Ch3 Variables and Hypothesis
Language of Research
Success
of
Research
Clear conceptualization
of concepts
Shared understanding
of concepts
What is a Variable?
Difference between concepts or characteristics
 Relationship between concepts or characteristics
 Variances: Square or standard deviation
 Deviations: Differences between the standard deviation
and the mean
 Variability: Extent of scores being different from one
and other

Operational Definitions
How can we define the variable
“class level of students”?
Freshman
 Sophomore
 Junior
 Senior

< 30 credit hours
 30-50 credit hours
 60-89 credit hours
 > 90 credit hours


Operational definitions are definitions stated in terms of
specific criteria for testing or measurement. The
specifications must be so clear that any competent person
using them would classify the objects in the same way.

If a study of college students required classifying students
by class level, a definition of each category would be
necessary. Students could be grouped by class level based
on self-report, number of years in school, or number of
credit hours completed. Credit hours is the most precise
measure.
A Variable Is the Property Being
Studied
Act
Event
Variable
Characteristic
Trait
Attribute
 In
practice, the term variable is used as a
synonym for the property being studied. In
this context, a variable is a symbol of an
event, act, characteristic, trait, or attribute
that can be measured and to which we
assign categorical values. The different
types of variables are presented on the
following slides.
Types of Variables
Dichotomous
Male/Female
Employed/ Unemployed
Discrete
Ethnic background
Educational level
Religious affiliation
Continuous
Income
Temperature
Age

For the purposes of data entry and analysis, we
assign numerical values to a variable based on
that variable’s properties. Dichotomous variables
have only two values that reflect the absence or
presence of a property. Variables also take on
values representing added categories such as
demographic variables. All such variables are said
to be discrete since only certain values are
possible. Continuous variables take on values
within a given range or, in some cases, an infinite
set.
Types of Variables
Quantitative: Numerical degree of difference
 Qualitative (categorical): Difference or relationship
between experiments, treatments, or methods
 Independent: Influence or affect on other variables
(treatments or experiments)
 Dependent: Affected or expected to be affected by the
independent variable (the criterion or outcome variables
 Manipulated: Treatments or experiments

Types of Variables (continued)
Select: Variables that already exits that the researcher
may want to use in their study
 Extraneous: Variables that occur without control

Types of variables
 Forms:
continuous variable & categorical
variable
 Sources: active variable & attribute variable
 Relationships: Independent variable、dependent
variable 、moderator variable 、control
variable 、confounding variable & intervening
variable
Independent and Dependent
Variable Synonyms
Independent Variable (IV) Dependent Variable (DV)
 Predictor
 Criterion
 Presumed cause
 Presumed effect
 Stimulus
 Response
 Predicted from…
 Predicted to….
 Antecedent
 Consequence
 Manipulated
 Measured outcome
Exhibit 3-2
 Exhibit 3-2 presents the commonly used
synonyms for independent and dependent
variables.
 An independent variable is the variable
manipulated by the researcher to cause an effect
on the dependent variable.
 The dependent variable is the variable expected to
be affected by the manipulation of an independent
variable.

The Relationship between Independent and
Dependent Variables
Independent
Variables
Dependent
Variable (s)
(presumed or
possible cause)
(presumed
Results)
Relationships Among Variable Types
Relationships Among Variable Types
Relationships Among Variable Types
Moderating Variables (MV)
The introduction of a four-day week (IV) will lead
to higher productivity (DV), especially among
younger workers (MV)
 The switch to commission from a salary
compensation system (IV) will lead to increased
sales (DV) per worker, especially more
experienced workers (MV).
 The loss of mining jobs (IV) leads to acceptance
of higher-risk behaviors to earn a familysupporting income (DV) – particularly among
those with a limited education (MV).

 Moderating
variables are variables that are
believed to have a significant contributory or
contingent effect on the originally stated IVDV relationship. Whether a variable is
treated as an independent or as a
moderating variable depends on the
hypothesis. Examples of moderating
variables are shown in the slide.
Extraneous Variables (EV)
 With
new customers (EV-control), a switch
to commission from a salary compensation
system (IV) will lead to increased sales
productivity (DV) per worker, especially
among younger workers (MV).
 Among residents with less than a high
school education (EV-control), the loss of
jobs (IV) leads to high-risk behaviors (DV),
especially due to the proximity of the firing
range (MV).

Extraneous variables are variables that could
conceivably affect a given relationship. Some can
be treated as independent or moderating variables
or assumed or excluded from the study. If an
extraneous variable might confound the study, the
extraneous variable may be introduced as a
control variable to help interpret the relationship
between variables. Examples are given in the slide.
Intervening Variables (IVV)
 The
switch to a commission compensation
system (IV) will lead to higher sales (DV)
by increasing overall compensation (IVV).
 A promotion campaign (IV) will increase
savings activity (DV), especially when free
prizes are offered (MV), but chiefly among
smaller savers (EV-control). The results
come from enhancing the motivation to
save (IVV).
 An
intervening variable (IVV) is a factor
that affects the observed phenomenon but
cannot be measured or manipulated. It is a
conceptual mechanism through which the IV
and MV might affect the DV
Research Hypothesis

Definition
-- A predication regarding a possible outcome
-- A declarative sentence that conjectures a relationship between
two or more variables (statement)
-- Well stated hypotheses are derived from the research question
or problem
-- You need a rationale for making predictions or a hypotheses
1. The review of the literature
2. Theory
Research Hypothesis (continued)
-- Differences between directional and non-directional
hypotheses
1. A directional hypothesis show a significant difference
between two or more variables and usually uses
inferential statistics in its analysis
2. A non-directional hypothesis shows that there is a
difference or a relationship between two or more variables
and usually uses descriptive statistics or qualitative research
to analyze the data
Propositions and Hypotheses
 Brand
Manager Jones (case) has a higherthan-average achievement motivation
(variable).
Generalization
 Brand
managers in Company Z (cases)
have a higher-than-average achievement
motivation (variable).
 A proposition
is a statement about
observable phenomena that may be judged
as true or false. A hypothesis is a
proposition formulated for empirical testing.
A case is the entity or thing the hypothesis
talks about. When the hypothesis is based
on more than one case, it would be a
generalization. Examples are provided in the
slide.
Hypothesis Formats
Descriptive Hypothesis
 In Detroit, our potato
chip market share
stands at 13.7%.
 American cities are
experiencing budget
difficulties.
Research Question
 What is the market
share for our potato
chips in Detroit?
 Are American cities
experiencing budget
difficulties?




A descriptive hypothesis is a statement about the existence,
size, form, or distribution of a variable. Researchers often
use a research question rather than a descriptive
hypothesis. Examples are provided in the slide. Either
format is acceptable, but the descriptive hypothesis has
three advantages over the research question.
Descriptive hypotheses encourage researchers to
crystallize their thinking about the likely relationships.
Descriptive hypotheses encourage researchers to think
about the implications of a supported or rejected finding.
Descriptive hypotheses are useful for testing statistical
significance.
Relational Hypotheses
Correlational

Young women (under 35)
purchase fewer units of
our product than women
who are older than 35.
Causal



The number of suits sold
varies directly with the
level of the business cycle.
An increase in family
income leads to an
increase in the percentage
of income saved.
Loyalty to a grocery store
increases the probability of
purchasing that store’s
private brand products.

A relational hypothesis is a statement about the
relationship between two variables with respect to some
case. Relational hypotheses may be correlational or
explanatory (causal).

A correlational hypothesis is a statement indicating that
variables occur together in some specified manner without
implying that one causes the other.

A causal hypothesis is a statement that describes a
relationship between two variables in which one variable
leads to a specified effect on the other variable.
The Role of Hypotheses
Guide the direction of the study
Identify relevant facts
Suggest most appropriate research
design
Provide framework for organizing
resulting conclusions
Characteristics of Strong
Hypotheses
Adequate
A
Strong
Hypothesis
Is
Testable
Better
than rivals
Theory within Research


Exhibit 3-5
What is the difference between theories and hypotheses?
 Theories tend to be complex, abstract, and involve multiple
variables.
 Hypotheses tend to be simple, limited-variable statements
involving concrete instances.

A theory is a set of systematically interrelated concepts,
definitions, and propositions that are advanced to explain
or predict phenomena. To the degree that our theories are
sound and fit the situation, we are successful in our
explanations and predictions.
 The product life cycle, shown in Exhibit 3-5, is an example of a
theory.
The Role of Reasoning


Exhibit 3-7:
Business models are developed through the use of inductive and
deductive reasoning.

As illustrated in Exhibit 3-7, a business model may originate from
empirical observations about market behavior based on researched
facts and relationships among variables.

Inductive reasoning allows the modeler to draw conclusions from the
facts or evidence in planning the dynamics of the model. The modeler
may also use existing theory, managerial experience or judgment, or
facts.
The Scientific Method
Direct observation
Clearly defined variables
Clearly defined methods
Empirically testable
Elimination of alternatives
Statistical justification
Self-correcting process

Good business research is based on sound reasoning because
reasoning is essential for producing scientific results. This slide
introduces the scientific method and its essential tenets. The scientific
method guides our approach to problem-solving.

An important term in the list is empirical. Empirical testing denotes
observations and propositions based on sensory experiences and/or
derived from such experience by methods of inductive logic, including
mathematics and statistics. Researchers using this approach attempt
to describe, explain, and make predictions by relying on information
gained through observation.

The scientific method is described as a puzzle-solving activity.
Researchers
Encounter problems
 State problems
 Propose hypotheses
 Deduce outcomes
 Formulate rival
hypotheses
 Devise and conduct
empirical tests
 Draw conclusions

Sound Reasoning
Types of Discourse
Exposition
Deduction
Argument
Induction
Exposition consists of statements that describe
without attempting to explain.
 Argument allows us to explain, interpret, defend,
challenge, and explore meaning. There are two
types of argument: deduction and induction.

 Deduction is a form of reasoning in which the conclusion
must necessarily follow from the premises given. The
next slide provides an example of a deductive argument.
 Induction is a form of reasoning that draws a conclusion
from one or more particular facts or pieces of evidence.
Slide 2-8 illustrates an inductive argument.
Deductive Reasoning
Inner-city household
interviewing is especially
difficult and expensive
This survey involves
substantial inner-city
household interviewing
The interviewing in this
survey will be especially
difficult and expensive
© 2002 McGraw-Hill Companies, Inc., McGraw-Hill/Irwin
Inductive Reasoning
 Why
didn’t sales increase during our
promotional event?
Regional retailers did not have sufficient stock
to fill customer requests during the
promotional period
A strike by employees prevented stock from
arriving in time for promotion to be effective
A hurricane closed retail outlets in the region
for 10 days during the promotion
Why Didn’t Sales Increase?
Exhibit 3-8
 Induction and deduction can be used together in
research reasoning. Induction occurs when we
observe a fact and ask, “Why is this?” In answer to
this question, we advance a tentative explanation
or hypothesis. The hypothesis is plausible if it
explains the event or condition (fact) that
prompted the question. Deduction is the process
by which we test whether the hypothesis is
capable of explaining the fact.
 Exhibit 3-8 illustrates this process.

Tracy’s Performance
Advantages of using a Hypothesis




Helps the researcher think more clearly and careful about what it
is you are investigating (keeps you focused)
Helps the researcher think more deeply and specifically about the
possible outcomes (critically evaluating what you are doing and
how you are doing it, emphasizing the precise nature of the study)
It makes for specific predictions based on prior evidence or
theory arguments.
Helps the researcher to see or not to see the relationships or
differences between variables
Disadvantages of using a Hypothesis



In qualitative research stating the hypothesis would unnecessary
before the research begins because it is difficult to predict what
the findings might be
It creates a bias by helping the researcher to arrange procedures
and/or manipulate the data to bring about a desired outcome.
The hypothesis may take the attention away from noticing other
things that might develop through the research.
Hypothesis Check List






Do your hypotheses suggest the relationship between two or
more variables?
Do your hypotheses specify the nature of the relationship?
Do the hypotheses imply the research design to be used ton study
the relationships? (differences relationships, significance)?
Are the hypotheses free of mentioning specific measures?
Are the hypotheses free of unnecessary methodological detail?
Have you kept your hypotheses to manageable number? (five or
fewer)