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Business Research Methods
William G. Zikmund
Chapter 12:
Experimental Research
Experiment
• A research investigation in which conditions are controlled
• One independent variable is manipulated (sometimes more than one)
• Its effect on a dependent variable is measured• To test a hypothesis
Basic Issues of Experimental Design
• Manipulation of the Independent Variable
• Selection of Dependent Variable
• Assignment of Subjects (or other Test Units)
• Control Over Extraneous Variables
The experimenter has some degree of control over the independent variable. The variable is independent because its value can be manipulated by the experimenter to whatever he or she wishes it to be.
Experiment Treatment
Alternative manipulations of the independent variable being
investigated
Independent Variable
• The experimenter controls independent variable.
• The variable’s value can be manipulated by the experimenters to whatever they wish it to be.
Manipulation of Independent Variable
• Classificatory Vs. continuous variables
• Experimental and control groups
• Treatment levels
• More than one independent variable
Experimental Treatments
• The alternative manipulations of the independent variable being investigated
Dependent Variable
• Its value is expected to be dependent on the experimenter’s manipulation
• Criterion or standard by which the results are judged
Dependent Variable
• Selection– e.g... sales volume, awareness, recall,
• Measurement
Test Units
• Subjects or entities whose response to the experimental treatment are measured or observed.
Two Types of Experimental Error
• Constant errors• Random errors
Field versus Laboratory Experiments
Establishing Control
Physical Control– Holding the value or level of extraneous
variables constant throughout the course of an experiment.
Statistical Control– Adjusting for the effects of confounding
variables by statistically adjusting the value of the dependent variable for each treatment conditions.
Design Control– Use of the experimental design to control
extraneous causal factors. Eg. Demand
Demand Characteristics
• Experimental procedures that intentionally hint to subjects something about the experimenter’s hypothesis
Demand Characteristics
• Guinea pig effect
• Hawthorne effect
Field Vs. Laboratory Experiment
Laboratory Experiment Field Experiment
Artificial-Low Realism
Few ExtraneousVariables
High control
Low Cost
Short Duration
Subjects Aware ofParticipation
Natural-High Realism
Many ExtraneousVariables
Low control
High Cost
Long Duration
Subjects Unaware ofParticipation
Control Groups
Isolate extraneous variation
When does an Experiment have Internal Validity?
Internal Validity - The ability of an experiment to answer the question whether the experimental treatment was the sole cause of changes in a dependent variable
Did the manipulation do what it was supposed to do?
Factors Influencing Internal Validity
• History
• Maturation
• Testing
• Instrumentation
• Selection
• Mortality
Isolating Extraneous Variationwith a Control Group
• History Effects
• Maturation Effects
• Mortality Effects
Type of Extraneous Variable Example
History - Specific events in theenvironment between the Beforeand After measurement that are beyond the experimenter’s control
Maturation - Subjects changeduring the course of the experiment
Testing - The Before measure alertsor sensitizes subject to nature of experiment or second measure.
A major employercloses its plant intest market area
Subjects become tired
Questionnaireabout the traditionalrole of women triggers enhanced awareness of womenin an experiment.
Instrument - Changes ininstrument result in response bias
Selection - Sample selectionerror because of differentialselection comparison groups
Mortality - Sample attrition; some subjects withdraw from experiment
New questions aboutwomen are interpreteddifferently from earlierquestions.
Control group and experimental group isself-selected groupbased on preference forsoft drinks
Subjects in one groupof a hair dying study marry rich widows and move to Florida
How can Internal Validity Increase?
Increasing Internal Validity
• Control group
• Random assignment
• Pretesting and posttesting
• Posttest only
What are the Different Basic Experimental Designs?
Quasi-Experimental Designs
• One Shot Design (After Only)
• One Group Pretest-Posttest
• Static Group Design
One Shot Design (After Only)
X O1
One Group Pretest-Posttest
O1 X O2
Static Group Design
Experimental Group X O1 Control Group O2
Three Good Experimental Designs
• Pretest - Posttest Control Group Design
• Posttest Only Control Group
• Solomon Four Group Design
Pretest-Posttest Control Group Design
Experimental Group R O1 X O2
Control Group R O3 O4
Posttest Only Control Group
Experimental Group R X O1
Control Group R O2
One-Shot DesignInternal Validity Problems
• History– weak
• Maturation– weak
• Testing– not relevant
• Instrumentation– not relevant
• Selection– weak
• Mortality– weak
One-Group Pretest-PosttestInternal Validity Problems
• History– weak
• Maturation– weak
• Testing– weak
• Instrumentation– weak
• Selection– controlled
• Mortality– controlled
Static-Group DesignInternal Validity Problems
• History– controlled
• Maturation– possible source of
concern
• Testing– controlled
• Instrumentation– controlled
• Selection– weak
• Mortality– weak
Pretest-Posttest ControlInternal Validity Problems• History
– controlled
• Maturation– controlled
• Testing– controlled
• Instrumentation– controlled
• Selection– controlled
• Mortality– controlled
Solomon Four-Group DesignInternal Validity Problems• History
– controlled
• Maturation– controlled
• Testing– controlled
• Instrumentation– controlled
• Selection– controlled
• Mortality– controlled
Posttest-Only ControlInternal Validity Problems
• History– controlled
• Maturation– controlled
• Testing– controlled
• Instrumentation– controlled
• Selection– controlled
• Mortality– controlled
Solomon Four Group Design
Experimental Group 1: R O1 X O2
Control Group 1: R O3 O4
Experimental Group 2: R X O5
Control Group 2: R O6
Advanced Experimental Designs are More Complex
• Completely randomized
• Randomized block design
• Latin square
• Factorial
Completely Randomized Design
• An experimental design that uses a random process to assign subjects (test units) and treatments to investigate the effects of only one independent variable.
Completely Randomized Designs
Average minutesshopper spendsin store
Control:no music
Experimentaltreatment:slow music
Experimentaltreatment:fast music
16 18 12
Independent Variable A
Group A Group B Group C
Level 1 Level 2 Level 3
Completely Randomized Design
With a pretest posttest
Group A R O1 X1 O2
Group B R O3 X2 O4
Group C R O5 X3 O6
With a posttest
Group A R X1 O1
Group B R X2 O2
Group C R X3 O3
Completely Randomized Design
Randomized Block Design
• An extension of the completely randomized design in which a single extraneous variable that might affect test units’ response to the treatment has been identified and the effects of this variable are isolated by blocking out its effects.
Independent Variables
Control:no music
Experimentaltreatment
slow music
Experimentaltreatment: fast music
Mornings andafternoons
Evening hours
Blo
ckin
g v
aria
ble
Randomized Block Design
Factorial Design
• An experiment that investigates the interaction of two or more variables on a single dependent variable.
Independent Variable 1
No Musiccart signs
Slow Music Fast MusicNo Music
Grocerycart signs
Ind
epen
den
t V
aria
ble
2
Price Red Gold
$25 Cell 1 Cell 4$30 Cell 2 Cell 5$35 Cell 3 Cell 6
Package Design
Factorial Design -- Roller Skates
Effects
• Main effect• The influence of a
single independent variable on a dependent variable.
• Interaction effect• The influence on a
dependent variable by combinations of two or more independent variables.
Men
Women
Ad A Ad B
65
65
70 60
Main Effectsof Gender
Main Effects of Ad
>
>
2 x 2 Factorial Design
100
90
80
70
60
50
40
30
20
10
Ad A Ad B
Women
Men
Bel
ieva
bilit
yInteraction Between Gender and
Advertising Copy
Level 1 Level 2
Level 1
Level 2
Group A
Group DGroup C
Group B
Ind
epen
den
t V
aria
ble
2Independent Variable 1
Group A R O1 X11 O2
Group B R O3 X21 O4
Group C R O5 X12 O6
Group D R O7 X22 O8
2 x 2 Factorial with a Pretest Posttest
Group A R X11 O1
Group B R X21 O2
Group C R X12 O3
Group D R X22 O4
2 x 2 Factorial Design with a Posttest Measure
A Test Market Experiment on Pricing
Sales in Units (thousands)
Regular Price$.99
1301188784
X1=104.75X=119.58
Reduced Price$.89
145143120131
X2=134.75
Cents-Off CouponRegular Price
1531299699
X1=119.25
Test Market A, B, or CTest Market D, E, or FTest Market G, H, or ITest Market J, K, or L
MeanGrand Mean
Latin Square Design
• A balanced, two-way classification scheme that attempts to control or block out the effect of two or more extraneous factors by restricting randomization with respect to the row and column effects.
1 2 3
1 A B C2 B C A3 C A B
Order of UsageS
UB
JEC
T
