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Psych 102 > Chapter 1 - Intro > Flashcards

Chapter 1 - Intro Flashcards

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1
Q

what is psych?

A
  • scientific study of behaviour

- study of thinking, emotion, cognition

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2
Q

goal of psych

A

to describe, explain, predict, and control

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3
Q

give an example of a different level of analysis

A

analyzing 1 individual vs. analyzing a group of individuals

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4
Q

psychological knowledge

A
  • how do we know what we know?

- how do we learn what we don’t know?

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5
Q

questions to ask when thinking critically about a study, headline, etc.

A
  • who is the sample? is it representative?
  • how would the researchers have measured this? what were their methods?
  • what things might have skewed these results?
  • what kind of people were studied? (ie. age, economic status, residence, etc.)
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6
Q

human reasoning

A
  • we can’t trust our personal experience as a valid source of evidence
  • many other variables, as well as the regression to the mean, may actually be the things changing our behaviour
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7
Q

if there is a strong correlation between 2 variables, does that imply a causal relationship?

A
  • no! Correlation does not imply causation

- other explanations are possible, like a 3rd variable

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8
Q

order in random events

A
  • given random data, we look for order/meaningful patterns, even if none exist
  • ex. hot-hand phenomenon: believing that if a basketball player makes 3 shots, they’re more likely to make the 4th -> untrue, we’re just attributing meaning to that event
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9
Q

confirmation bias

A
  • we attend to info we agree with and ignore what we don’t
  • ex. study on attitudes toward capital punishment where reading fact sheets about its pros and cons strenghtened people’s beliefs; those who slightly supported it now strongly supported it (and vice versa) because they only attended to info that supported their belief
  • ex. psychiatrists mistakenly diagnosing patients as depressed b/c they gave symptoms of depression first, even though they later gave way more symptoms of anxiety
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10
Q

can we trust smart people? (professors, doctors, etc.)

A
  • not really, smart people aren’t immune to biases and faulty reasoning
  • we have a tendency to try to explain things we don’t understand, even if the explanation is ridiculous (ex. greek poet’s explanation for the solar eclipse)
  • thoeries that seem well-researched can be completely inaccurate (ex. phrenology)
  • we continue to do things even if they make no sense (ex. icing the kicker even though there’s no data to show that it works)
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11
Q

what we can’t trust vs. what we can trust

A
  • we can’t trust our own personal experiences, the opinions of friends, relatives, loved ones, or smart people
  • we can trust data
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12
Q

why do we need the scientific method?

A

to protect us from sloppy thinking and human reasoning

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13
Q

7 hallmarks of the scientific method

A
  1. objective observation and logically necessary conclusions based on studies
  2. parsimonious explanations
  3. independent replication
  4. scepticism
  5. careful designs
  6. falsifiability
  7. open-mindedness
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14
Q

objective observation and logically necessary conclusions based on a study

A
  • hallmark of scientific method
  • ex. the logically necessary conclusion would be that stressful life events are related to depression, not that they cause depression
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15
Q

parsimonious explanations

A
  • hallmark of scientific method
  • if we have 2 theories that explain something, we go with the more efficient one (unless it can’t explain something that a more complex one can)
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16
Q

independent replication

A
  • hallmark of scientific reasoning
  • if only 1 person is showing that something is true, we need to be weary of it
  • we want an independent team to look at it as well, and we can only be confident if they find the same thing
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17
Q

skepticism

A
  • hallmark of scientific reasoning

- be sceptical of the study until you can look into it and see that it’s a well designed one

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18
Q

careful designs

A
  • hallmark of scientific reasoning

- using study designs to help us avoid alternative explanations (ie. regression to the mean)

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19
Q

falsifiability

A
  • hallmark of scientific reasoning

- translating a theory into a way where it can either be proven true or false

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20
Q

open-mindedness

A
  • hallmark of scientific reasoning
  • being open to someone else’s ideas and evidence rather than using confirmation bias to ignore their thoughts if they don’t agree with your own
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21
Q

the dialectic of science

A

“science is a unique mix of openness and skepticism”

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22
Q

research process

A
  1. theory (ex. low self-esteem feeds depression)
  2. hypothesis (ex. people with low self-esteem will score higher on a depression scale)
  3. research and observations (ex. administer tests of self-esteem and depression; see if a low score on one predicts a high score on the other)
  4. Generate new theories or refine yours, and the cycle continues
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23
Q

when human reasoning goes unchecked by scientific investigation

A
  • reasoning/theories -> reasoning/theories -> reasoning/theories -> who knows??
  • reasoning/theories -> anecdotal evidence -> reasoning/theories -> who knows??
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24
Q

when human reasoning is kept in check by scientific investigation

A
  • reasoning (theories) -> science -> reasoning (theories) -> science -> truth (or closer towards it)
  • anecdotal evidence -> science -> reasoning (theories) -> science -> truth (or closer towards it)
25
Q

2 possible outcomes if scientific method is used

A
  1. inaccurate beliefs are discredited and replaced by more accurate ones
  2. we don’t have methods or tech to study and make progress in a certain area, so we have to temporarily remain ignorant (but it’s better to say we don’t know rather than creating an elaborate theory that’s completely inaccurate)
    - either way, we’re protecting the public from inaccurate beliefs
26
Q

theory

A
  • the idea
  • definition of it is different in hard sciences vs. social sciences
  • not the same as a hypothesis
27
Q

hypothesis

A

a testable prediction to enable us to keep, reject, or otherwise revise the theory

28
Q

construct

A

the concept that is being measured (ex. depression)

29
Q

operational definition

A

how you’re measuring the construct; the method used to define/measure a variable in a study (ex. a depression questionnaire)

30
Q

replication

A

finding the same thing to be true more than once with different participants in different situations (ie. different ages, locations, etc.)

31
Q

random sampling

A

when each member of a population has an equal chance of being included in a sample (aka: an unbiased sample)

32
Q

3 types of scientific studies

A
  • descriptive
  • correlational
  • experimental (or quasi-experimental)
33
Q

descriptive studies

A
  • purpose: careful and accurate description (ex. how much sleep do people get? what’s the average? etc.)
  • methods: questionnaires and interviews, naturalistic observation, case studies
  • cannot infer correlation from descriptive studies
34
Q

correlational

A
  • purpose: evaluating relationships
35
Q

R

A
  • correlation coefficient
  • +/- indicates direction of relationship (positive or negative)
  • 0-1 indicates strength of relationship (0 being none, 1 being strong)
36
Q

scatterplot (slope and scatter)

A
  • graph that visually represents 2 variables of correlational data
  • slope: depicts direction
  • scatter: depicts strength of relationship
37
Q

illusory correlation

A
  • perception of a relationship where no relationship actually exists
  • ex. correlation btwn parents adopting children and then conceiving shortly after (disconfirming evidence sticks out much less than confirming evidence, and because of this we perceive there to be a relationship were none exists)
38
Q

experimental/quasi-experimental

A
  • manipulating the IV to measure its effect on DV

- purpose: exploring cause and effect

39
Q

experimental condition

A

exposes participants to the treatment/IV

40
Q

control condition

A

participants aren’t exposed to the treatment/IV

41
Q

placebo

A
  • inert substance/condition that takes the place of the active treatment agent
  • given to control group
42
Q

random assignment

A
  • every participant must have the equal chance of being randomly assigned to experimental or control groups
  • must have this to have an experiment
  • minimizes all other differences between groups except for the treatment (controls for possible confounding variables)
43
Q

double-blind randomized control trial

A
  • research participants and the researcher are unaware of each participant’s status (treatment or control)
  • ensures that participants’ expectations/beliefs don’t affect how they do
  • also ensures that the researcher doesn’t have conscious or unconscious bias (confirmation bias) while assessing the patients
44
Q

statistics

A
  • analyze and interpret data in a convienent way
  • allow us to see what the unaided eye misses
  • objective way to quantify and summarize what happens in a study to avoid pitfalls of human judgement
45
Q

2 main types of statistics

A
  • descriptive

- inferential

46
Q

descriptive statistics

A
  • accurate, meaningful description of data

- 2 ways to acheive this: measures of central tendency and measures of variation

47
Q

measures of central tendency

A
  • single score that represents a whole set of scores
  • mode: most frequently occuring score in a distribution
  • mean: arithmetic average of scores in a distribution (can be distorted by a few atypical scores)
  • median: middle score in a rank-ordered distribution
48
Q

measures of variation

A
  • range: difference between highest and lowest scores in a distribution
  • standard deviation: computed measure of the average amount by which scores deviate from the mean
49
Q

normal distribution/normal curve

A
  • bell shape most common, naturally-occurring

- most scores occur in the middle - as we go to extreme high or low scores, there are less of them

50
Q

skewed distribution

A

bell shape lost because many of the extreme values are on the left or right because the mean (and median, though not as extremely) get pulled away from the centre

51
Q

inferential statistics

A
  • statistical statement of how frequently a result in a study could occur by chance
52
Q

when is an observed difference reliable (and not by chance?)

A
  • large samples
  • large mean difference or correlational relationship
  • less variability
53
Q

when is a difference statistically significant?

A
  • when observed difference is unlikely to happen by chance

- alpha level of .05 (probability is less than .05)

54
Q

why can’t we rely on human intuition?

A
  • hindsight bias
  • overconfidence
  • tendency to perceive patterns in random events
55
Q

hindsight bias

A
  • tendency to believe after learning the outcome that one would have foreseen it (the “I knew it all along” phenomena)
  • ex. if 2 of our friends start dating, we’ll say we knew all along that they were meant to be together
56
Q

overconfidence

A
  • human tendency to think we know more than we do

- ex. getting factual questions wrong even when confident, getting predictions of social behaviour wrong

57
Q

tendency to perceive patterns in random events

A
  • perceiving patterns where none exist in order to make sense of the world
  • ex. seeing a face on the moon, perceiving a pattern in a random set of numbers… random sequences often don’t look random
58
Q

3 scientific attitudes

A
  • curiosity
  • humility
  • scepticism

Psych 102 (9 decks)

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