Psych 105 study guide

The Truth About Truth

1. How and why is our perception of reality a personal thing?  

   - Perception is influenced by individual experiences, beliefs, and emotions. Our brain interprets sensory information subjectively, and personal factors like culture, upbringing, and mood shape how we see and understand reality.

2. What are the goals of our personal belief system?  

   - To provide a framework for understanding the world, make sense of experiences, reduce uncertainty, and guide decision-making and behavior.

3. Why are personal beliefs sometimes wrong?  

   - They can be influenced by misinformation, cognitive biases, limited experiences, and emotional reasoning, leading to errors in judgment or faulty conclusions.

4. Examples of how emotion and biases affect thinking:  

   - Emotion: Fear may lead to overestimating risks (e.g., fear of flying).  

   - Biases: Confirmation bias causes people to focus on information that supports their existing beliefs while ignoring contradictory evidence.

5. What are the goals of science?  

   - To systematically uncover truths about the natural world through observation, experimentation, and evidence, and to minimize subjective biases.

6. What is the "human problem," and how does science rise above it?  

   - The "human problem" refers to our tendency toward subjective and biased thinking. Science overcomes this by using empirical evidence, standardized methods, and peer review.

7. What makes up the scientific attitude?  

   - Curiosity, skepticism, humility, and openness to new evidence while maintaining rigorous standards of testing and inquiry.

8. What is empirical testing? Why is it important?  

   - Empirical testing relies on observation and experimentation to collect measurable data. It's important because it provides objective evidence rather than relying on subjective opinion.

9. What is systematic testing? Why is it important?  

   - Systematic testing involves structured and repeatable methods to evaluate hypotheses. It’s important for ensuring reliability and validity in results.

10. What is objective evidence? Why is it important?  

   - Objective evidence is unbiased data that is observable and measurable. It’s crucial for making reliable conclusions and avoiding personal bias.

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### Breaking Through the Breakthrough Myth

1. What is the scientific breakthrough myth?  

   - The belief that science progresses through sudden, groundbreaking discoveries rather than gradual accumulation of knowledge.

2. What fills the gap from scientific goals to benefits?  

   - Incremental research, replication, and rigorous testing bridge the gap, leading to advancements in understanding and technology.

3. What are scientific hypotheses?  

   - Testable predictions derived from theories that explain a phenomenon or relationship.

4. What is a scientific theory?  

   - A well-substantiated explanation of a natural phenomenon based on evidence, experimentation, and repeated testing.

5. What is the principle of connectivity?  

   - Scientific ideas must build on or align with established knowledge, connecting new findings to existing research.

6. What is the principle of falsifiability? Why are more specific ideas valuable?  

   - Falsifiability means a hypothesis must be testable and potentially proven wrong. Specific ideas are more valuable because they provide clear criteria for testing, improving precision. This does not limit science but strengthens its reliability.

7. What is the principle of convergence?  

   - Multiple lines of evidence from independent studies should lead to the same conclusion, increasing confidence in findings.

8. Is diverging evidence valuable? Explain.  

   - Yes, it challenges existing theories and can lead to refining, revising, or even disproving ideas, driving scientific progress.

9. What is the principle of public verification? Why is it important?  

   - Findings must be shared and replicable by others. It ensures transparency, reliability, and credibility in science.

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### Constructing Psychology

1. What are constructs?  

   - Abstract concepts like intelligence, motivation, or stress that cannot be directly observed but are studied through measurable variables.

2. Difference between independent and dependent variables:  

   - Independent variable: The factor manipulated in an experiment.  

   - Dependent variable: The outcome measured in response to the manipulation.

3. What is the "construct problem,” and how do we solve it?  

   - Constructs are abstract and difficult to measure. We solve this by operationalizing them into specific, measurable terms.

4. What are operational definitions?  

   - Clear, precise ways of defining and measuring constructs in research.

5. Four common ways psychologists operationalize constructs:  

   - Observations, self-reports, standardized tests, and physiological measures.

6. Advantages and limitations of using observations:  

   - Advantages: Provide direct, real-world data.  

   - Limitations: Subject to observer bias and can lack objectivity.

7. Examples of self-report methods:  

   - Surveys, interviews, questionnaires, and diaries.

8. Concerns with testimonial evidence:  

   - Can be biased, unreliable, and influenced by memory errors or exaggeration.

9. Advantages of using self-report:  

   - Easy to collect, cost-effective, and can provide insights into thoughts and feelings.

10. Limitations of self-report methods:  

    - Prone to social desirability bias and inaccuracies in self-perception.

11. Two types of aptitude/abilities tests:  

    - Intelligence tests and skill-based assessments.

12. Usefulness and limitations of aptitude/abilities tests:  

    - Helpful for identifying strengths and weaknesses but can be culturally biased.

13. Physiological measures' usefulness and limitations:  

    - Useful for measuring biological responses (e.g., heart rate, brain activity). Limitations include high cost and potential invasiveness.

14. Benefits of using multiple approaches:  

    - Provides a comprehensive understanding of constructs, reduces bias, and improves reliability.

15. What is reliability? Validity?  

    - Reliability: Consistency of results.  

    - Validity: Accuracy of what the test or method measures.

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### Signs of a Strong Relationship

1. Information from observation, self-report, aptitude tests, and physiological measures:  

   - They provide qualitative, quantitative, and objective data to study behavior and mental processes.

2. What does correlation tell us?  

   - The strength and direction of the relationship between two variables.

3. Criteria for causation:  

   - Presence, precedence, and strength of the relationship.

4. Presence, precedence, strength of relationship:  

   - Presence: Variables are related.  

   - Precedence: Cause comes before the effect.  

   - Strength: Strong correlation or consistent evidence supports the relationship.

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### Together to Support a Cause

1. Why do we need experiments?  

   - To establish causation by controlling variables and testing hypotheses.

2. Why do experiments require controlled conditions?  

   - To minimize confounding variables and ensure the accuracy of results.

3. Independent vs. dependent variable:  

   - Independent: Manipulated factor.  

   - Dependent: Outcome measured.

4. What is compared in a between-participants design? Why?  

   - Different groups are compared to isolate the effect of the independent variable.

5. Control group vs. experimental group:  

   - Control: No intervention. Experimental: Receives the intervention.

6. What is compared in a within-participants design?  

   - The same participants are compared under different conditions.

7. What is internal validity?  

   - The extent to which an experiment establishes a cause-and-effect relationship.

8. What is external validity?  

   - The extent to which findings generalize to real-world settings.

9. What are confounding factors? Example:  

   - Variables that interfere with results (e.g., differences in participants' prior knowledge).

10. How to combat confounding factors:  

    - Random assignment ensures equal distribution of participant characteristics.

11. Why are participants’ motivations a concern?  

    - Can lead to biased responses or behaviors.

12. Participants’ expectations and the placebo effect:  

    - Expectations can influence outcomes. The placebo effect occurs when results arise from belief, not treatment.

13. Do researchers' expectations matter? Explain:  

    - Yes, they can unintentionally influence outcomes (e.g., experimenter bias).

14. What is generalizability?  

    - The ability to apply findings to other populations or settings.

15. What limits generalizability?  

    - Sample size, diversity, and experimental conditions.

16. Random selection vs. random assignment:  

    - Random selection: Choosing participants. Random assignment: Allocating participants to groups.

17. Why is converging evidence important?  

    - It increases confidence in findings by confirming results across multiple studies.  

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This guide covers your questions in detail—feel free to ask for clarifications!