Chapter 1
INTRODUCTION TO STATISTICS AND
RESEARCH
Going Forward
Your goals in this chapter are to learn:
• The logic of research and the purpose of statistical
procedures
• What a relationship between scores is
• When and why descriptive and inferential statistical
procedures are used
• What the difference is between an experiment and a
correlational study, and what the independent
variable, the conditions, and the dependent variable
are
• What the four scales of measurement are
Learning About Statistics
What is Statistics?
Statistics help make sense of data in four ways:
• Organize scores to see patterns
• Summarize data to understand general
characteristics
• Communicate results of a study
• Interpret what the data indicate
Studying Statistics
Carefully read and study the material
Use the in-chapter “Quick Practice”
Learn the terminology
Do the end-of-chapter study questions
Review the Chapter Summary tear-out card
Complete the Putting It All Together tear-out
card
Visit the CourseMate website
The Logic of Research
Behavioral Research
The goal of behavioral research is to understand
the “laws of nature” that apply to the behaviors
of living organisms.
Samples and Populations
• The entire group to which a law of nature
applies is the population
• A sample is a relatively small subset of a
population intended to represent, or stand in
for, the population
• The individuals measured in a sample are
called the participants
Samples and Populations
• Use the scores in a sample to infer—that is, to
estimate—the scores we would expect to find
in the population.
• This assumes a sample is representative of
the population.
• If a sample is unrepresentative, it inaccurately
reflects the population. Unrepresentative
samples may give misleading results.
Understanding Variables
A variable is anything that can produce two or
more different scores. Some common variables
in behavioral research are:
• Age
• Race
• Gender
• Personality type
• Physical attributes
Types of Variables
The two categories of variables are:
• Quantitative variables in which a score
indicates the amount of a variable that is
present and
• Qualitative variables that classify or
categorize an individual on the basis of some
characteristic
Understanding Relationships
Relationships
In a relationship, as the scores on one variable
change, the scores on the other variable change
in a consistent manner.
Types of Relationships
Simple relationships have one of two patterns. If
we call one variable X and the other variable Y,
then
• Pattern 1: The more you X, the more you Y
• Pattern 2: The more you X, the less you Y
Example: The more you drive distracted, the more
likely it is you will have an accident (Pattern 1).
Relationship Consistency
• If a score on one variable is always paired with
one and only one score on the other variable,
we have a perfectly consistent relationship.
• Perfect consistency is not required to have a
relationship, only some degree of consistency.
This means as the scores on one variable
change, the scores on the other variable tend
to change in a consistent fashion.
Relationship Consistency
When essentially the same set of Y scores are
paired with every X score, a relationship does
not exist.
Applying Descriptive and
Inferential Statistics
Applying Statistics
• Descriptive statistics are procedures for
organizing and summarizing sample data
• Inferential statistics are procedures for
drawing inferences about the scores and
relationship that would be found in the
population
Statistics Vs. Parameters
• A statistic is a number describing an
aspect of the scores in a sample
• A parameter is a number describing
an aspect of the scores in the population
Statistics Vs. Parameters
• Statistics are represented using English letters
such as A, B, C, etc.
• Parameters are represented using Greek
letters such as a, b, c, etc.
Understanding Experiments and
Correlational Studies
Research Designs
• A study’s design is the way the study is laid
out
• Different designs require different descriptive
and inferential procedures, so learn when to
use each procedure
• There are two major types of designs:
– Experiments
– Correlational studies
Experiments
In an experiment, the researcher actively
changes or manipulates one variable and then
measures participants’ scores on another
variable to see if a relationship is produced.
The Independent Variable
• The independent variable is changed or
manipulated by the experimenter
• A condition is the specific amount or
category of the independent variable
creating the specific situation under
which participants are studied
The Dependent Variable
The dependent variable is the variable
measuring a behavior or attribute of
participants we expect will be influenced by the
independent variable.
Can You?
Identify the independent variable, the
conditions of the independent variable, and the
dependent variable for the following study:
The effect of an intensive summer school
college preparatory program (compared to no
program) on the GPAs of at-risk freshmen
students.
Correlational Studies
In a correlational study, the researcher
measures participants’ scores on two variables
and then determines whether a relationship
exists.
The Characteristics of Scores
Measurement Scales
The kind of information scores convey depends
on the scale of measurement used. There are
four types of measurement scales:
• A nominal scale does not measure an amount;
rather, it categorizes or classifies individuals.
• An ordinal scale indicates rank order. There is no
score of 0 (zero), and the same amount does not
separate every pair of adjacent scores.
Measurement Scales (cont’d)
• An interval scale indicates an actual quantity, and
there is an equal amount separating any adjacent
scores. Interval scales do not have a “true” 0.
• A ratio scale also measures an actual quantity.
There is an equal amount separating any adjacent
scores, and 0 truly means none of the variable is
present.
Continuous Versus Discrete
Any variable also may be either continuous or
discrete.
• A continuous variable can be measured in
fractional amounts and so decimals make
sense
• A discrete variable can only be measured in
fixed amounts, which cannot be broken into
smaller amounts
Examples
For each of the following variables, indicate (1)
the measurement scale and (2) whether it is
continuous or discrete:
 The number of tickets sold to an event
 Your flavor preferences in soft drinks
 Weight
 IQ
Examples
The number of tickets sold to an event
 ratio, discrete
Your flavor preferences in soft drinks
 ordinal, discrete
Weight
 ratio, continuous
IQ
 interval, continuous