📊Experimental Design Unit 11 – Designing Experiments for Analysis

Key Concepts and Terminology

• Experimental design involves planning and conducting experiments to test hypotheses and draw conclusions
• Independent variable (IV) represents the factor being manipulated or changed in an experiment
• Dependent variable (DV) represents the outcome or response being measured in an experiment
• Extraneous variables are factors that may influence the DV but are not of primary interest in the study
  • Confounding variables are extraneous variables that systematically vary with the IV and can affect the DV
• Control group serves as a baseline for comparison, typically not exposed to the IV
• Experimental group is exposed to the IV being tested
• Randomization involves randomly assigning participants to different groups or conditions to minimize bias
• Replication refers to repeating an experiment multiple times to assess the consistency of results

Experimental Design Principles

• Randomization helps ensure that any differences between groups are due to the IV rather than preexisting differences
• Replication allows researchers to assess the reliability and generalizability of findings
• Control of extraneous variables is crucial to minimize their influence on the DV
  • Techniques include holding extraneous variables constant, counterbalancing, and using matched pairs
• Blinding involves keeping participants and/or researchers unaware of the group assignments to reduce bias
  • Single-blind design conceals group assignments from participants
  • Double-blind design conceals group assignments from both participants and researchers
• Manipulation of the IV should be carefully planned and executed to ensure it is the only factor varying between groups
• Measurement of the DV should be reliable, valid, and sensitive to changes caused by the IV
• Sample size should be sufficient to detect meaningful differences between groups and ensure adequate statistical power

Types of Experimental Designs

• Between-subjects design compares different groups of participants, each exposed to a different level of the IV
• Within-subjects design exposes each participant to all levels of the IV, allowing for comparisons within individuals
• Factorial design manipulates two or more IVs simultaneously to examine their individual and combined effects on the DV
  • Allows for the investigation of main effects and interactions between IVs
• Repeated measures design involves measuring the DV multiple times for each participant under different conditions
• Quasi-experimental design lacks random assignment of participants to groups but still manipulates the IV
  • Useful when random assignment is not feasible or ethical
• Single-case design focuses on the detailed analysis of a small number of individuals or cases over time
• Crossover design exposes each participant to all levels of the IV in a randomized order, with a washout period between conditions

Sampling Methods and Techniques

• Random sampling involves selecting participants from a population in a way that gives each individual an equal chance of being chosen
  • Helps ensure the sample is representative of the population
• Stratified sampling divides the population into subgroups (strata) based on specific characteristics and then randomly samples from each stratum
  • Ensures proportional representation of subgroups in the sample
• Cluster sampling involves dividing the population into clusters (naturally occurring groups) and randomly selecting entire clusters to include in the sample
• Convenience sampling selects participants based on their availability and willingness to participate
  • May limit the generalizability of findings to the broader population
• Purposive sampling selects participants based on specific criteria or characteristics relevant to the research question
• Sample size determination should consider the desired level of statistical power, effect size, and significance level
• Inclusion and exclusion criteria specify the characteristics that participants must or must not possess to be eligible for the study

Variables and Controls

• Independent variable (IV) is the factor being manipulated or changed by the researcher
  • Levels of the IV represent the different conditions or groups being compared
• Dependent variable (DV) is the outcome or response being measured, expected to be influenced by the IV
• Extraneous variables are factors other than the IV that may affect the DV
  • Control techniques aim to minimize their influence on the DV
• Control group serves as a baseline for comparison, not exposed to the IV
  • Helps determine if changes in the DV are due to the IV or other factors
• Placebo control involves giving a fake treatment to the control group to account for placebo effects
• Positive control is a group exposed to a treatment known to produce the expected effect, used to validate the experimental procedure
• Manipulation check assesses whether the IV was successfully manipulated as intended
• Operational definitions specify how variables will be measured or manipulated in the study

Data Collection Strategies

• Observations involve systematically watching and recording behavior or events
  • Can be structured (using predefined categories) or unstructured (open-ended)
• Surveys and questionnaires collect self-reported data from participants using a set of questions
  • Can be administered in person, by mail, phone, or online
• Interviews involve asking participants questions in a one-on-one or group setting
  • Can be structured (fixed questions), semi-structured (mix of fixed and open-ended questions), or unstructured (open-ended)
• Physiological measures assess biological or physical responses (heart rate, brain activity)
• Behavioral measures assess overt actions or responses (reaction time, accuracy)
• Archival data involves using existing records or data sources (medical records, public databases)
• Triangulation involves using multiple data collection methods to cross-validate findings
• Pilot testing helps refine data collection procedures and identify potential issues before the main study

Statistical Analysis Approaches

• Descriptive statistics summarize and describe the main features of a dataset (mean, median, standard deviation)
• Inferential statistics use sample data to make inferences or draw conclusions about the population
  • Hypothesis testing involves comparing sample data to a null hypothesis to determine if the results are statistically significant
• t-tests compare means between two groups or conditions
  • Independent samples t-test compares means from two separate groups
  • Paired samples t-test compares means from the same group under two different conditions
• Analysis of Variance (ANOVA) compares means across three or more groups or conditions
  • One-way ANOVA examines the effect of one IV on the DV
  • Factorial ANOVA examines the effects of two or more IVs on the DV
• Correlation assesses the strength and direction of the relationship between two variables
• Regression predicts the value of a DV based on one or more IVs
  • Linear regression assumes a linear relationship between variables
  • Multiple regression includes two or more predictor variables
• Effect size measures the magnitude of the difference between groups or the strength of the relationship between variables
• Statistical power is the probability of detecting a true effect when it exists, influenced by sample size, effect size, and significance level

Ethical Considerations in Experimentation

• Informed consent ensures that participants are fully informed about the study and voluntarily agree to participate
  • Includes information about the purpose, procedures, risks, benefits, and confidentiality of the study
• Confidentiality protects participants' personal information and ensures that data is kept secure and anonymous
• Debriefing involves providing participants with additional information about the study after their participation
  • Helps address any concerns or misconceptions and provides resources if needed
• Minimizing harm and maximizing benefits involves weighing the potential risks and benefits of the study for participants and society
• Deception should be used sparingly and only when necessary for the integrity of the study
  • Participants must be debriefed and any deception explained
• Vulnerable populations (children, prisoners, individuals with mental illness) require special considerations and protections
• Institutional Review Boards (IRBs) review and approve research proposals to ensure they meet ethical standards
• Responsible conduct of research involves adhering to ethical principles throughout the research process, from planning to dissemination of findings