Week 1 Flashcards

1
Q

Wilhelm Wundt

A
  • Established psych as independent field in Germany
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2
Q

William James

A
  • Brought psychology from Germany to America - “father of modern psychology”
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3
Q

Edward Titchner

A
  • Wundt’s student
  • Pioneered structuralism and introspection
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4
Q

Structuralism

A
  • 1st
  • Pioneered by Edward Titchner
  • Break the psyche down into individual parts
    (think chem and molecules).
  • Individual parts found via introspection – trained individuals reflect on their own experiences
  • Weaknesses: experience is subjective
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5
Q

Psychoanalytic Theory

A
  • 2nd
  • Freud
  • General theory that emphasizes influence of unconscious feelings, thoughts, etc
  • Conscious thoughts and feelings motivated by secret desires or anxieties
  • The unconscious: part of mind containing info that ppl are unaware of
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6
Q

Functionalism

A
  • 3rd
  • Mental states and actions should be understood with evolution in mind (adaptive significance)
  • Weakness: doesn’t account for individuality
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7
Q

Behaviorism

A
  • 4th
  • John Broadus Watson
  • Study ONLY observable behavior and not cognitive processes (i.e., stim and response)
  • Weakness: didn’t account for neurological processes
  • Popularized by Skinner box experiment
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8
Q

Cognitive psychology

A
  • 5th
  • Pushed back against behaviorism – “cognitive processes are important too”
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9
Q

Phineas Gage

A
  • Rail tamp went through head –> damaged frontal lobe –> afterwards, his behavior changed to mean, poor executive functioning, etc
  • First patient revealing association between behavior and part of brain
  • Caveat: not observed by scientists in the years after the accident and initial behavior changes; some accounts described him as nice and pleasant
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10
Q

Cross-Cultural psychology

A
  • Draw comparisons btw individual/group behaviors across populations
  • 96% of psych study populations are WEIRD despite only being 12% of global pop
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11
Q

Why psychology is WEIRD

A

W - white
E - Educated
I - Industrialized
R - Rich
D - Democratic

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12
Q

Basic vs applied research

A

Basic: things we do for the sake of science (not necessarily a clear application)

Applied: we can use the results to solve real-world problems (clinical, educational, forensic, etc)

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13
Q

Hindsight bias

A

Belief that an outcome was foreseeable after it had already occurred (e.g. “I KNEW he shouldn’t have built that rocket)

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14
Q

Scientific method

A
  • Standardized procedure to reduce bias
  • Theory –> hypothesis –> research –> results either support or refute theory
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15
Q

Operational variable

A

Description of a property in concrete terms (e.g. measuring wealth in terms of yearly income, net worth, etc)

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16
Q

Power vs reliability

A

Power: presence of change

Reliability: absence of change

Good detector detects power, not reliability

17
Q

Construct validity

A

Operations of definitions generally seen as good indicators for that def (e.g. smiles is generally seen as good indicator of happiness)

18
Q

Correlational vs experimental design

A

Correlational: OBSERVATION; researchers don’t manipulate variables and just observe relationship btw two variables
- Can only infer correlation and NOT causation, but can inspire experimental study

Experimental: researchers actively MANIPULATE DV to est CAUSAL relationship
- Controlled lab settings can make real-world application difficult

19
Q

Correlational design

A
  • Observation of the relationship btw two variables
  • Establishes correlational relationship
  • Variables called the PREDICTOR and OUTCOME/CRITERION (not IV and DV)
  • Results can inspire future experimental studies to est a causal relationship
20
Q

Different kinds of correlations

A

Direct/positive correlation: x and y in same direction

Indirect/negative correlation: x and y in different directions

Zero correlation: one var not predictably related to the other

21
Q

Correlation strength

A
  • Pearson’s R (r) – coefficient to represent correlation strength
  • Ranges from -1 to 1
  • Certinanity based on absolute value; closer to 0 means less of a correlation
  • Pearson’s R represents the data’s fit to the line, NOT slope
22
Q

Experimental design

A
  • Researchers actively manipulate IV to find causal relationship to DV
23
Q

Random assignment

A
  • Randomly assign participants to different lvls of IV
  • Increases chance that characteristics will be spread out
24
Q

Population vs sample

A

Population: EVERYONE in the group a study is interest in (e.g. all white ppl, all ppl with low income, etc)

Sample: subset of the population of interest

25
Convenience sampling
Sampling ppl conveniently available (usually uni students)
26
Random sampling
EVERY person in the population has an equal chance of being chosen
27
What makes a good hypothesis
- Must be FALSIFIABLE -- able to be disproven - Includes variables and predicted relationship