00:00:00 Elizabeth Boyle 1/10. It was boring. The print was too small for convenient reading. I thought it was a good example of how not to write a book. At one point in my notes, I wrote "worst book ever."

Review # 4 was written on 2013-06-30 00:00:00 Nicholas Serrano Dense, but also very basic. Not all of it was known stuff, but a lot of it was and the coverage was highly superficial - though this could not possibly be avoided given the page count. The number of topics covered is high due to the format, which seems quite problematic in the specific context; it seems quite likely that people reading a book like this will end up thinking they know a lot more statistics than they actually do, and so become overconfident when evaluating research or conducting data analyses of their own. Some questionable assumptions and approaches are occasionally seen in the book in specific contexts, but I'm not sure I consider this to be a major problem as the question of how to optimize the level of precision is likely quite difficult when writing books like this one, which is presumably in part aimed at people with limited knowledge of quantitative methods. A big problem is that the scope of the book is too wide, in my opinion; if a book finds that it is necessary to tell people how to calculate the mean value of a sample, that same book should not be telling you stuff about things like proportional hazard models. The guy who needs to read the first part will get only an illusory knowledge of the latter, and the guy who's only interested in the latter will do a lot better by just reading a specific text dealing with the sub-topic of interest, instead of limiting himself to the 3 pages the book might devote to the relevant topic. I think the 'at a glance' concept is questionable when dealing with topics such as those covered in this book; either that or the authors failed in their application. It's not a terrible book, but it's also not very good. I liked Fletcher and Fletcher, which sort of deals with similar stuff even though there are also some substantial differences in terms of topics covered, better.