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Already, reading and applying findings in relevant disciplines,
as well as in library and information science, can yield a store of researchable
ideas that is large and complex enough to fill (if not exceed) any present
capacity in the field.
In the following chapters of this book we hope to give
a basic understanding of statistics, statistical analysis, and its usefulness
in library science. In attempting this, we have kept the mathematical prerequisites
at a minimal level. Our goal is not to turn our readers into accomplished
statisticians, which we could not do in a few chapters. Our goal is to
acquaint readers with the most common statistical techniques and terminology
encountered in any basic research area. After reading this text and attempting
the problems at the end of each chapter, one should have a fundamental
grasp of some of the basic elements of statistical analysis. For those
who would like to explore statistical and methodological topics beyond
the scope of this text, we have included references at the end of each
chapter.
Our discussion begins in chapter 1 with an introduction
to descriptive statistics that are geared toward quantifying characteristics
of a group of individuals or cases on a number of variables of interest
to us. In order to quantify these characteristics, we must learn something
about the measurement process which, essentially, assigns numbers to individuals
according to the qualities or amount of the variable they possess. This
presentation is also included in the first chapter.
Chapter 1 also contains the methods for calculating certain
summary statistics. Through them, we are able to summarize great amounts
of information by means of a few statistics or numbers. Sometimes, however,
we are not interested in only the small number of individuals or cases
to which we have immediate access. Rather, we would like to make generalizations
about a larger number of individuals (i.e., all library users), based on
our small subgroup of library users on whom we have data. To make this
inference valid, we must become acquainted with some of the ways to acquire
such a subgroup or sample in order~ to make sounder generalizations.
Chapter 2 deals with samples and sampling procedures.
Based on our newly acquired knowledge, we turn to inferential statistics
in chapter 3 and cover some of the fundamental concepts on which inductive
statistics are based. It is at this point that we will begin using statistical
methods for making generalizations and testing our statistical hypothesis
in a logical inductive manner.
In chapter 4 we expand on inductive techniques and begin
to examine relationships between variables that are of interest to us.
Chapter 5 covers the important area of nonparametric statistics.
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