Cogs 14a midterm 2 study guide

COGS 14A - Midterm 2 Study Guide

General Exam Information

• 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.

Key Topics from Lectures

Lecture 9: The Research Process and Methods

• 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.

Lecture 10: Measurement Methods in Cognitive Science

• 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.

Lecture 11: Ethics in Research

• 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.

Lecture 13: Literature Searches, Measurement, and Statistics

• 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.

Lecture 14: The Role of Statistics in Research

• 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.

Lecture 15: Measures for Comparing Groups

• 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.

Lecture 16: Correlations vs. Controlled Between-Group Designs

• 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.

Study Strategies

1. Review Lecture Slides & Notes: Focus on key definitions and concepts.

2. Practice with Quizzes: Look at past questions to understand question format.

3. Create Flashcards: Memorize key terms and concepts.

4. Explain Concepts to a Friend: Teaching reinforces understanding.

5. Take Timed Practice Tests: Simulate the exam environment.

Good luck with your midterm! 🎯📚