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

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 Variation with a Control Group History Effects Maturation Effects Mortality Effects

Type of Extraneous VariableExample 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.

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

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) XO 1

One Group Pretest-Posttest O 1 X O 2

Static Group Design Experimental GroupX O 1 Control Group O 2

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 O 1 X O 2 Control Group R O 3 O 4

Posttest Only Control Group Experimental Group R X O 1 Control Group R O 2

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

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

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

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

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

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

Solomon Four Group Design Experimental Group 1: R O 1 X O 2 Control Group 1: R O 3 O 4 Experimental Group 2: R X O 5 Control Group 2: R O 6

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 minutes shopper spends in store Control: no music Experimental treatment: slow music Experimental treatment: fast music

Independent Variable A Group AGroup BGroup C Level 1Level 2Level 3

Completely Randomized Design With a pretest posttest Group ARO 1 X 1 O 2 Group BRO 3 X 2 O 4 Group CRO 5 X 3 O 6

With a posttest Group ARX 1 O 1 Group BRX 2 O 2 Group CRX 3 O 3 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 Experimental treatment slow music Experimental treatment: fast music Mornings and afternoons Evening hours Blocking variable 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 Music cart signs Slow MusicFast MusicNo Music Grocery cart signs Independent Variable 2

PriceRedGold $25Cell 1Cell 4 $30Cell 2Cell 5 $35Cell 3Cell 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 Main Effects of Gender Main Effects of Ad > > 2 x 2 Factorial Design

Ad AAd B Women Men Believability Interaction Between Gender and Advertising Copy

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

Group ARO 1 X 11 O 2 Group BRO 3 X 21 O 4 Group CRO 5 X 12 O 6 Group DRO 7 X 22 O 8 2 x 2 Factorial with a Pretest Posttest

Group ARX 11 O 1 Group BRX 21 O 2 Group CRX 12 O 3 Group DRX 22 O 4 2 x 2 Factorial Design with a Posttest Measure

A Test Market Experiment on Pricing Sales in Units (thousands) Regular Price $ X 1 = X= Reduced Price $ X 2 = Cents-Off Coupon Regular Price X 1 = 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

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.

ABC 2BCA 3CAB Order of Usage SUBJECT