Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

Statistics Organizer: Finding the Right
Statistics for Your Data
Overview: Three Basic Data Structures
After students have completed a statistics course, they occasionally are confronted
with situations in which they have to apply the statistics they have
learned. For example, in the context of a research methods course, or while
working as a research assistant, students are presented with the results from a
study and asked to do the appropriate statistical analysis. The problem is that
many of these students have no idea where to begin. Although they have learned
the individual statistics, they cannot match the statistical procedures to a specific
set of data. The Statistics Organizer attempts to help you find the right statistics
by providing an organized overview for most of the statistical procedures presented
in this book.
We assume that you know (or can anticipate) what your data look like. Therefore,
we begin by presenting some basic categories of data so you can find that one
that matches your own data. For each data category, we then present the potential
statistical procedures and identify the factors that determine which are appropriate
for you based on the specific characteristics of your data. Most research data can
be classified in one of three basic categories.
Category 1: A single group of participants with one score per participant.
Category 2: A single group of participants with two variables measured for
each participant.
Category 3: Two (or more) groups of scores with each score a measurement
of the same variable.
In this section we present examples of each structure. Once you match your own
data to one of the examples, you can proceed to the section of the chapter in which
we describe the statistical procedures that apply to that example.
■ Scales of Measurement
Before we begin discussion of the three categories of data, there is one other
factor that differentiates data within each category and helps to determine which
statistics are appropriate. In Chapter 1 we introduced four scales of measurement
and noted that different measurement scales allow different kinds of mathematical
manipulation, which result in different statistics. For most statistical applications,
however, ratio and interval scales are equivalent so we group them together for
the following review.
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