This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings.  Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design.  Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.

Part I

Basic Probability Theory
Experimental Design and the Basics of Statistics: Signal detection Theory (SDT)
The Core Concept of Statistics
Variations on the t-test
PART II
The Multiple Testing Problem
ANOVA
Experimental design: Model Fits, Power, and Complex Designs
Correlation
PART III
Meta-analysis
Understanding replication
Magnitude of excess success
Suggested improvements and challenges