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Questions and Answers
What is a notable characteristic of pre-experimental designs?
Which of the following describes a One-Shot Design?
What distinguishes the One-Group Pretest-Posttest Design from other designs?
Which pre-experimental design is characterized by the absence of a control group?
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Which of these designs is most commonly used in exploratory research?
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What are independent variables in experimentation?
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What is a primary advantage of using Randomized Block Design?
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Which of the following best describes dependent variables?
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What is an example of extraneous variables?
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In Latin Square Design, how are test units grouped?
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What does the term 'interaction effect' refer to in Factorial Design?
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Which type of experimentation occurs in real-world settings?
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Which of the following best characterizes a 3 x 2 factorial design?
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What is the role of test units in experimentation?
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Which of the following can impair the validity of experimental results?
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Which of these are considered factors affecting the validity of an experiment?
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What is the dependent variable in the grocery store chain example using factorial design?
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In the context of experimentation, what is the primary concern of validity?
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Which type of variable is typically unaffected by the manipulation of independent variables?
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What distinguishes Factorial Design from other experimental designs?
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In which scenario would Randomized Block Design be most beneficial?
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What is a major weakness of the Static Group Design?
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In which design is the effect of extraneous variables assumed to be the same for both experimental and control groups?
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Which design utilizes a testing effect as a risk factor?
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What defines a Completely Randomized Design?
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How is the treatment effect calculated in a Pretest-Posttest Control Group Design?
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Which design eliminates the risk of a testing effect?
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What is a key characteristic of the Randomized Block Design?
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When is the Completely Randomized Design not recommended?
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What does the notation O1 symbolize in experimental designs?
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What is the likely approach to treatment evaluation when pre-testing is impractical?
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Study Notes
Experimentation Overview
- Experimentation involves manipulating one or more variables to observe effects on dependent variables.
- Validity in experimentation is influenced by external factors like history, maturation, testing, instrumentation, sampling bias, and mortality.
Definition and Key Concepts
- Independent Variables: Variables manipulated to study their effects (e.g., price levels).
- Dependent Variables: Measurable outcomes affected by independent variables (e.g., sales, profits).
- Test Units: Subjects (individuals or organizations) whose responses are analyzed (e.g., consumers).
- Extraneous Variables: Variables other than independent variables that can influence the outcome (e.g., store location).
Types of Experimentation
- Field Experimentation: Conducted in real-world settings.
- Laboratory Experimentation: Conducted in controlled environments.
Experimental Design Types
- Pre-Experimental Design: Lacks adequate controls for validity.
- True Experimental Design: Incorporates controls and random assignments, enhancing validity.
- Extension of True Experimental Design: Builds on true designs for more complex research needs.
Pre-Experimental Designs
- Characteristics: Often exploratory, do not classify as true experiments, and may lack control over extraneous variables.
One-Shot Design
- Measures a single outcome after treatment with no comparison group.
- Diagram: X -> O1
One-Group Pretest-Posttest Design
- Measures outcomes before and after treatment in a single group, lacking a control group.
- Risk of results being affected by maturation between tests.
- Diagram: O1 -> X -> O2
Static Group Design
- Compares an experimental group with a control group after treatment without pre-measurement.
- Major weakness: uncertainty about group equivalence prior to treatment.
- Diagram: Experimental Group X -> O1, Control Group -> O2
Advanced Experimental Designs
Pretest-Posttest Control Group Design
- Involves both experimental and control groups tested before and after treatment, with random assignments to enhance validity.
- Diagram: (O2 - O1) - (O4 - O3)
- Example: Increase in brand awareness after advertising treatment calculated as 13%.
Posttest-Only Control Group Design
- Tests after treatment exposure with random assignments for both groups, minimizing testing effects.
- Example: Evaluate a foot remedy's effectiveness without a pretest.
Randomized Design Approaches
Completely Randomized Design
- Treatments randomly assigned, allowing control over extraneous variables.
- Suitable when test members are similar regarding extraneous variables.
Randomized Block Design
- Treatments assigned within identified blocks based on extraneous variables (e.g., demographic factors).
Specialized Designs
Latin Square Design
- Manages two extraneous variables by systematically arranging test units in a grid format.
- Useful for comparing multiple treatment levels.
Factorial Design
- Examines multiple independent variables' effects on dependent variables.
- Main effects assess each independent variable's impact, while interaction effects evaluate combined variable influences.
- Example: A study involving store hours and promotions to analyze sales change, requiring multiple experimental groups.
Summary of Experimentation
- Experimentation involves careful design to manipulate and measure variables effectively.
- Understanding and controlling variables is essential for deriving valid conclusions.
- Increased sophistication in design leads to improved clarity and impact of results in marketing research.
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Description
Explore Session 10 of the MBA III Marketing Research course, focusing on the designs of experimentation. This quiz will test your understanding of experimental design concepts, methods, and applications. Enhance your marketing research skills through this targeted assessment.
