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PSYC 104 - Introductory Psychology I > Chapter 2 - Research Methods > Flashcards

Chapter 2 - Research Methods Flashcards

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1
Q

Why we need good research methods?

A

-protect against bias to ensure results are accurate and conclusions are true
-avoid errors

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2
Q

Prefrontal Lobotomy

A

-surgical procedure that severs fibres connecting the frontal lobe of the brain with the thalamus
-used to treat schizophrenia
-results based only on subjective clinical results
-didn’t conduct systematic research and assumed their observations were enough to verify their results

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3
Q

System 1 Thinking

A

-intuitive
-fast
-relies on feelings and gut reactions
-may be an assumption
-relies on heuristics
-prone to error

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4
Q

Heuristic

A

-mental shortcut or rule of thumb that helps us to streamline our thinking and make sense of our world
-based on past history

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5
Q

System 2 Thinking

A

-analytical
-slow
-relies on careful evaluation of evidence
-reflective

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6
Q

Scientific Method

A

-not a singular way of doing things
-it is a toolbox of skills that can be applied in specific ways
-permit us to test hypotheses

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7
Q

Surveys

A

-used to measure peoples opinions and attitudes
-a self-report measure

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8
Q

Questionnaire

A

-a self-report measure
-assess personality traits, mental illnesses, interests

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9
Q

Self-Report Measure Advantages

A

-easy to administer and gather large amount of data
-cost effective
-allows assessment of internal processes, thoughts, feelings that outside observers are not typically aware

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10
Q

Self-Report Measure Disadvantages

A

-the wording of the question can lead to different results
-assumes respondents have enough knowledge to report accurately
-assumes participants are honest

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11
Q

Response Sets

A

-tendency of research participants to distort their responses to questionnaire items

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12
Q

Malingering

A

-tendency to make ourselves appear psychologically disturbed
-aim of achieving a clear-cut personal goal
-may be trying to obtain financial compensation or escape military duty

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13
Q

Rating Data

A

-a self-report measure
-someone else is asked to comment on a person’s behaviour
-it is assumed they know the person well

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14
Q

Rating Data Advantages

A

-gets around malingering and response set bias

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15
Q

Rating Data Disadvantages

A

-halo effect
-horns effect
-susceptible to stereotypes

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16
Q

Halo Effect

A

the tendency for a high rating in one positive characteristic to spill over and enhance the ratings of other characteristics

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17
Q

Horns Effect

A

the tendency for a high rating in one negative characteristic to spill over and lower ratings of other characteristics

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18
Q

Random Selection

A

-procedure that ensures that every person in a population has an equal chance of being chosen to participate
-allows us to generalize our results
-studying fewer people broadly is better than studying more people narrowly

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19
Q

Generalizability

A

-a measure of how useful the results of a study are for a broader group of people or situations
-ie. if the study results are applicable to many people or situations = good generalizability

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20
Q

Reliability

A

-an evaluating measure
-the consistency of a measurement
-the study will measure the same way over and over again

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21
Q

Test-Retest Reliability

A

-reliable questionnaire yields same scores over time
-consistent results
-ie. stepping on a scale and measuring the same weight multiple times

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22
Q

Interrater Reliability

A

-the extent to which different people who conduct an interview or make observations agree on the characteristics they are measuring

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23
Q

Validity

A

-the extent to which a measure assesses what it purports to measure
-ie. lie detector polygraph is not valid

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24
Q

Reliability + Validity

A

-reliability is necessary for validity
-validity is not necessary for reliability

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25
Q

Replicability Crisis

A

-open and transparent science is needed to ensure findings are replicable and reproducible
-sparked the open science movement

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26
Q

Post Data Publicly

A

-a response to the replicability crisis
-data needs to be public to be replicated and peer reviewed

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27
Q

Conduct Replications

A

-a response to the replicability crisis
-replications of own and others work needs to be available

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28
Q

Preregister Research

A

-a response to the replicability crisis
-prevents forged numbers
-when you provide a blueprint it is unchangeable

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29
Q

Publish ALL Sound Science

A

-a response to the replicability crisis
-journals only publish fancy findings to gain interest
-publish all works including replications
-scientists want to be published and wont replicate if they know they won’t be selected

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30
Q

Less Emphasis on Single Study Findings

A

-a response to the replicability crisis
-more emphasis on replicated studies

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31
Q

3 Types of Research Methods

A

-descriptive
-correlational
-experimental

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32
Q

Naturalistic Observation

A

-descriptive research method
-observe behaviour naturally without trying to manipulate it
-ie. observing in the wild

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33
Q

Natural Observation Advantages

A

-high in external validity
-captures natural behaviour

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34
Q

Naturalistic Observation Disadvantages

A

-low internal validity
-doesn’t allow us to infer causation
-possible reactivity (people know they are being studied)
-possible observer bias
-no control over other variables

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35
Q

External Validity

A

-extent to which we can generalize findings to real-world settings

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36
Q

Internal Validity

A

-extent to which we can draw cause-and-effect inferences from a study

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37
Q

Case Studies

A

-descriptive research method
-an in depth analysis on an individual, group, or event over an extended time period

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38
Q

Existence Proof

A

-demonstration that a given psychological phenomenon can occur

39
Q

Case Study Advantages

A

-can provide existence proofs
-allows study of rare phenomena
-good for hypotheses generation
-offers insights for later testing

40
Q

Case Study Disadvantages

A

-typically anecdotal
-don’t allow us to infer causation
-generalization may be an issue
-possible observer bias

41
Q

Correlational Designs

A

-research design that examines the extent to which to variables are associated/related
-allow us to generate predictions about the future

42
Q

Correlate

A

-two things that relate to each other statistically rather than interpersonally

43
Q

Advantages of Correlational Designs

A

-flexible and easier to conduct than experiments

44
Q

Disadvantages

A

-cannot explain causation

45
Q

Positive Correlation

A

-as the value of one variable changes, the other goes in the same direction
- + = perfect positive correlation

46
Q

Zero Correlation

A

-the variables don’t go together at all

47
Q

Negative Correlation

A

-as the value of one variable change, the other goes in the opposite direction
- -1.0 = perfect negative correlation

48
Q

Third-Variable Problem

A

-the reason correlational research doesn’t show causation
-while x and y might show correlation, there could be a third z variable that affects the two

49
Q

Correlation Coefficient

A

-measures the strength of a correlation
-scale from -1.0 (negative) to + 1.0 (positive)

50
Q

Scatterplot

A

-grouping of point on a two-dimensional graph (x, y) in which each dot represents a single person’s data

51
Q

Scatterplot Negative Correlation

A

-the plot goes in a downward slope
-if the correlation isn’t a perfect negative (-1.0) that means that some students still did well and some students who drank non still did poorly
-ie. shows the more beers drank the worse students do on an exam

52
Q

Scatterplot Zero Correlation

A

-no definite pointing up or down
-no association

53
Q

Scatterplot Positive Correlation

A

-dots point in an upward slope
-ie. more psych classes attended, the better they do on their exam

54
Q

Illusory Correlation

A

-perception of a statistical association between two variables where none exists

55
Q

Experimental Design

A

-a research design characterized by random assignment of participants to conditions
-involves the manipulation of at least one variable
-allows researchers to establish as causal relationship between variables

56
Q

Components of an Experiment

A
  1. Random assignment of a participants to conditions
  2. Manipulation of an independent variable
57
Q

Random Assignment

A

-randomly sorting participants into groups
-cancels out preexisting differences between the two groups
-ensures the participant has an equal chance of being sorted into one of the two groups

58
Q

Experimental Group

A

-in an experiment, the group of participants that receives the manipulation

59
Q

Control Group

A

-in an experiment, the group of participants that doesn’t receive the manipulation

60
Q

Independent Variable

A

-variable that an experimenter manipulates

61
Q

Dependent Variable

A

-variable that an experimenter measures to see whether the manipulation has an effect

62
Q

Between-subjects Design

A

-in an experiment, researchers assign different groups to the control or experimental condition
-group A gets drug, group B doesn’t

63
Q

Within-subjects Design

A

-in an experiment, each participant acts as his or her own control
-they measure a behaviour before a variable is manipulated, and then after

64
Q

Operational Definition

A

-a working definition of what a researcher is measuring

65
Q

Confounds (extraneous/confounding variables)

A

-any variable that differs between experimental and control group
-may be responsible for the observed difference between the groups after manipulation
-researcher trie to control things that could affect the results that weren’t accounted for
-ensures there is only one manipulated variable
-ie. was the result do to the drug or financial status

66
Q

Experimental Design Example

A

-Hypothesis: drug will increase a participants mood
-Independent variable: whether a subject gets the drug
-Dependent variable: mood of the participant

67
Q

Placebo Effect

A

-improvement resulting from the mere expectation of improvement

68
Q

Blind

A

-a way to control the placebo effect
-unaware of whether one is in the experimental or control group

69
Q

Nocebo Effect

A

-harm resulting from the mere expectation of harm
-ie. voodoo dolls

70
Q

Experimenter Expectancy Effect

A

-phenomenon in which researchers hypotheses lead them to unintentionally bias the outcome of a study
-usually in line with their expected hypothesis
-driven by confirmation bias

71
Q

Double-Blind

A

-a way to protect against experimenter expectancy effect
-neither researcher nor participants are aware of who’s in the experimental or control group

72
Q

Demand Characteristics

A

-cues that participants pick up from a study that allow them to generate guesses regarding the researchers hypotheses
-changes how they act based on their assumptions

73
Q

Preventing Demand Characteristics

A

-researchers often disguise the true purpose of a study until after the study has been completed

74
Q

Hawthorne Effect

A

-people’s knowledge that they are being studied changes their behaviour

75
Q

Tuskegee Study

A

-an unethical study
-for 40 years (from 1932-1972) the US Public Health Service diagnosed black men in a poor community in Alabama with Syphilis
-They had no idea they had it and infected women and children
-Eventually died
-Treatment was available at the time

76
Q

Belmont Report

A

-1979
-in response to Tuskegee study
-made guidelines about ethical research

77
Q

Findings of Belmont Report

A

Research should be:
-allow people to make decisions about themselves
-be beneficent
-distribute benefits and risks equally to all participants

78
Q

Informed Consent

A

-informing research participants of what is involved in a study before asking them to participate

79
Q

Educating Participants

A

-protect them from harm
-know what they are getting into
-non-technical language

80
Q

Freedom from Coercion

A

-you can’t bribe/coerce people to participate in a study
-especially if it’s harmful

81
Q

Risk-benefit analysis

A

-determine the risks and benefits
-is it worth it?
-are the risks too high?

82
Q

Statistics

A

-application of mathematic to describing and analyzing data

83
Q

Descriptive Statistics

A

-numerical characterization that describe data

84
Q

Central Tendency

A

-measure of the “central” scores in a data set
-where the group tends to cluster

85
Q

Variability

A

-measure of how loosely or tightly bunched scores are

86
Q

Mean

A

-average
-add up all numbers, divide by how many there are

87
Q

Median

A

-middle score in a data set
-measure of central tendency

88
Q

Mode

A

-most frequent score in a data set
-measure of central tendency

89
Q

Range

A

-a measure of variability
-difference between the highest and lowest scores

90
Q

Standard Deviation

A

-measure of variability
-average amount that an individual data point differs from the mean

91
Q

Inferential Statistics

A

-mathematical methods that allow us to determine whether we can generalize findings from our sample to the full population
-allows to determine if results are likely to occur due to chance

92
Q

Statistical Significance

A

-the probability that the findings are due to chance
-if they are statistically significant that means the results are unlikely to occur due to chance

93
Q

Practical Significance

A

-determination of whether the finding has any real world importance

94
Q

Peer Review

A

-process of quality control for research before it is published in an academic journal
-reviewers identify flaws that undermine the findings of a study

PSYC 104 - Introductory Psychology I (12 decks)

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