AP PSYCH UNIT 1

Psychological Perspectives:

  1. Biological: Focuses on how biology influences behavior (e.g., brain, neurotransmitters).

  2. Evolutionary: Looks at how evolution and natural selection shape behavior.

  3. Psychodynamic/Psychoanalytic: Emphasizes unconscious drives and early experiences (Freud’s theories).

  4. Behavioral: Studies observable behavior and its causes (classical/operant conditioning).

  5. Humanistic: Focuses on free will, self-actualization, and human potential (Maslow, Rogers).

  6. Cognitive: Examines mental processes like memory, thinking, and problem-solving.

  7. Social-Cultural: Looks at how society and culture affect behavior.

Cognitive Biases:

  1. Confirmation Bias: Tendency to search for information that confirms one's beliefs.

  2. Hindsight Bias: Believing after an event that you "knew it all along."

  3. Overconfidence: Being more confident than correct in judgments.

Research Methods and Design:

  1. Experimental Method: Used to explore cause and effect by manipulating variables.

    • Independent Variable (IV): The variable that is manipulated.

    • Dependent Variable (DV): The variable that is measured.

    • Confounding Variable: A variable that could i44nterfere with results.

    • Random Assignment: Randomly placing participants into control/experimental groups to reduce bias.

    • Experimental Group: Receives the treatment.

    • Control Group: Does not receive the treatment (used for comparison).

  2. Deception: Used to ensure the study's integrity without revealing too much to participants.

  3. Placebo Effect: When participants show improvement simply because they believe they are receiving treatment.

    • Single Blind: Participants don’t know which group they’re in.

    • Double Blind: Neither participants nor researchers know who is in which group.

Non-experimental Methods:

  1. Correlation: Measures the relationship between two variables.

    • Positive Correlation: Both variables increase together (+1).

    • Negative Correlation: One variable increases, the other decreases (-1).

    • No Correlation: No relationship between variables (0).

    • Illusory Correlation: Perceiving a relationship that doesn't exist.

    • Correlation ≠ Causation: Just because two things are related, doesn’t mean one causes the other.

  2. Case Study: An in-depth analysis of an individual or group.

  3. Naturalistic Observation: Observing behavior in its natural setting.

  4. Meta-Analysis: Combining results from multiple studies.

Sampling:

  1. Sample: A subset of the population being studied.

  2. Population: The entire group of people you're interested in studying.

  3. Representative Sample: A sample that accurately reflects the population.

  4. Random Sample: Everyone in the population has an equal chance of being selected.

  5. Convenience Sampling: Selecting people who are easy to access.

  6. Sampling Bias: Occurs when the sample is not representative.

  7. Generalizability: The extent to which study results apply to the population.

Ethics:

  1. IRB: Oversees research to ensure ethical guidelines are followed.

  2. Informed Consent: Participants must agree to the study knowing all the risks.

  3. Informed Assent: Parental consent for minors in research.

  4. Protection from Harm: Ensuring participants are not harmed.

  5. Right to Withdraw: Participants can leave the study at any time.

  6. Confidentiality: Participants' information must remain private.

  7. Debriefing: Explaining the study's purpose to participants afterward.

Data Interpretation:

  1. Measures of Central Tendency:

    • Mean: The average score.

    • Median: The middle score in a set.

    • Mode: The most frequently occurring score.

  2. Measures of Variation:

    • Range: The difference between the highest and lowest scores.

    • Standard Deviation: How spread out the scores are.

    • Normal Curve: A bell-shaped curve representing data distribution.

      • 68-95-99.7 rule: Percentage of data falling within 1, 2, and 3 standard deviations from the mean.

  3. Skewness:

    • Positive Skew: More low scores, tail on the right.

    • Negative Skew: More high scores, tail on the left.

    • Bimodal: Two peaks in the data set.

  4. Scatterplot: A graph that shows the relationship between two variables.

  5. Correlation Coefficient: A statistical measure of the strength and direction of a relationship between two variables.

Interpretation of Results:

  1. Statistical Significance: Indicates whether the results are due to chance.

  2. Effect Size: Measures the strength of the relationship between variables.

Essential Questions:

  • Psychological Approaches: Each approach explains behavior from different angles (e.g., biological focuses on the brain, cognitive on mental processes).

  • Experimental vs Non-experimental Methods: Experiments involve manipulating variables; non-experimental methods observe relationships without manipulation.

  • Independent vs Dependent Variables: IV is what you change, DV is what you measure.

  • Random Assignment Importance: Helps reduce bias and create equal groups.

  • Experimental vs Control Groups: Experimental gets treatment, control does not.

  • Deception and Placebo: Used to prevent bias or ensure genuine reactions.

  • Negative vs Positive Correlation: Positive = both increase, Negative = one increases, the other decreases.

  • Operational Definitions: Precise definitions that allow replication and understanding.

  • Generalizability: A study is generalizable if it applies to the broader population; limited by sampling bias.

  • Ethical Research: Ensures participants' rights and well-being are protected.

  • Mean, Median, Mode: Measures of central tendency for understanding data distribution.

  • Range and Standard Deviation: Help measure variability in data.

Statistical Significance: Indicates if results are likely not due to chance.