SAP Psychology Unit 0: Science Practices Study Guide

Psychological Perspectives

• Intro to Psychological Science:     * Definition: Psychology is categorized as a science, specifically a social science. It utilizes the scientific method to critically evaluate evidence.     * Study of Behaviors: Psychologists study observable behaviors, which include actions such as laughing and fidgeting.     * Study of Mental Processes: These are non-observable behaviors, including thinking, analysis, and decision-making.

Historical Context and Core Debates

• Wilhelm Wundt (German):     * Known as the Father of Psychology.     * $18802$: Created the first psychology lab to perform scientific experiments (Note: Transcript specifies $18802$).     * Contribution: He shifted the study of the brain from a purely philosophical perspective to a scientific one by adding scientific methodology to philosophy ($\text{Philosophy} + ext{Science} = ext{Psychology}$).

• Nature vs. Nurture:     * Nature: Focuses on genetic influence, genes, and inherited traits.     * Nurture: Focuses on environmental influence and external factors.

Modern Psychological Approaches

• Biological Psychology:     * Focuses on how genes affect behavior and mental processes.     * Views behavior as something inherited.     * Studies the physical brain to understand behavior.

• Cognitive Psychology:     * Studies mental processes (thinking).     * Investigates how we perceive, process, remember, think, and communicate.     * Central premise: How we think affects our behavior.     * Cognitive Neuroscience: A combination of the study of the mind (cognitive) and the study of the brain (neuroscience).

• Behavioral Psychology:     * Focuses on how the environment influences behavior and mental processes.     * Views behavior as something learned through the environment.     * Defines psychology as an objective science.

• Sociocultural Psychology:     * Studies how behavior and thinking are impacted by culture.     * Focuses on understanding how "unwritten rules" affect behavior.

• Humanistic Psychology:     * Studies how the drive for personal growth and self-actualization impacts behavior.     * Believes people strive to be their best and achieve highest potential.     * Recognizes the role of individual free will in changing one's life.

• Evolutionary Psychology:     * Studies behaviors that developed over generations.     * Based on Charles Darwin's theories; behavior is naturally selected for survival.

• Psychodynamic Psychology:     * Focuses on the unconscious mind and its effect on behavior.     * Questions: What is the mind hiding? What impact did childhood have on the current state?     * Based on the ideas of Sigmund Freud.

• Modern BioPsychoSocial Approach:     * Eclectic: Incorporates Biology, Psychology, and Social factors.     * Merges several modern approaches together.

Roadblocks to Critical Thinking

• Why Science is Necessary: Psychology applies critical thinking and scientific investigation to address flaws in human thinking.

• Common Flaws:     * Hindsight Bias: Defined as the tendency to think, after knowing an outcome, that one "knew it all along."         * Example: The suitcase with wheels; many people claimed they could have come up with that invention after seeing it.     * Overconfidence: The tendency to think we know more than we actually do.         * Example: Parents believing that kids eating sugar makes them hyperactive.     * Perceiving Order in Random Events: Humans naturally perceive patterns even where none exist.         * Gambler’s Fallacy: Believing that random happenings are more or less likely because of the frequency of past occurrences.

• Key Point: These three roadblocks—hindsight bias, overconfidence, and perceiving patterns—lead us to overestimate our intuition, necessitating the scientific method in psychology.

Non-Experimental Research Designs

• Types of Non-Experimental Research: Includes case studies, naturalistic observation, surveys, meta-analysis, and correlation analysis.

• Case Study:     * In-depth study of one individual or a small group to reveal universal principles in unique circumstances.     * Example Topic: Studying the Amygdala, which controls rage and fear.     * Strengths: Allows examination of unusual behavior; provides large amounts of qualitative data.     * Limitations: Results may not be generalizable to the larger population; cannot determine cause-and-effect relationships.     * Data Types:         * Qualitative Data: Non-numerical info (interviews, lab notes, diaries, photos).         * Quantitative Data: Numerical data that can be counted, measured, or assigned value.

• Naturalistic Observation:     * Observing and recording behavior in naturally occurring situations without manipulation.     * Examples: Observing risk-taking differences between genders or triggers for laughter in social situations.     * Strengths: Subjects behave normally outside lab settings.     * Limitations: Researcher observations may be subjective; cannot determine cause-and-effect.     * The Hawthorne Effect: When individuals modify behavior because they know they are being observed.

• Survey:     * A technique for obtaining self-reported attitudes or behaviors via a representative random sample.     * Example: Identifying that $68\%$ of people say religion is important to them.     * Strengths: Quick way to gather info on beliefs/behaviors; can include many cases.     * Limitations: Wording/expectation effects, difficulty in random sampling, no cause-and-effect determination.

• Detailed Survey Limitations:     * Response Bias: Tendency for participants to respond inaccurately or falsely.     * Wording Effect: The phrasing of questions significantly affects responses.     * Expectation Effect: Behaviors or answers change due to personal expectations or those of the interviewer (e.g., rating the quality of SJA teachers).     * Social Desirability Bias: Answering questions to look good to others; leads to over-reporting desirable behaviors and under-reporting undesirable ones.

• Sampling in Surveys:     * Population: The entire group being studied.     * Random Sample: Every population member has an EQUAL chance of selection. Larger samples are better if representative.     * Convivence Sampling: (Per transcript spelling) Non-probability sampling focusing on easy-to-access participants. Example: Surveying your class instead of the whole school.         * Pros: Quick, low cost, easy.         * Cons: Sampling/selection bias, unable to generalize, low validity.     * Representative Samples: Accurately reflects the whole population. Assumed accurate if randomly selected and matches demographic distributions (e.g., matching a school's ethnic breakdown of $25\%$ Hispanic, $30\%$ Asian, $35\%$ African American, and $10\%$ Caucasian).     * Sampling Bias: Flawed process producing an unrepresentative sample.

• Meta-Analysis:     * Statistical technique combining results of multiple studies on the same question.     * Advantages: Improved precision, answers new questions, settles controversies from conflicting claims.     * Example: Combining $8$ studies ($860$ people total) to analyze the relationship between sunscreen and melanoma.

Correlation Studies

• Definition: Measures how two variables change together and predict each other. Correlation DOES NOT equal causation.

• Positive Correlation: Variables move in the same direction. As one goes up, the other goes up (e.g., height and weight).

• Negative Correlation (Inverse): Variables move in opposite directions. As one goes up, the other goes down (e.g., social media time vs. grades; outdoor temperature vs. heater use).

• Correlation Coefficients ($r$):     * Statistical index from $-1$ to $1$.     * Examples provided: $r = +8$ or $r = -2$ (Transcript values used, though normally decimals).     * Impossible values: $r = +1.2$ or $r = -1.5$.     * $-1$ and $+1$ are the strongest correlations; $0$ means no correlation.     * Signs indicating direction, not quality.

• Scatterplots: Clusters of dots; slope suggests direction and scatter suggests strength.

• Variables: Factors that can change (age, gender, weight). Example: To-do lists and stress levels.

Experimental Research

• Experimentation: Manipulating factors (Independent Variables) to observe effects on behavior/mental processes (Dependent Variables).

• Scientific Method: Purpose, Research, Hypothesis, Experiment, Analysis, Conclusion.

• Theory vs. Hypothesis:     * Theory: Broad explanation of observations that predicts behaviors (e.g., sleep improves memory).     * Hypothesis: Testable, precise, specific prediction, often "if/then" (e.g., if sleep deprived, then people remember less).

• Falsifiable Hypothesis: Scientific only if it can be conceptually disproven by experimental observation.

• Operational Definitions: Carefully worded statements of exact procedures that are concrete and measurable. Essential for Replication (repeating an experiment to confirm findings).

• Groups and Assignment:     * Experimental Group: Receives treatment.     * Control Group: Does not receive treatment.     * Random Assignment: Assigning participants by chance to minimize group differences and confounding variables. Note: Different from random sampling.

• Blinding Procedures:     * Double-Blind: Neither participants nor researchers know who received treatment vs. placebo.     * Single-Blind: Only participants are unaware.

• Placebo Effect: Results caused by expectations alone; caused by an inert substance (e.g., a sugar pill).

• Specific Variables:     * Independent Variable (IV): Manipulated factor; only given to experimental group.     * Dependent Variable (DV): Measured outcome that changes based on IV manipulation; studied in both groups.     * Confounding Variables: Unaccounted third variables that influence results and affect validity. (e.g., AC sales and drowning rates; heat is the confounding variable).

• Validity and Reliability: Validity means truthfulness; Reliability means consistency.

• Peer Review: Evaluation of theory, originality, and accuracy by experts before publication in scientific journals.

Ethics in Research

• Ethical Procedures:     1. Informed Consent: Participants must know everything that will happen and agree to it.     2. Protection from Harm: No emotional, physical, or psychological hurt.     3. Confidentiality/Anonymity: Keeping participant identities private.     4. Free from Deception: Cannot lie about study aspects.     5. Debriefing: Explaining findings to subjects after completion.     6. Right to Withdraw: Subjects can leave at any time.     7. No Coercion: Participants must be volunteers.

• Institutional Review Board (IRB): Must review and approve all study proposals before research begins.

Science Practice 3: Data Interpretation

• Descriptive Statistics: Numerical data used to measure/describe group characteristics, often shown in histograms.

• Measures of Central Tendency:     1. Mean: Average score. Sum of scores divided by number of scores. Best for evenly distributed data without outliers. (Example: $7, 9, 15, 21, 13, 6 = 14.5$).     2. Median: Middle score ($50^{th}$ percentile). Better for skewed data. (Example for odd set: $2, 4, 5, 7, 8$ is $5$; for even set: add two middle and divide by $2$).     3. Mode: Most frequent score. Can be single, bimodal, or multimodal. Useful for categorical data.

• Skewed Distributions: When extreme scores throw off central tendency (mostly mean).     * Positive Skew: One score is much higher; tail pulled to the right; pulls Mean to the higher end.     * Negative Skew: One score is much lower; tail pulled to the left; pulls Mean to the lower end.

• Measures of Variation:     1. Range: Difference between highest and lowest ($Highest - Lowest$). Example: $10 - 1 = 9$.     2. Standard Deviation: Measures how much scores vary around the mean.         * Normal Curve (Bell Curve): $68\%$ of scores fall near the average.         * Low SD: Consistency; numbers are close to the average (e.g., $SD = 1$).         * High SD: Variation; numbers are spread out (e.g., $SD = 4$). Smaller SD means results are less likely due to chance.

• Percentile Rank: Percentage of scores lower than a specific score. ($95^{th}$ percentile means doing better than $95\%$ of others).

• Statistical Significance ($p$-value):     * Likelihood that results occurred by chance.     * Threshold: Chance must be no more than $5\%$ ($p \le 0.05$).     * $p \le 0.05$ means it is $95\%$ likely results did NOT occur by chance. Researchers want $p$ closest to zero.

• Generalization: Results can be generalized if: the sample is representative, data is statistically significant, and results are replicable.