Reviews for Human rights and legal history

The average rating for Human rights and legal history based on 4 reviews is 2.5 stars.

Review # 1 was written on 2014-01-27 00:00:00 Jimmy Barton Good, but perhaps too simple? I can see why some people don't like this book, although it's one of the clearest mathematical textbook I have ever seen in my limited experience. Because it's too clear and easy to understand, it may seem even trivial especially to those who like mathematics for its complexity and sophistication (whether real or not). It is a pretty well-known psychological phenomenon, however: you tend to perceive something to be of high quality if you have a harder time understanding it (one experiment I have in mind is how people's rating of restaurant food changed depending on how hard it was to read the menu). This might in part explain some people's raving reviews of abstruse modernist works of literature (like Joyce's Ulysses or Pynchon's Rainbow's Gravity, both of which I slugged through with guidebooks). Anyway, though the exercises were a little too easy, this textbook is definitely a GREAT way to start studying statistics, as it requires only the knowledge of some high school algebra and explains everything so well that you really don't need to spend hours trying to decipher what's going on in a proof or an equation. Will be reading Freedman's more advanced textbook, Statistical Models next, supplemented maybe with some standard college textbook on mathematical statistics, like Wasserman's All of Statistics.

Review # 2 was written on 2014-01-27 00:00:00 Robin Foster Good, but perhaps too simple? I can see why some people don't like this book, although it's one of the clearest mathematical textbook I have ever seen in my limited experience. Because it's too clear and easy to understand, it may seem even trivial especially to those who like mathematics for its complexity and sophistication (whether real or not). It is a pretty well-known psychological phenomenon, however: you tend to perceive something to be of high quality if you have a harder time understanding it (one experiment I have in mind is how people's rating of restaurant food changed depending on how hard it was to read the menu). This might in part explain some people's raving reviews of abstruse modernist works of literature (like Joyce's Ulysses or Pynchon's Rainbow's Gravity, both of which I slugged through with guidebooks). Anyway, though the exercises were a little too easy, this textbook is definitely a GREAT way to start studying statistics, as it requires only the knowledge of some high school algebra and explains everything so well that you really don't need to spend hours trying to decipher what's going on in a proof or an equation. Will be reading Freedman's more advanced textbook, Statistical Models next, supplemented maybe with some standard college textbook on mathematical statistics, like Wasserman's All of Statistics.

Review # 3 was written on 2012-11-04 00:00:00 John Diemer Decent textbook on statistics. The book itself is aimed at both a general public and undergraduates, meaning that the content is not too sophisticated. I read this to freshen up my rusty statistical knowledge (to prepare for some tests), so in this sense the book has served its purpose. The authors write in an accessibly style and use lots of simple examples to lay down the foundations of the most important statistical theories and tools. Descriptive statistics, inferences, frequency theory of chance, using models, and tests of signicifance like the chi square test (for testing frequencies) and t-tests (both between-group and within-group analysis). It would have been nice to read some more about the historical context of these ideas and their development over time. Also, it would have been nice to read some more about the philosophical problems surrounding statistics as tool for reliable knowledge. The authors mention that in modern science, especially the alfa sciences, statistics is over-used and in many cases merely used as weighty language to proffer up results. I can attest to this last point - any analysis based on models is simply based on the assumptions of the model itself. Trash in = trash out. Modern sciences like psychology like to present their results as significant, but they're really only presenting their own assumptions in weighty language. (It is common knowledge that replicability, for example, is a huge issue in psychology and that sociological research is heavily influenced by political-ideological assumptions). Would have been nice to read some famous case studies... Anyway, the book is decent - I can't really recommend it besides digging up old knowledge. To learn statistics one needs some more guidance, preferably within a course setting.

Review # 4 was written on 2012-11-04 00:00:00 Eric Hatzenbehler Decent textbook on statistics. The book itself is aimed at both a general public and undergraduates, meaning that the content is not too sophisticated. I read this to freshen up my rusty statistical knowledge (to prepare for some tests), so in this sense the book has served its purpose. The authors write in an accessibly style and use lots of simple examples to lay down the foundations of the most important statistical theories and tools. Descriptive statistics, inferences, frequency theory of chance, using models, and tests of signicifance like the chi square test (for testing frequencies) and t-tests (both between-group and within-group analysis). It would have been nice to read some more about the historical context of these ideas and their development over time. Also, it would have been nice to read some more about the philosophical problems surrounding statistics as tool for reliable knowledge. The authors mention that in modern science, especially the alfa sciences, statistics is over-used and in many cases merely used as weighty language to proffer up results. I can attest to this last point - any analysis based on models is simply based on the assumptions of the model itself. Trash in = trash out. Modern sciences like psychology like to present their results as significant, but they're really only presenting their own assumptions in weighty language. (It is common knowledge that replicability, for example, is a huge issue in psychology and that sociological research is heavily influenced by political-ideological assumptions). Would have been nice to read some famous case studies... Anyway, the book is decent - I can't really recommend it besides digging up old knowledge. To learn statistics one needs some more guidance, preferably within a course setting.