Final Exam Review - Psych 2910

Lecture 2: Knowledge Metaphysical Systems

• Supernatural Explanations: Attributes behavior to non-physical forces like spirits and deities.

  • Animism: Belief that natural phenomena are alive and influence behavior.

    • Example: Possessing an eagle’s feather grants certain properties to the owner.

  • Mythology and Religion: Non-physical forces affect human behavior, differing from scientific assumptions.

  • Astrology: Suggests that celestial bodies influence human behavior and predict actions.

Philosophical Systems

• Shift towards logic and empirical observation.

  • Empiricism (David Hume): Knowledge should be based on observations.

  • Positivism (Auguste Comte): Focus on knowledge derived solely from sense perceptions.

Methods of Acquiring Knowledge

• Intuition: Knowledge based on instinctive feeling rather than conscious reasoning.

  • Problem: Conclusions often drawn without sufficient evidence.

• Authority: Trusting figures of authority to provide information.

  • Problem: Questioning the authenticity of the authority.

• Scientific Skepticism: Withholding judgment and systematically evaluating claims helps consider all possibilities.

• Science: Requires adapting views based on new evidence.

Key Concepts

• Determinism: The universe operates in a systematic, orderly manner; events have meaningful causes.

  • Causation:

    • Covariation of Cause and Effect: Presence of cause corresponds with presence of effect.

    • Temporal Precedence: Cause must occur before the effect.

    • Elimination of Alternative Explanations: Ensuring no other variable influences the effect.

Goals of Scientific Psychology

• Objectives:

  • Describe behavior.

  • Predict behavior.

  • Determine causes of behavior.

  • Explain behavior.

Types of Research

• Basic Research: Addresses fundamental questions.

• Applied Research: Focuses on practical problems.

Four Keys of Research

1. Replication: Detailed description for duplicating studies and results.

2. Testability/Falsifiability: Rejecting untestable ideas.

3. Peer Review: Validating research to ensure study quality.

4. Adversarial Process: Evaluating opposing theories for experimental comparison.

Pseudoscience**: Characteristics include:

• Unfalsifiable hypotheses.

• Non-scientific methodology.

• Anecdotal evidence or reliance on authority.

• Lack of peer-reviewed citations and revisions based on new data.

• Ignoring conflicting evidence.

Specific Concepts in Pseudoscience

• Biorhythms: Claiming human behavior follows physical, emotional, and intellectual cycles of specific durations.

• Homeopathy: Substance that induces symptoms in healthy individuals cures similar symptoms in patients.

• Phrenology: Inferring personality traits based on skull bumps.

Critical Evaluation

• Assess data source for credibility.

• Evaluate methods of study conduct.

• Analyze statistical methods used.

• Review conclusions drawn from analysis.

Lecture 3: Intro to Statistics

• Why Statistics?: Trust issues due to biases; control of extraneous variables; direct study limitations necessitating statistical methods.

• Statistics Defined: Method of understanding data, aiding in decision-making.

Types of Statistics**:

• Descriptive Statistics: Numbers summarizing data (mean, median, standard deviation).

• Inferential Statistics: Making predictions about a population from sample data.

Theoretical Frameworks

• Theory: General statements on relationships among variables, providing organizational frameworks and generating new knowledge.

Key Questions in Research

• Sample characteristics, reasons for participation, controls, sample size, wording, causation, funding sources, and peer-reviewed publication.

Key Terms in Research Methodology

• Population: Entire group of interest.

• Sample: Subset of the population tested.

• Independent Variable (IV): Manipulated variable.

• Dependent Variable (DV): Measured outcome.

• Construct: Internal attribute not directly observable.

• Operational Definition: Specifies procedures to represent a construct, e.g., measuring hunger.

Lecture 4: Measurement Scales

• Variable Types:

  • Discrete Variable: Indivisible categories (e.g., number of children).

  • Continuous Variable: Measurable characteristics (e.g., height, weight).

  • Dichotomous Variable: Only two possible outcomes.

Measurement Scales

1. Nominal Scale: Categorizes data without implying order. Frequency calculations only; no intermediate values.

2. Ordinal Scale: Includes order but does not quantify the gap between points.

3. Interval Scale: Provides numeric intervals but lacks a true zero point; zero is arbitrary (e.g., temperature).

4. Ratio Scale: Has all properties of interval scales but includes an absolute zero.

Lecture 5: Central Tendency

• Mean: Average score; influenced by extremes but computationally simple.

• Mode: Most common score in a dataset; relevant for nominal scales.

• Median: Middle value dividing data into halves; especially useful in skewed distributions.

Lecture 6: Variability

• Variability Defined: Quantifies how spread out the scores are within a distribution.

• Range: Difference between highest and lowest scores; influenced by extremes.

• Interquartile Range: Range of middle 50% of data, calculated as Q3-Q1.

• Standard Deviation: Average distance from the mean, widely used measure of variability.

Lecture 7: Ethics in Research**

• Key Ethical Organizations: CIHR, NSERC, SSHRC.

• Concerns: Protecting subjects from risks, informed consent, and ethical conduct in experiments.

• Experiments During WWII: Resulted in establishing ethical guidelines (Nuremberg Code, Helsinki Declaration, Belmont Report).

• Milgram Study Insights: Experiment demonstrating obedience—65% of subjects administered maximum shocks when instructed.

Core Ethical Principles**:

1. Respect for Persons: Ensuring voluntary participation.

2. Concern for Welfare: Balancing risks against potential benefits.

3. Justice: Fair treatment of participants.

Risk vs. Benefit Analysis**

• Consider psychological, physical, and privacy-related risks while weighing the benefits to society.

Informed Consent**

• Required prior to participation; ensuring participants are fully briefed.

Vulnerable Populations**: Special considerations should include children, prisoners, and individuals lacking capacity to consent.

Lecture 8: Percentiles**

• Definition: Percentiles indicate the position of a score within a distribution.

Lecture 9: Standard Scores (z-scores)

• Purpose of z-scores: Standardize scores by indicating how many standard deviations they are from the mean.

Lecture 10: Sampling

• Good Sample Characteristics: Representative and sufficiently large to minimize errors.

• Central Limit Theorem (CLT): As sample size increases, the distribution of sample means approaches normality.

Expected Value**: The mean of a distribution of sample means equals the population mean.

Lecture 11: Inferential Statistics**

• Distinction between descriptive (summarizes data) and inferential statistics (draws conclusions about populations).

Testing Hypotheses**: Impact of hypotheses on interpreting results; understanding p-values as indicators of statistical significance.

Lecture 12: t-tests**

• Differences between z-tests and t-tests based on population standard deviation availability.

Lecture 13: Independent vs. Dependent Groups**

• Clarification of designs: Independent samples versus dependent samples in testing means.

Lecture 14: Correlation**

• Importance of understanding correlation and causation; types of correlations analyzed.

Lecture 15: Probability**

• Primary concepts include analytical probability, mutual exclusivity, and addition/multiplication rules.

Lecture 16: Research Design**

• Types of Studies: Differentiating experimental from non-experimental designs.

Lecture 17: Measurement**

• Discussing reliability, validity, and various types of reliability and validity tests.

Lecture 18: Observation**

• Overview of observational methods including naturalistic and systematic observation, as well as concerns inherent in qualitative research.