Experimental Design and Cognitive Practices Vocabulary

🧠 PSYCHOLOGY — CHAPTER 1 MASTER NOTES

Thinking Critically With Psychological Science

Modules 1–3 | Myers, DeWall & Gruber, 14th Edition

These are the Master Notes version: the goal is completeness first. I am combining the textbook material you provided with the professor's slides and keeping definitions, examples, distinctions, repeated concepts, and test/retrieval material instead of reducing Chapter 1 to a short summary.

MODULE 1 — THE HISTORY AND SCOPE OF PSYCHOLOGY

1. What Is Psychology?

📌 Psychology = the scientific study of mind and behaviour.

The word comes from Greek:

• psyche = soul/mind

• logia = study

People naturally try to understand why others behave the way they do using common sense, personal experience, and intuition. In that sense, people often act as “intuitive psychologists.” However, psychology goes beyond intuition by systematically collecting and evaluating evidence.

🧠 KEY IDEA

The important word in the modern definition of psychology is science.

Psychology today is the science of behaviour and mental processes, and contemporary psychology considers cognition, biology and experience, culture and gender, and human flourishing.

2. Psychology as a Science

Psychological science involves a passion for exploring and understanding without misleading others or being misled ourselves.

A scientific attitude requires us to be:

• Skeptical, but not cynical

• Open-minded, but not gullible

• Willing to admit that our own beliefs could be wrong

📌 Humility = awareness that we are vulnerable to error combined with an openness to new perspectives.

The three parts of the scientific attitude

Curiosity + Skepticism + Humility → smarter thinking

Critical Thinking

📌 Critical thinking involves thinking intelligently about information rather than simply accepting it.

Critical thinkers:

• Examine assumptions.

• Appraise/evaluate the source.

• Look for hidden biases.

• Evaluate evidence.

• Assess conclusions.

Scientific critical thinking helps us check our own biases.

3. The Birth of Psychological Science

Psychology developed from earlier questions in philosophy and biology.

The historical material in the slides includes figures such as:

• Plato

• Aristotle

• Thomas Hobbes

• René Descartes

• John Locke

• Jean-Jacques Rousseau

• Gustav Fechner

• Charles Darwin

• Wilhelm Wundt

• William James

• Ivan Pavlov

• Hermann Ebbinghaus

• Sigmund Freud

• Edward Bradford Titchener

• John B. Watson

• Sir Frederic Bartlett

• Jean Piaget

• B. F. Skinner

• Donald Broadbent

These thinkers contributed to questions about the mind, learning, memory, development, behaviour, consciousness, and the relationship between biology and experience.

4. Structuralism

Wilhelm Wundt

Wilhelm Wundt is identified in the slides as the “father of psychology.”

In 1879, he established the world's first experimental psychology laboratory at the University of Leipzig.

This helped establish psychology as an experimental scientific discipline.

Edward Titchener

Wundt's student Edward Titchener developed the approach associated with structuralism.

Structuralism attempted to identify the basic “structures” or elements of psychological experience.

Introspection

📌 Introspection = looking inward/self-reflection.

Participants were trained to report the elements of their conscious experience.

Professor's example: Participants might look at or smell a rose and then carefully describe their internal experience.

Why did structuralism/introspection fail?

The slides specifically give several problems:

1. Introspection required people who were smart and verbally capable.

2. Results were unreliable, varying from person to person and experience to experience.

3. People often do not actually know why they feel what they feel or do what they do.

4. People's recollections are frequently erroneous/inaccurate.

🎯 EXAM CONNECTION

Structuralism → structure/components of consciousness → introspection → Wundt/Titchener.

5. Functionalism

William James

William James (1842–1910) established a psychology laboratory at Harvard.

Rather than asking primarily what consciousness is made of, functionalism asked:

What does the mind do, and how does it help us function?

James studied how mental and behavioural processes allow organisms to:

• adapt

• survive

• flourish

He also used introspection to study the stream of consciousness and emotion.

Influence of Charles Darwin

James was influenced by Charles Darwin's evolutionary theory.

James believed thinking, like smelling, developed because it was adaptive—it helped our ancestors survive.

⚠ DON'T CONFUSE

Structuralism:
“What are the components/structures of conscious experience?”

Functionalism:
“What are mental processes FOR? How do they help us adapt and survive?”

6. Psychology's First Women

Mary Whiton Calkins

William James admitted Mary Calkins to his Harvard graduate seminar despite objections.

Calkins became:

• An important memory researcher

• The first female president of the APA

James admitted her into his graduate seminar in 1890; the slides identify her APA presidency year as 1905.

Margaret Floy Washburn

Margaret Floy Washburn:

• Wrote the influential book The Animal Mind

• Was the first woman to receive a psychology PhD

• Became the second female APA president.

Increasing diversity

The professor's slides note:

• From 1988–2025, more than half of the elected presidents of the Association for Psychological Science were women.

• Women now earn most psychology doctorates in the United States, Canada, and Europe.

7. Behaviorism

📌 Behaviorism argued that psychology:

1. Should be an objective science, and

2. Should study behaviour without reference to inner mental processes.

Instead of trying to examine invisible consciousness through introspection, behaviourists focused on observable behaviour.

John B. Watson & Rosalie Rayner

Watson and Rayner are associated with the scientific study of behaviour and the famous Little Albert experiment involving learned fear.

Ivan Pavlov

/

Pavlov's work strongly influenced behaviourism.

/

His dogs learned to salivate to a tone after that tone had previously been associated with food.

This demonstrated how behaviour can be learned through conditioning.

B. F. Skinner

Skinner became a leading behaviourist.

He:

• Rejected introspection.

• Studied observable behaviour.

• Studied how consequences shape behaviour.

• Emphasized reinforcement and punishment.

Behaviorism remained highly influential well into the 1960s.

🧠 MEMORY CONNECTION

Watson/Rayner → learned fear/Little Albert
Pavlov → conditioning/dogs
Skinner → consequences, reinforcement & punishment

8. Freudian / Psychoanalytic Psychology

Sigmund Freud

📌 Psychoanalytic psychology emphasizes how our unconscious mind and childhood experiences affect behaviour.

Freud focused on:

• Unconscious sexual conflicts

• Childhood experiences

• The mind's defences against its own wishes and impulses

His methods included:

• Talk therapy

• Dream analysis

• Free association

Freudian psychology is associated with psychoanalysis.

Freud's Theory of Personality

Freud divided personality into:

• Id

• Ego

• Superego

Freud's Theory of Development

His psychosexual stages were:

Oral → Anal → Phallic → Latency → Genital

The professor's slides explicitly note that many Freudian ideas are controversial today.

9. Humanistic Psychology

Behaviorists and Freud dominated much of psychology, but Carl Rogers and Abraham Maslow considered both approaches too limiting.

📌 Humanistic psychology emphasizes:

• Human growth potential

• Need for love and acceptance

• Environments that nurture or limit personal growth

Humanistic psychologists viewed humans as inherently good and driven by a desire for growth or self-actualization.

Abraham Maslow

Associated with:

• Hierarchy of Needs

• Self-actualization

Carl Rogers

Associated with the person-centered approach.

Rogers argued that growth is facilitated through:

1. Genuineness

2. Empathy

3. Unconditional positive regard

⚠ DON'T CONFUSE THE BIG THREE

Behaviorism: observable learned behaviour
Freud/Psychodynamic: unconscious conflicts + childhood
Humanistic: growth, potential, acceptance, self-actualization

10. The Cognitive Revolution

The dominance of strict behaviourism eventually weakened as psychologists again became interested in internal mental processes.

The slides identify Noam Chomsky as a primary instigator of the Cognitive Revolution in the late 1950s and 1960s.

The shift challenged behaviorism by treating the mind as an active system involving innate structures and internal mental states.

Cognitive Psychology

Focuses on mental processes such as:

• Thinking

• Knowing

• Remembering

• Processing information

Cognitive Neuroscience

Combines cognitive psychology with study of the brain.

11. Nature–Nurture

One of psychology's enduring questions concerns the relative contribution of:

Nature → biology/genes

versus

Nurture → environment/experience

Contemporary psychology does not simply choose one side.

Behaviour and mental processes generally emerge from interactions between biology and experience.

12. Evolutionary Psychology vs. Behavior Genetics

Modern psychologists study both shared human characteristics and individual differences.

Evolutionary Psychology

Focus:

How are humans alike because of our shared biology?

It examines how natural selection may have shaped behavioural tendencies.

Behavior Genetics

Focus:

Why do humans differ because of different genes and environments?

It studies how genes and environment contribute to individual differences.

Natural Selection

Traits that increase survival and reproductive success can become more common across generations.

🎯 DON'T CONFUSE

Evolutionary psychology → similarities/shared biology

Behavior genetics → individual differences/genes + environments

13. Culture and Gender

📌 Culture involves shared ideas and behaviours passed from one generation to the next.

Culture can shape people in many ways, so psychologists study people from different societies to determine:

• What varies across cultures

• What psychological processes may be broadly shared

A major concern is that much psychological research has historically involved WEIRD populations:

Western
Educated
Industrial
Rich
Democratic

Research based primarily on WEIRD populations may not automatically describe all humans.

14. Positive Psychology

Contemporary psychology also examines human flourishing rather than studying only disorders and problems.

Positive psychology, associated with Martin Seligman, studies positive emotions, strengths, resilience, well-being, and factors that help people and communities flourish.

15. Levels of Analysis & the Biopsychosocial Approach

Behaviour can be examined at different levels.

No single level provides a complete explanation.

The major levels can be organized as:

Biological

Genes, brain, nervous system, hormones, evolution.

Psychological

Thoughts, emotions, learning, perceptions, memories.

Social-cultural

Relationships, social environments, culture, expectations.

📌 Biopsychosocial approach = integrates biological + psychological + social-cultural factors.

🧠 KEY IDEA

A person's behaviour rarely has only one explanation.

Different levels can simultaneously contribute to the same behaviour or mental process.

16. Psychology's Major Theoretical Perspectives

The professor's table identifies seven major perspectives.

Examples of the questions each asks

Neuroscience: How does a pain message travel from the hand to the brain?

Evolutionary: How does evolution influence behavioural tendencies?

Behavior genetics: How much of a trait reflects genes versus environment?

Psychodynamic: Can behaviour be understood through unconscious wishes, conflicts, or childhood experiences?

Behavioral: How did someone learn a fear? How can behaviour be changed?

Cognitive: How do people remember, reason, and solve problems?

Social-cultural: How are behaviour and thinking influenced by other people and culture?

17. Psychology's Subfields

Psychology contains many subfields, but they share an interest in describing and explaining behaviour and the mind underlying it.

Basic Research

Primarily expands knowledge.

Examples listed in the slides:

• Biological psychology

• Developmental psychology

• Cognitive psychology

• Personality psychology

• Social psychology

Applied Research / Applied Psychology

Uses psychological knowledge to solve practical problems.

Examples:

• Industrial-organizational psychology

• Counseling psychology

• Clinical psychology

• Community psychology

18. How to Study Psychology Effectively

The Module 1 material emphasizes principles such as:

Testing Effect

Repeatedly retrieving information strengthens memory more effectively than simply rereading it.

Distributed Practice

Spread studying across time instead of cramming everything into one session.

Active Processing

Actively engage with information—retrieve it, explain it, connect it, and apply it.

Overlearning

Continuing to practice material after you initially know it can strengthen retention.

🎯 This means these Master Notes should not only be reread. Eventually, the material should be converted into active-recall questions/Quizlet, which is our next stage.

🔬 MODULE 2 — RESEARCH STRATEGIES

How Psychologists Ask and Answer Questions

19. Why Do We Need Psychological Science?

Humans cannot rely exclusively on intuition and common sense.

Three major problems are:

1. Hindsight bias

2. Overconfidence

3. Perceiving patterns in random events

20. Hindsight Bias

📌 Hindsight bias = after learning an outcome, believing we would have predicted it beforehand.

AKA:

“I knew it all along.”

Professor's Super Bowl example

Before the 2025 Super Bowl, the Kansas City Chiefs and Philadelphia Eagles were expected to have a close game, with the Chiefs predicted on the slide to edge out a victory.

After the Chiefs lost badly, fans/commentators could explain why the result had been “obvious,” as though they had known beforehand.

That's hindsight bias.

21. Overconfidence

📌 Overconfidence = tendency to be more confident in our knowledge/judgments than accuracy warrants.

The professor uses scrambled words to demonstrate this.

Examples include:

WREAT → WATER
ETRYN → ENTRY
GRABE → BARGE

Then students estimate how long they would have taken to solve them.

Once the solution is visible, solving the problem seems easier than it actually would have been.

22. Perceiving Patterns in Random Events

Humans naturally search for meaning.

Professor examples:

• “Synchronicity”

• “Angel numbers”

• “Signs from the universe”

But genuine random sequences contain patterns and streaks more frequently than people intuitively expect.

Randomness does not mean every possible outcome will appear perfectly evenly in a short sequence.

23. Misinformation and Disinformation

The slides distinguish misleading information generally from intentionally false disinformation.

Misinformation can:

• Make people fear the wrong things

• Kill

• Rationalize war

• Fuel conspiracy theories

Why are people vulnerable to misinformation?

The professor lists:

• Fake news spreads quickly.

• Humans have a natural tendency to believe what others tell them.

• Repetition breeds belief.

• Vivid examples remain mentally available.

• People are motivated to confirm existing beliefs.

• Echo chambers can polarize opinions.

24. Debunking Misinformation

Incoming information can be filtered using critical thinking and a scientific mindset.

Stephan Lewandowsky and colleagues' four-step debunking method:

1. FACT

Lead with a clear, simple assertion.

2. MYTH

Acknowledge the false belief.

3. FALLACY

Explain why/how it is misinformation.

4. FACT

Restate the accurate information so the truth is what remains.

FACT → MYTH → FALLACY → FACT

25. Prebunking / Psychological Inoculation

Rather than correcting misinformation only after exposure, prebunking attempts to build resistance beforehand.

The slide's psychological-inoculation figure shows:

Warn about misinformation + provide evidence-based refutation

↓

Develop critical thinking and resistance to misinformation

↓

Improved individual immunity to misinformation

↓

Reduced community spread of misinformation

Think of it like a psychological vaccine against manipulation.

26. Combating Misinformation

The slides recommend:

• Embrace a scientific mindset.

• Become aware of personal biases.

• Discuss opposing views before dismissing them.

• Combine curiosity + skepticism + humility.

Notice that these are the same scientific-attitude qualities introduced in Module 1.

27. The Scientific Method

📌 Scientific method = a self-correcting process for evaluating ideas using observation and analysis.

If evidence supports predictions, the theory receives support.

If predictions repeatedly fail, the theory may need to be revised or rejected.

When research is submitted to scientific journals, peer reviewers evaluate aspects such as:

• Theory

• Originality

• Accuracy

28. Theory → Hypothesis → Test

Theory

📌 Theory = an explanation using an integrated set of principles that organizes observations and predicts behaviours/events.

A scientific theory is therefore not merely a guess.

Hypothesis

📌 Hypothesis = a testable prediction, often derived from a theory.

Operational Definition

📌 Operational definition = carefully worded statement describing the exact procedures/operations used in a research study.

This allows researchers to define exactly what they mean by variables such as “stress,” “aggression,” “memory,” etc.

Replication

📌 Replication = repeating the essence of a study, usually with different participants and in different situations, to determine whether the basic finding can be reproduced.

🧠 FLOW

Theory → Hypothesis → Operationalize variables → Test → Analyze → Replicate

29. Preregistration

📌 Preregistration involves researchers publicly specifying their research questions, hypotheses, methods, and/or analysis plans before examining the results.

This helps reduce the temptation to reshape hypotheses or analyses after seeing the data.

30. Meta-Analysis

📌 Meta-analysis statistically combines results from many studies to estimate an overall effect.

Instead of depending heavily on one study, researchers examine a larger body of evidence.

This connects directly with Module 3:

More estimates are generally better than fewer estimates.

31. Reliability vs. Validity

Reliability

Think:

Consistency

Would a measurement/study produce reasonably consistent results?

Validity

Think:

Accuracy

Does the method actually measure what it claims to measure?

⚠ Something can be reliable without being valid.

A measure can repeatedly give the same result while repeatedly measuring the wrong thing.

32. Descriptive Research

📌 Descriptive research observes and records behaviour.

Major descriptive methods:

1. Case studies

2. Naturalistic observation

3. Surveys

Descriptive research can reveal useful information, but by itself it does not establish cause and effect.

33. Case Study

📌 Case study = intensive examination of one individual or group.

Strength

Can provide rich, detailed information and may reveal phenomena worth investigating further.

Limitations

An individual case may be unusual and therefore not representative of everyone.

Professor material also connects case studies with problems involving:

• Representativeness

• Reliability

• Observer bias

• Validity

🎯 KEY RULE:
A fascinating individual case does not automatically generalize to the population.

34. Naturalistic Observation

📌 Naturalistic observation = recording behaviour in the subject's natural environment.

It can provide revealing descriptions of real behaviour.

But:

It describes behaviour; it does not explain its cause.

Professor's listed disadvantages:

1. Little environmental control → can undermine reliability and makes cause/effect difficult to establish.

2. Observer bias

3. Hawthorne effect — people may change their behaviour when they realize they're being observed.

4. Can be time-consuming and expensive.

35. Laboratory Observation

Observation in a laboratory gives researchers greater control over the situation and setting.

But greater control creates a potential problem:

Artificiality

Professor's example/question:

Will children behave the same way in the laboratory?

So:

Naturalistic → realism ↑, control ↓

Laboratory → control ↑, potential artificiality ↑

36. Surveys

📌 Survey = a list of questions answered by research participants that allows researchers to collect information from many people.

Researchers use a sample to learn about a larger population.

Population

📌 Population = all the individuals in the group researchers want to study/generalize to.

Sample

The smaller group actually studied.

Random Sample

📌 Random sample = sample that fairly represents the population because each member has a chance of being selected.

Wording Effects

Small changes in the wording or order of questions can substantially alter responses.

Survey disadvantages

Professor specifically lists:

1. Sampling bias, including self-selection → undermines reliability.

2. Wording effects/question types → undermine validity.

37. Correlational Research

📌 Correlation = measure of the extent to which two variables change together and therefore how well one predicts the other.

📌 Variable = anything that can vary and is feasible and ethical to measure.

Examples:

• Sleep hours

• Test scores

• Stress

• Age

• Exercise

• Mood

38. Correlation Coefficient

📌 Correlation coefficient = numerical measure of the strength and direction of a relationship.

Represented as r.

Range:

−1.00 to +1.00

Direction

Positive (+) → variables move in the same direction.

As X increases, Y tends to increase.

OR as X decreases, Y tends to decrease.

Negative (−) → variables move in opposite directions.

As X increases, Y tends to decrease.

Strength

Closer to ±1.00 = stronger

Closer to 0 = weaker

⚠ The sign tells you direction, NOT strength.

So:

r = −.90 is much stronger than r = +.20.

39. Scatterplots

📌 Scatterplot = graph of clustered dots representing values of two variables.

Each dot represents paired values.

The overall pattern tells us:

• Direction of relationship

• Strength of relationship

Tightly clustered pattern → stronger correlation.

Widely scattered points → weaker correlation.

40. CORRELATION ≠ CAUSATION

🚨 EXTREMELY IMPORTANT

If A and B correlate, there are multiple possibilities:

A → B

OR

B → A

OR

C → both A and B

Therefore:

Correlation does NOT prove causation.

Correlation allows prediction, not necessarily causal explanation.

41. Illusory Correlation

📌 Illusory correlation = perceiving a relationship where none actually exists OR perceiving a relationship as stronger than it really is.

Illusory correlations can contribute to:

• Superstitious thinking

• Illusions of control

42. Regression Toward the Mean

📌 Regression toward the mean = tendency for extreme or unusual scores/events to move back toward the average.

Example

Someone performs extraordinarily well once.

Their next performance is more likely to be closer to their normal average rather than equally extraordinary.

This doesn't necessarily mean something caused the decline—it may simply reflect normal variation.

43. Experimental Research

Descriptive research describes.

Correlational research predicts relationships.

Experimental research can test cause and effect.

📌 Experiment = research method in which investigators manipulate one or more factors to observe the effect on some behaviour or mental process.

The professor's broader research-method material also identifies:

• Correlational

• Longitudinal

• Experimental

• Quasi-experimental research

44. Experimental Group vs. Control Group

Experimental Group

Receives the treatment/manipulation.

Control Group

Does not receive the experimental treatment, or receives a comparison/placebo condition.

The control condition provides a baseline for comparison.

Without comparison, it becomes difficult to know whether the treatment actually produced the observed change.

45. Random Assignment

📌 Random assignment = assigning participants to experimental and control conditions by chance.

Purpose:

Make the groups initially similar by minimizing pre-existing differences.

This allows researchers to make stronger cause-and-effect conclusions.

🚨 DON'T CONFUSE

Random Sampling

WHO gets into the study?

Purpose → representative sample/generalization.

Random Assignment

WHICH GROUP do participants enter?

Purpose → equalize groups/cause and effect.

This distinction appears again in Module 3.

46. Placebo Effect

📌 Placebo effect = experimental results caused by participants' expectations rather than the actual treatment.

A placebo resembles a treatment but lacks the active ingredient/manipulation.

47. Single-Blind vs. Double-Blind Procedures

Single-Blind

Participants do not know which condition they are in.

Double-Blind

Neither the participants nor the researchers interacting with/evaluating them know who received the real treatment versus placebo.

Double-blind procedures help reduce:

• Participant expectation effects

• Researcher expectancy/bias

48. Independent Variable

📌 Independent variable (IV) = factor the researcher manipulates.

Think:

I manipulate the IV.

49. Dependent Variable

📌 Dependent variable (DV) = outcome that is measured.

It may change depending on the IV.

Example

Research question:

Does caffeine affect test performance?

IV: caffeine amount
DV: test performance

50. Confounding Variable

📌 Confounding variable = factor other than the intended independent variable that might influence the result.

Example:

Suppose:

• Experimental group receives caffeine in the morning.

• Control group receives no caffeine at night.

Now time of day is confounded with caffeine.

You cannot confidently know whether caffeine or time caused the difference.

51. Comparing the Three Major Research Methods

Professor's comparison adds the main weaknesses:

Descriptive: no control of variables; individual cases may mislead.

Correlational: cannot determine cause and effect.

Experimental: sometimes impossible or unethical; results may not generalize perfectly to other contexts.

52. Research Ethics

Psychological research must protect participants.

Important principles include:

Informed Consent

Participants receive enough information to voluntarily choose whether to participate.

Protection from Harm

Researchers must minimize unnecessary risk/harm.

Confidentiality

Personal information should be appropriately protected.

Debriefing

📌 Debriefing = explaining the study to participants afterward, including deception when appropriate.

Institutional Review Boards (IRBs)

Research involving humans is reviewed for ethical acceptability.

Animal research also involves ethical standards regarding humane treatment and whether the research is justified.

53. Scientific Integrity & Values

Science depends on researchers reporting methods and findings accurately.

Psychology is a science, but scientists themselves are human. Researchers' questions and interpretations can be influenced by values and assumptions.

This makes:

• Transparency

• Replication

• Peer review

• Critical thinking

especially important.

📊 MODULE 3 — STATISTICAL REASONING IN EVERYDAY LIFE

54. Statistical Literacy

📌 Statistics = using mathematical methods to understand numerical information/data.

Basic statistical literacy benefits everyone because numbers can easily be misunderstood or presented misleadingly.

The professor warns about:

“Off-the-top-of-the-head” estimates and big, round, undocumented numbers.

Slide examples include claims involving:

• “10 percent of people…”

• “10 percent of the brain…”

• “10,000 steps…”

The lesson is not simply to accept a number because it sounds scientific.

55. Descriptive Statistics

📌 Descriptive statistics = statistical methods used to summarize data.

They describe the data you actually collected.

56. Misleading Graphs

Graphs can make the same numerical difference appear:

• Huge

• Tiny

depending on the scale.

The professor emphasizes the vertical/y-axis.

When reading a graph:

1. Look at the scale labels.

2. Examine the range.

3. Don't judge only by the visual height of bars.

The truck-brand figure demonstrates that the same data can look dramatically different simply by changing the y-axis range.

🎯 EXAM CONNECTION: Always read the scale labels.

57. Measures of Central Tendency

📌 Central tendency = a single score used to represent an entire distribution.

Three major measures:

Mode

📌 Mode = most frequently occurring score(s).

Mean

📌 Mean = arithmetic average.

Add all scores ÷ number of scores

Problem:

The mean can be distorted by a few extreme/atypical scores.

Median

📌 Median = middle score.

Half the scores fall above it and half below it.

58. Outliers & Skewed Distributions

📌 Outliers = one or more extreme scores.

They can make a distribution asymmetrical/skewed and strongly affect the mean.

The professor's family-income figure illustrates this.

Most families are clustered at relatively lower incomes, but a few extremely high incomes pull the mean upward.

The figure approximately shows:

Mode ≈ 40

Median ≈ 60

Mean ≈ 140

because very high incomes such as 180, 950, and 1420 pull the mean to the right.

🎯 KEY RULE

Extreme scores distort the MEAN most.

That is why median income is often useful for describing a skewed income distribution.

59. Measures of Variation

Central tendency tells us where scores center.

Variation tells us how similar or different the scores are.

Range

📌 Range = highest score − lowest score.

Easy to calculate but heavily affected by extremes.

Standard Deviation

📌 Standard deviation (SD) = computed measure showing how much scores differ from the mean.

Interpretation

Small SD → scores cluster near the mean.

Large SD → scores are more spread out.

🎯 Module Test idea:
If asked “What does standard deviation tell us?”

→ How much individual scores differ from the mean.

60. Normal Curve / Normal Distribution

📌 Normal curve = symmetrical, bell-shaped distribution in which most scores fall near the mean and fewer occur toward the extremes.

Approximately:

68% → within 1 SD

95% → within 2 SD

99.7% → within 3 SD

The slide explicitly emphasizes about 68% within one standard deviation.

WAIS example

Scores on aptitude tests often approximate a bell-shaped distribution.

The Wechsler Adult Intelligence Scale defines the average score as 100.

61. Generalizability vs. Cause & Effect

This is one of the most important connections between Modules 2 and 3.

Random Sampling

Necessary for generalizing from a sample → population.

Random Assignment

Important for drawing cause-and-effect conclusions.

Probability models can then help researchers estimate expected random variation, whether results could occur by chance, and margins of error.

🚨 MEMORIZE

Random SAMPLE → population

Random ASSIGNMENT → experiment/groups/cause

62. Inferential Statistics

📌 Inferential statistics = statistical methods that use data from a sample to make inferences about a larger population.

Compare:

Descriptive

“What does our collected data look like?”

Inferential

“What can this sample tell us about the population?”

63. When Can We Trust a Sample Difference?

Three principles from the professor/textbook:

1. Representative samples > biased samples

2. Bigger samples > smaller samples

3. More estimates > fewer estimates

And:

Estimates based on a few unrepresentative cases are unreliable.

This connects back to:

• Random sampling

• Replication

• Meta-analysis

• Avoiding conclusions based only on anecdotes

64. Null Hypothesis

📌 Null hypothesis = assumption that no real difference exists between the groups/populations.

Researchers initially ask:

If there truly were no difference, how surprising would our observed result be?

65. Statistical Testing

Researchers use statistical tests to estimate how likely their result would be if the null hypothesis were true.

If:

• Estimates are reliable, AND

• The observed difference is relatively large,

then the difference is more likely to reach statistical significance.

66. p-Values

📌 p-value = probability of obtaining the result, given the null hypothesis.

The course uses the conventional threshold:

p < .05

Meaning the observed result would be sufficiently unlikely under the null hypothesis to meet the course's conventional significance threshold.

When p is very low, researchers have stronger evidence for rejecting the null/no-difference hypothesis.

67. Statistical Significance

📌 Statistical significance concerns how likely the observed result would have happened by chance if the null hypothesis were true.

🚨 CRITICAL DISTINCTION

Statistically significant DOES NOT mean:

• Important

• Huge

• Strong

• Practically meaningful

A statistically significant finding may have a tiny effect size and little practical significance.

68. Effect Size & Practical Significance

📌 Effect size concerns the magnitude/size of an observed effect or difference.

A huge sample can make a very small effect statistically significant.

Textbook example you provided

A study involving roughly 20,000 people found an approximately 1.5-point IQ difference between first-born and later-born children.

Because the sample was huge, the difference could be statistically significant.

But:

A ~1.5-point difference may have little practical importance.

Therefore:

Statistical significance

“Is this result unlikely under the null hypothesis?”

Effect size

“How large is the difference/effect?”

Practical significance

“Does this difference actually matter in the real world?”

🚨 STATISTICALLY SIGNIFICANT ≠ PRACTICALLY IMPORTANT

69. Regression Toward the Mean — Textbook Retrieval Practice

The textbook example you sent:

At the University of Michigan, around 100 Arts & Sciences students might earn perfect marks after their first term, but only roughly 10–15 ultimately graduate with perfect marks.

Why?

One important statistical principle is:

Regression toward the mean

Extremely high first-term results tend to be followed by results closer to the person's typical performance as more courses and opportunities for variation accumulate.

70. Descriptive vs. Inferential Statistics — Retrieval Practice

Descriptive Statistics

Summarize the data.

Examples:

• Mean

• Median

• Mode

• Range

• Standard deviation

• Graphs

Inferential Statistics

Determine whether sample results can reasonably generalize to a population.

🧠 MEMORY TRICK

Describe → Descriptive

Infer beyond sample → Inferential

🔥 CHAPTER 1 — HIGH-YIELD “DON'T CONFUSE THESE” SECTION

🧪 PROFESSOR/TEXTBOOK CHECK-YOUR-UNDERSTANDING & MODULE-TEST MATERIAL

These should be treated as exam material, not optional extras.

1. From the 1920s to the 1960s, what two major forces dominated psychology?

Behaviorism and Freudian/psychoanalytic psychology.

2. What is natural selection?

The evolutionary process through which traits that contribute to survival/reproduction become more common across generations.

3. Contemporary psychology's position on nature–nurture?

Both matter and interact. Biology and experience jointly influence behaviour and mental processes.

4. Which perspective examines differences across situations and cultures?

Social-cultural.

5. Which perspective focuses on observable responses and learning?

Behavioral.

6. What is hindsight bias?

Believing after an outcome occurs that we would have predicted it beforehand — “knew it all along.”

7. Why can't intuition/common sense replace science?

Because human thinking is vulnerable to hindsight bias, overconfidence, and perceiving patterns in randomness.

8. What is replication?

Repeating the essence of a study with different participants/situations to see whether the finding can be reproduced.

9. Why is an unrepresentative sample dangerous?

It may not accurately represent the population, making generalization unreliable.

10. Does correlation prove causation?

NO.

A → B, B → A, or a third variable C could explain both.

11. What is regression toward the mean?

Extreme results tend to be followed by results closer to average.

12. Why use a placebo/control group?

To provide a comparison and separate the treatment's effect from expectations or other changes.

13. What is a confounding variable?

An unintended factor that varies with the IV and provides an alternative explanation for the outcome.

14. Why does an experiment need a control/comparison condition?

Without comparison, researchers cannot confidently determine whether the experimental manipulation caused the outcome.

15. Which measure of central tendency is most distorted by extremely high or low scores?

MEAN.

16. What does standard deviation tell you?

How much individual scores differ from the mean.

17. What is a bell-shaped distribution called?

Normal curve / normal distribution.

18. When are sample differences more likely to be statistically significant?

When:

Sample averages/estimates are reliable + observed difference is relatively large.

19. What is the conventional significance threshold used in this chapter?

p < .05

20. Does statistically significant mean important?

NO.

A statistically significant effect can still be tiny and have little practical significance.

21. What is the difference between descriptive and inferential statistics?

Descriptive → summarizes data.

Inferential → uses sample data to draw conclusions about a population.

🧠 CHAPTER 1 BIG PICTURE

Everything in this chapter connects to one central idea:

Human intuition can be useful, but it can also mislead us. Psychological science gives us systematic tools for checking what we think we know.

Module 1 establishes psychology as a science and shows how the field developed from structuralism and functionalism through behaviourism, psychoanalysis, humanism, cognition, and today's multiple perspectives.

↓

Module 2 asks:

How do psychologists produce trustworthy evidence?

Through scientific theories, hypotheses, operational definitions, replication, careful sampling, descriptive/correlational/experimental methods, controls, random assignment, and ethical research.

↓

Module 3 asks:

Once psychologists collect data, how do they interpret it correctly?

Through descriptive and inferential statistics while recognizing sampling issues, variability, chance, effect size, and the distinction between statistical significance and practical importance.

The Chapter 1 logic is therefore:

Scientific attitude

→ Critical thinking

→ Scientific method

→ Research design

→ Collect data

→ Analyze statistics

→ Evaluate evidence

→ Revise conclusions when evidence requires it

That is the foundation the rest of psychology builds on.