Review of the book “Fact or Fake?”

With the knowledge one acquires in high school stochastics lessons, one can understand some of the additional sections of working with profit. Addresses issues of evaluating statistics: How are so-called “representative” surveys defined? How do you test hypotheses, what is a null hypothesis, what is the level of significance? What data can be made if confidence intervals are known? The authors explain the methods in detail and calculate some examples in detail.

They also discussed the usefulness of “significance tests,” which some experts object to. Müller and Quatember name errors that occur when such tests are used, such as the lack of a (research) hypothesis or the use of data collected in another way whose randomness is not guaranteed. They also complain that significant results are published almost exclusively. Because: “Even insignificant test results can be regarded as success on the path to knowledge and mainly serve to comprehensively include various research results.”

However, two sections of the book require more than average knowledge of mathematics. However, the problem dealt with can be well understood, and one can only marvel at the complex methods developed by statisticians. Who knew you could track down rigged election results with their help? And how likely is it to accumulate records, for example in terms of rainfall or temperatures?

In all chapters, the authors have largely dispensed with the formulas in the main text. Supplements in mathematical terms follow in the respective appendix. The book follows scholarly standards: each cited example is accompanied by a source, and each chapter concludes with bibliographic references. Overall, this is a very interesting and readable book. The wide range of topics with many examples certainly helps to enhance your ‘statistical literacy’ – even if you don’t understand all the mathematical ins and outs in detail.