The exam is open-book and open-note, but you must work alone.
The test consists of multiple-choice, fill-in-the-blank, and short-answer questions.
Time limit: 55 minutes.
The best way to study: review lecture materials, quizzes, and assigned readings.
Steps in conducting scientific research:
Identify a topic: Determine an area of interest or a research question.
Learn about the topic: Conduct literature reviews to gather existing knowledge.
Form a hypothesis: Develop a testable prediction.
Design the study: Establish the methodology, including independent and dependent variables.
Collect data: Gather empirical evidence through experiments, surveys, or observations.
Analyze data: Use statistical methods to evaluate results.
Interpret results: Compare findings with existing theories.
Communicate results: Present in a scientific format, typically following APA guidelines.
Pilot Studies: Small-scale preliminary studies used to test feasibility and refine methodologies before full-scale research.
Ecological vs. External Validity:
Ecological Validity: The extent to which findings apply to real-world settings.
External Validity: The ability to generalize findings to different populations or conditions.
Blind Review in Data Analysis: Preventing experimenter bias by keeping analysts unaware of study conditions.
Scientific Communication:
APA format: Abstract, Introduction, Methods, Results, Discussion.
Peer-reviewed journals and their impact factors.
Challenges of Measurement in Cognitive Science: Different disciplines (e.g., psychology, neuroscience) use distinct measurement techniques.
Non-experimental Methods:
Field Studies: Observing behavior in natural environments.
Surveys and Interviews: Collecting qualitative and quantitative responses.
Longitudinal Studies: Tracking changes in individuals/groups over time.
Case Studies: In-depth analysis of unique individuals (e.g., brain injury patients).
Experimental Methods:
Direct manipulation of independent variables to observe effects.
Requires control groups and random assignment to ensure validity.
Neuroscientific Methods:
Reaction Time Studies: Measuring cognitive processing speed through response times.
Eye Tracking: Using infrared cameras to analyze gaze patterns and attention.
EEG (Electroencephalography): Recording brain wave activity to study neural processes.
ERP (Event-Related Potentials): Averaging EEG responses to specific stimuli.
MEG (Magnetoencephalography): Measuring magnetic fields from neural activity for high temporal precision.
CT (Computed Tomography): Structural imaging technique using X-rays.
PET (Positron Emission Tomography): Tracking metabolic activity via radioactive tracers.
fMRI (Functional MRI): Measuring blood oxygen levels to infer brain activity.
DTI (Diffusion Tensor Imaging): Mapping white matter pathways in the brain.
Unethical Research Cases:
Tuskegee Syphilis Study: Withheld treatment from Black men to observe disease progression.
Henrietta Lacks: Her cancer cells were taken without consent and used for research.
Project MKUltra: CIA-funded experiments involving mind control and drug testing.
Key Ethical Guidelines:
Nuremberg Code: Established voluntary consent as a research requirement.
Declaration of Helsinki: Guidelines for ethical medical research.
Belmont Report: Defined principles of respect, beneficence, and justice.
Institutional Review Boards (IRB):
Committees ensuring research adheres to ethical standards.
Review studies to minimize risks and ensure informed consent.
Boolean Search Methods:
Using "AND" to narrow results.
Using "OR" to expand results.
Using "NOT" to exclude certain terms.
Role of Citations:
Preventing plagiarism and acknowledging sources.
Difference between reference sections (cited works) and bibliographies (all consulted works).
Operational Definitions:
Defining abstract concepts through measurable variables.
Population vs. Sample:
Population: Entire group of interest.
Sample: Subset used for research.
Parameters vs. Statistics:
Parameter: Numerical characteristic of a population.
Statistic: Estimate derived from a sample.
Sampling Error & Variability:
Differences between population parameters and sample statistics.
Normal Distribution Characteristics:
Symmetrical, bell-shaped curve where most values cluster around the mean.
Types of Measurement Scales:
Nominal: Categories (e.g., eye color, gender).
Ordinal: Ordered categories without equal intervals (e.g., ranking in a race).
Interval: Ordered values with equal spacing but no true zero (e.g., IQ scores, Celsius temperature).
Ratio: Interval scale with a meaningful zero point (e.g., height, reaction time).
Measures of Central Tendency:
Mean: Arithmetic average, best for normally distributed data.
Median: Middle value, best for skewed distributions.
Mode: Most frequently occurring value.
Measures of Dispersion:
Variance and Standard Deviation: Indicate data spread around the mean.
Correlations vs. Experiments:
Correlations: Measure relationships without causation (e.g., height and weight).
Experiments: Manipulate variables to establish cause-effect relationships.
Common Statistical Tests:
Chi-Square Test: Analyzes categorical data.
T-Test: Compares two means for significant differences.
ANOVA (F-Test): Compares multiple groups.
Pearson’s Correlation Coefficient (r):
Measures strength/direction of linear relationships (-1 to +1).
Regression Analysis:
Predicting dependent variables based on independent variables.
Review Lecture Slides & Notes: Focus on key definitions and concepts.
Practice with Quizzes: Look at past questions to understand question format.
Create Flashcards: Memorize key terms and concepts.
Explain Concepts to a Friend: Teaching reinforces understanding.
Take Timed Practice Tests: Simulate the exam environment.
Good luck with your midterm! 🎯📚