The introductory statistics course presents serious pedagogical problems
to the instructor. For the great majority of students, the course
represents the only formal contact with statistical thinking that he or
she will have in college. Students come from many different fields of
study, and a large number suffer from math anxiety. Thus, an instructor
who is willing to settle for some limited objectives will have a much
better chance of success than an instructor who aims for a broad
exposure to statistics. Many statisticians agree that the primary
objective of the introductory statistics course is to introduce students
to variability and uncertainty and how to cope with them when drawing
inferences from observed data. Addi- tionally, the introductory COurse
should enable students to handle a limited number of useful statistical
techniques. The present text, which is the successor to the author's
Introduction to Statistics: A Nonparametric Approach (Houghton Mifflin
Company, Boston, 1976), tries to meet these objectives by introducing
the student to the ba- sic ideas of estimation and hypothesis testing
early in the course after a rather brief introduction to data
organization and some simple ideas about probability. Estimation and
hypothesis testing are discussed in terms of the two-sample problem,
which is both conceptually simpler and more realistic than the
one-sample problem that customarily serves as the basis for the
discussion of statistical inference.