Lesson Plan: Experimental Design in Data Analysis
Subject: Data Analysis
Topic: Experimental Design
Grade Level: College (Undergraduate)
Duration: 1.5 hours
Lesson Objectives:
By the end of this lesson, students will be able to:
1. Define experimental design and its importance in data analysis.
2. Identify the key components of an experimental design.
3. Differentiate between types of experimental designs.
4. Apply the concepts of control groups, randomization, and replication.
5. Analyze examples of experimental designs and discuss their relevance to data analysis.
Lesson Outline:
I. Introduction to Experimental Design (15 mins)
Definition:
Experimental design refers to planning and structuring experiments to ensure that the data collected can answer
the research question effectively and be analyzed with statistical methods.
Importance:
Helps determine cause-and-effect relationships between variables.
Minimizes bias and variability in results.
Ensures reproducibility and reliability of findings.
Key Components:
1. Independent Variable (IV): The factor that is manipulated.
2. Dependent Variable (DV): The factor that is measured.
3. Control Variables: Factors that remain constant to ensure fair testing.
4. Hypothesis: A prediction that can be tested through experimentation.
II. Types of Experimental Design (25 mins)
1. Completely Randomized Design (CRD):
o Each subject is randomly assigned to one of the treatment groups.
o Example: Testing the effect of a new drug on blood pressure by randomly assigning patients to
either the treatment or placebo group.
2. Randomized Block Design (RBD):
o Subjects are divided into blocks based on some characteristic, and within each block, subjects are
randomly assigned treatments.
o Example: Testing a new teaching method in schools, where each block is a different school and
randomization occurs within each school.
3. Factorial Design:
o Involves two or more independent variables studied simultaneously to assess their interaction
effects.
o Example: Testing the effect of different diets and exercise regimens on weight loss.
4. Matched Pairs Design:
o Subjects are paired based on similar characteristics, with one from each pair assigned to different
treatments.
o Example: Comparing the performance of two algorithms using the same dataset for both.
III. Essential Principles of Experimental Design (20 mins)
1. Randomization:
o Randomly assign subjects to different treatment groups to ensure unbiased results.
2. Replication:
o Conduct the experiment multiple times to ensure consistency and accuracy in results.
3. Control:
o Use control groups to compare the treatment effects with no intervention or standard treatment.
4. Blinding:
o Involves not informing participants (single-blind) or both participants and researchers (double-
blind) about which group receives the treatment to reduce bias.
5. Placebo:
o A fake treatment used in control groups to assess the true effect of the experimental intervention.
IV. Steps in Designing an Experiment (10 mins)
1. Formulate the research question and hypothesis.
2. Choose the appropriate design (CRD, RBD, Factorial, etc.).
3. Define the independent and dependent variables.
4. Control confounding variables.
5. Determine the sample size and method of randomization.
6. Carry out the experiment and collect data.
7. Analyze the data using statistical tools.
V. Case Study: Designing an Experiment (20 mins)
Scenario:
A school is interested in finding out whether incorporating technology (tablets) into classroom teaching
improves students' mathematics scores. Design an experiment to investigate this.
Discussion Questions:
1. What is the independent variable?
2. What is the dependent variable?
3. How would you implement randomization in this case?
4. Would you use a control group? Why or why not?
5. How would you handle potential biases?
VI. Conclusion and Assignment (10 mins)
Summary:
Experimental design is critical in ensuring the reliability and validity of data.
Different experimental designs serve different research purposes.
Key principles like randomization, control, and replication enhance the quality of experimental research.
Assignment:
Design a simple experiment that could test the effect of study hours on student performance. Identify the
independent and dependent variables, and discuss how you would control for confounding factors.
References:
Montgomery, D. C. (2017). Design and Analysis of Experiments. Wiley.
Fisher, R. A. (1935). The Design of Experiments. Oliver & Boyd.
