Statistical inference is a process of drawing general conclusions from data in a specific sample. Typical inferential problems are: Does alternative A give higher return than alternative B? Is drug A more effective than drug B? In both cases solutions are based on observations in a single sample.
To solve inferential problems one has to deal with the problems: (i) How to find the best estimate of an unknown quantity, (ii) How to find an interval that covers the true unknown value and (iii) How to test hypothesis about the value of an unknown quantity. The treatment of these issues can be found in a large amount of statistical textbooks. The present book differs from the latter since it focuses on problem solving and only a minimum of the theory needed is presented.