- Hot Topic
While the rating tells you how good a book is according to our two core criteria, it says nothing about its particular defining features. Therefore, we use a set of 20 qualities to characterize each book by its strengths:
Applicable – You’ll get advice that can be directly applied in the workplace or in everyday situations.
Analytical – You’ll understand the inner workings of the subject matter.
Background – You’ll get contextual knowledge as a frame for informed action or analysis.
Bold – You’ll find arguments that may break with predominant views.
Comprehensive – You’ll find every aspect of the subject matter covered.
Concrete Examples – You’ll get practical advice illustrated with examples of real-world applications or anecdotes.
Controversial – You’ll be confronted with strongly debated opinions.
Eloquent – You’ll enjoy a masterfully written or presented text.
Engaging – You’ll read or watch this all the way through the end.
Eye opening – You’ll be offered highly surprising insights.
For beginners – You’ll find this to be a good primer if you’re a learner with little or no prior experience/knowledge.
For experts – You’ll get the higher-level knowledge/instructions you need as an expert.
Hot Topic – You’ll find yourself in the middle of a highly debated issue.
Innovative – You can expect some truly fresh ideas and insights on brand-new products or trends.
Insider’s take – You’ll have the privilege of learning from someone who knows her or his topic inside-out.
Inspiring – You’ll want to put into practice what you’ve read immediately.
Overview – You’ll get a broad treatment of the subject matter, mentioning all its major aspects.
Scientific – You’ll get facts and figures grounded in scientific research.
Visionary – You’ll get a glimpse of the future and what it might mean for you.
Well structured – You’ll find this to be particularly well organized to support its reception or application.
Researchers commonly refer to the differences between sets of data – measures from different treatment groups, for example – as being (or not being) “statistically significant.” The sets are considered significantly different only if an arbitrary statistical threshold is exceeded. If it isn’t, people often conclude that there is no difference between the sets of data. This assumption, however, is not necessarily valid. A sub-threshold finding may still be relevant. And, as Carl Sagan put it, absence of evidence is not evidence of absence. A group of over 800 scientists is now calling to “retire statistical significance.” The article will engage and inform anyone concerned that statistical analyses can be misleading but were never quite sure exactly how or why.
About the Authors
Valentin Amrhein is a professor of zoology at the University of Basel, Switzerland. Sander Greenland is a professor of epidemiology and statistics at the University of California, Los Angeles. Blake McShane is a statistical methodologist and professor of marketing at Northwestern University in Evanston, Illinois.