1. Business Research Methods William G. Zikmund
Chapter 12:
Experimental Research

2. 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

3. 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

4. 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.

5. Experiment Treatment
Alternative manipulations of the independent variable being investigated

6. Independent Variable The experimenter controls independent variable.
The variable’s value can be manipulated by the experimenters to whatever they wish it to be.

7. Manipulation of Independent Variable
Classificatory Vs. continuous variables
Experimental and control groups
Treatment levels
More than one independent variable

8. Experimental Treatments
The alternative manipulations of the independent variable being investigated

9. Dependent Variable
Its value is expected to be dependent on the experimenter’s manipulation
Criterion or standard by which the results are judged

10. Dependent Variable Selection Measurement
e.g... sales volume, awareness, recall,
Measurement

11. Test Units
Subjects or entities whose response to the experimental treatment are measured or observed.

12. Two Types of Experimental Error
Constant errors
Random errors

13. Field versus Laboratory Experiments

14. Controlling Extraneous Variables
Elimination of extraneous variables
Constancy of conditions
Order of presentation
Blinding
Random assignment

15. How May an Experimenter control for Extraneous Variation?
Eliminate Extraneous Variables
Hold Conditions Constant
Randomization
Matching Subjects

16. Establishing Control

17. Demand Characteristics
Experimental procedures that intentionally hint to subjects something about the experimenter’s hypothesis

18. Demand Characteristics
Guinea pig effect
Hawthorne effect

19. Field Vs. Laboratory Experiment

20. Laboratory Experiment
Field Experiment
Artificial-Low Realism
Natural-High Realism
Few Extraneous
Variables
Many Extraneous
Variables
High control
Low control
Low Cost
High Cost
Short Duration
Long Duration
Subjects Aware of
Participation
Subjects Unaware of
Participation

21. Control Groups
Isolate extraneous variation

22. 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?

23. Factors Influencing Internal Validity
History
Maturation
Testing
Instrumentation
Selection
Mortality

24. Isolating Extraneous Variation with a Control Group
History Effects
Maturation Effects
Mortality Effects

25. Type of Extraneous Variable
Example
History - Specific events in the
environment between the Before
and After measurement that are
beyond the experimenter’s control
Maturation - Subjects change
during the course of the experiment
Testing - The Before measure alerts
or sensitizes subject to nature of
experiment or second measure.
A major employer
closes its plant in
test market area
Subjects become
tired
Questionnaire
about the traditional
role of women
triggers enhanced
awareness of women
in an experiment.

26. Instrument - Changes in
instrument result in response bias
Selection - Sample selection
error because of differential
selection comparison groups
Mortality - Sample attrition; some subjects withdraw from experiment
New questions about
women are interpreted
differently from earlier
questions.
Control group and
experimental group is
self-selected group
based on preference for
soft drinks
Subjects in one group
of a hair dying study
marry rich widows and
move to Florida

27. How can Internal Validity Increase?

28. Increasing Internal Validity
Control group
Random assignment
Pretesting and posttesting
Posttest only

29. What are the Different Basic Experimental Designs?

30. Quasi-Experimental Designs
One Shot Design (After Only)
One Group Pretest-Posttest
Static Group Design

31. One Shot Design (After Only)
X O1

32. One Group Pretest-Posttest
O1 X O2

33. Static Group Design
Experimental Group X O1
Control Group O2

34. Three Good Experimental Designs
Pretest - Posttest Control Group Design
Posttest Only Control Group
Solomon Four Group Design

35. Pretest-Posttest Control Group Design
Experimental Group R O1 X O2
Control Group R O3 X O4

36. Posttest Only Control Group
Experimental Group R X O1
Control Group R O2

37. One-Shot Design Internal Validity Problems
History
weak
Maturation
Testing
not relevant
Instrumentation
not relevant
Selection
weak
Mortality

38. One-Group Pretest-Posttest Internal Validity Problems
History
weak
Maturation
Testing
Instrumentation
weak
Selection
controlled
Mortality

39. Static-Group Design Internal Validity Problems
History
controlled
Maturation
possible source of concern
Testing
Instrumentation
controlled
Selection
weak
Mortality

40. Pretest-Posttest Control Internal Validity Problems
History
controlled
Maturation
Testing
Instrumentation
controlled
Selection
Mortality

41. Solomon Four-Group Design Internal Validity Problems
History
controlled
Maturation
Testing
Instrumentation
controlled
Selection
Mortality

42. Posttest-Only Control Internal Validity Problems
History
controlled
Maturation
Testing
Instrumentation
controlled
Selection
Mortality

43. Experimental Group 1: R O1 X O2 Experimental Group 2: R X O5
Solomon Four Group Design
Experimental Group 1: R O1 X O2
Control Group 1: R O O4
Experimental Group 2: R X O5
Control Group 2: R X O6

44. Advanced Experimental Designs are More Complex
Completely randomized
Randomized block design
Latin square
Factorial

45. 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.

46. Completely Randomized Designs
Control:
no music
Experimental
treatment:
slow music
Experimental
treatment:
fast music
Average minutes
shopper spends
in store

47. Independent Variable A
Level 1
Level 2
Level 3
Group A
Group B
Group C

48. Completely Randomized Design
With a pretest posttest
Group A R O1 X1 O2
Group A R O3 X2 O4
Group A R O5 X3 O6

49. Completely Randomized Design
With a posttest
Group A R X1 O1
Group B R X2 O2
Group C R X3 O3

50. 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.

51. Randomized Block Design
Independent Variables
Control:
no music
Experimental
treatment
slow music
Experimental
treatment:
fast music
Mornings and
afternoons
Evening hours
Blocking variable

52. Factorial Design
An experiment that investigates the interaction of two or more variables on a single dependent variable.

53. Independent Variable 1 No Music Slow Music Fast Music No Music
cart signs
Independent Variable 2
Grocery
cart signs

54. Factorial Design -- Roller Skates
Package Design
Price Red Gold
$25 Cell 1 Cell 4
$30 Cell 2 Cell 5
$35 Cell 3 Cell 6

55. 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.

56. 2 x 2 Factorial Design Ad A Ad B Men Women 65 > > 70 60
Main Effects
of Gender
>
70 60
>
Main Effects of Ad

57. Interaction Between Gender and Advertising Copy
100 90 80 70 60 50 40 30 20 10
Ad A Ad B
Women
Men
Believability

58. Independent Variable 1 Level 1 Level 2 Level 1 Level 2 Group A Group B
Group D
Group C

59. 2 x 2 Factorial with a Pretest Posttest
Group A R O1 X11 O2
Group B R O3 X21 O4
Group C R O5 X12 O6
Group D R O7 X22 O8

60. 2 x 2 Factorial Design with a Posttest Measure
Group A R X11 O1
Group B R X21 O2
Group C R X12 O3
Group D R X22 O4

61. A Test Market Experiment on Pricing
Sales in Units (thousands)
Test Market A, B, or C
Test Market D, E, or F
Test Market G, H, or I
Test Market J, K, or L
Mean
Grand Mean
Regular Price
$.99
130
118 87 84
X1=104.75
X=119.58
Reduced Price
$.89
145
143
120
131
X2=134.75
Cents-Off Coupon
Regular Price
153
129 96 99
X1=119.25

62. 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.

63. Order of Usage
A B C 2 B C A 3 C A B
SUBJECT

64. TEST MARKETING Controlled experimentation Not just trying
something
out
But scientific
testing

65. Test Marketing Controlled experimentation Not just trying
something
out
But scientific
testing

66. Test Marketing
An experimental procedure that provides an opportunity to test a new product or a new marketing plan under realistic market conditions to measure sales or profit potential.

67. Functions of Test Marketing
IDENTIFY AND
CORRECT
WEAKNESSES
IN PLANS
ESTIMATE
OUTCOMES

68. A Lengthy and Costly Procedure
$$$$$
When not
to Test?
Loss of
Secrecy
How Long
Should a
Test Last?

69. Popular Test Markets Pittsfield, Massachusetts
Charlotte, North Carolina
Columbus, Ohio
Little Rock, Arkansas
Evansville, Indiana
Cedar Rapids, Iowa
Eau Claire,Wisconsin
Wichita, Kansas
Tulsa, Oklahoma
Omaha, Nebraska
Grand Junction. Colorado
Wichita Falls, Texas
Odessa-Midland, Texas

70. Selecting a Test Market
Population size
Demographic composition
Lifestyle considerations
Competitive situation
Media
Self-contained trading area
Overused markets - secrecy

71. Control Method of Test Marketing
Small city
Low chance of being detected
Distribution is forced (guaranteed)

72. The Advantages of Using the Control Method of Test Marketing
Reduced costs
Shorter time period needed for reading test market results
Increased secrecy from competitors
No distraction of company salespeople from regular product lines

73. Some Problems Estimating Sales Volume
Over-attention
Unrealistic store conditions
Reading competitive environment incorrectly
Incorrect volume forecasts
Adjusted data
Penetration and repeat purchase rate
Time lapse

74. High Tech Test Markets Electric Test Markets Simulated Test Markets
Virtual-reality
Simulated
Test Markets