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Reviews for Applied statistics

 Applied statistics magazine reviews

The average rating for Applied statistics based on 4 reviews is 3 stars.has a rating of 3 stars

Review # 1 was written on 2017-06-11 00:00:00
0was given a rating of 3 stars Rich Sucik
A brief, effective tour of applied statistics. The first part covers general principles for successful data analysis, while the second part consists of three- or four-page discussions of real (or nearly-real) datasets. (These discussions aren't worked examples so much as sketches of the authors' recommended analyses for the various datasets.) I really liked the authors' emphases on descriptive statistics and on sensitivity, and I think they show pretty convincingly that every dataset has its quirks, and requires its own mindset and its own unique analysis. The book feels dated (which it is!) - there's very little discussion of computationally-intensive analytic techniques - but I learned a lot from the authors' careful, first-principles approach. I wouldn't have understood this book when I first started learning about statistics, but I think I could have benefited from it once I'd worked a handful of applied problems, and I think statisticians much more experienced than I am (that's most of them) would enjoy this book and derive some insights from it.
Review # 2 was written on 2014-10-28 00:00:00
0was given a rating of 3 stars Jeromy Hutchinson
speechless
Review # 3 was written on 2017-06-11 00:00:00
0was given a rating of 3 stars Debra Brunk
A brief, effective tour of applied statistics. The first part covers general principles for successful data analysis, while the second part consists of three- or four-page discussions of real (or nearly-real) datasets. (These discussions aren't worked examples so much as sketches of the authors' recommended analyses for the various datasets.) I really liked the authors' emphases on descriptive statistics and on sensitivity, and I think they show pretty convincingly that every dataset has its quirks, and requires its own mindset and its own unique analysis. The book feels dated (which it is!) - there's very little discussion of computationally-intensive analytic techniques - but I learned a lot from the authors' careful, first-principles approach. I wouldn't have understood this book when I first started learning about statistics, but I think I could have benefited from it once I'd worked a handful of applied problems, and I think statisticians much more experienced than I am (that's most of them) would enjoy this book and derive some insights from it.
Review # 4 was written on 2014-10-28 00:00:00
0was given a rating of 3 stars Ador Galendez
speechless


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