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AP psychology chapter 2 Flashcards

1
Q

Hindsight bias

A

After hearing about something, people believed they knew it all along.

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2
Q

Applied research

A

Research that has real, practical applications, e.g testing efficacy of smoking addiction programs.

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3
Q

Basic research

A

Research about something interesting but with no real world application, used as basis for applied research (e.g studying how people form attitudes about others.

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4
Q

Valid

A

The research is accurate, represents/measures what the researcher set out to measure.

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5
Q

Reliable

A

The research is internally consistent.

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6
Q

Standardized

A

Tests produce the same results after many administrations.

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7
Q

Sample

A

A group of participants.

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8
Q

Sampling

A

Decides who or what to study to investigate a hypothesis. Must identify population first.

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9
Q

Population

A

Anyone or anything that could have been selected.

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10
Q

Theory

A

Aims to explain a phenomenon, used to generate a testable hypothesis.

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11
Q

Operational definition

A

The way a variable is measured (e.g surveys, self report inventories, kilometres, etc.

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12
Q

Random sampling

A

Selecting random subjects from all possible participants, ensures sample is a representative of the general population and that all have an equal chance of being selected.

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13
Q

Stratified sampling

A

Each member of the larger population is categorized into another subset based on characteristics. For example, age, gender. Allows researcher to ensure that the sample accurately represents the population on a specific criteria.

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14
Q

Representative sample

A

A sample that accurately represents the population on a specific criteria. E.g in a population with 200 Chinese, 500 African Americans, and 300 latinos, a representative sample would in life 20 Chinese, 50 African Americans, and 30 latinos.

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15
Q

Lab experiments

A

Conducted in labs - highly controlled environments. Conditions are controlled.

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16
Q

Field experiments

A

Conducted out in the world, more realistic.

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17
Q

Confounding variables

A

An unmeasured variable that may cause a difference between the experimental conditions and control conditions; will likely affect the independent variable.

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18
Q

Participant-relevant confounding variables

A

Any differences amongst participants that may skew results, e.g education; random assignment limits this.

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19
Q

Situation relavent confounding variables

A

Differences in experimental environment that can impact results, e.g time of day; limited by group matching.

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20
Q

Assignment

A

Comes after sampling, participants, after being chosen, are put into either the experimental or control group.

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21
Q

Random assignment

A

Each participant has an equal chance of being placed in any group, limits participant relevant founding variables.

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22
Q

Group matching

A

Could be used to make sure the 2 similar groups are similar on some criteria (such as sex, age, iq), minimizes situation relavent variables.

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23
Q

Experimenter bias

A

A type of situation relavent confounding variable when the researcher subconsciously treats participants differently to support their hypothesis.

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24
Q

Double-blind procedure

A

Prevents experimenter bias, in which neither researchers nor participants can interact/affect outcome of research.

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25
Single-blind procedure
Only the participants don’t know which group they are in, minimizes affects of demand characteristics and response/participant bias.
26
Response or participant biases
Tendency for participants to consciously or unconsciously respond/behave in a certain way. One kind is social desirability.
27
Demand characteristics
Cues about the purpose of the study, which may influence participant responses.
28
Social desirability
The tendency for participants to give answers that reflect well on themselves.
29
Hawthorne effect
When participants try to change or improve their behaviour because they know it is being evaluated or studied.
30
Placebo method
A method of control. Allows researchers to separate psychological effects of drugs from physiological.
31
Counterbalancing
Participants can be their own control group.
32
Correlation method
Expressed a relationship between two variables without ascribing a cause.
33
Positive correlation
The presence of something predicts the presence of something else.
34
Negative correlation
The presence of something predicts the absence of something else.
35
Ex Post facto study
When an investigation occurs after a fact has occurred.
36
Survey method
Asks participants to fill out surveys, can only prove a correlation, no independent or dependant variables, lots of confounding variables.
37
Naturalistic observation
Observed participants in natural settings with no interaction, obtains more realistic image of participant behaviour, no control.
38
Case study method
Gets a fuller and more detailed picture of one of a small group of participants. Findings can’t be generalized, often used by clinical psychologists.
39
Descriptive statistics
Describes a set of data using methods like frequency distribution, states facts and proven outcomes from a population
40
Frequency distribution
A representation in either graph or table form that displays the number of observations within a given interval. Has two types: frequency polygons or histograms, y is frequency, x is whatever is being graphed.
41
Frequency polygons
Line graphs.
42
Histograms
Bar graphs.
43
Measures of central tendency
Attempts to mark the center of distribution, mean, median, and mode (scores that appear the most).
44
Outliers
Extreme scores that skew distribution.
45
Positive skew
More low scores than high, the mean is higher than the median, median is towards the left.
46
Negative skew
More high scores than low, the median is higher than the mean, median is towards the right.
47
Measures of variability
Other types of statistical measures, range, standard deviation, variance.
48
Range
High to lowest score.
49
Variance/standard deviation
The average distance of any score from the mean; the higher they are, the more spread out the distribution. Standard deviation is sqrt2 of variance.
50
Measures of variability
Tries to show the diversity of distribution.
51
z-score
Distance of any score from the mean in units of standard deviation. Calculated using z = (x-y)/σ (x = score, y = mean, σ = standard deviation).
52
Normal curve
A theoretical bell-shaped curve for which the area under the curve between any 2 z-scores has been predetermined. Around 68% of scores in a normal distribution fall within 1 standard deviation of the mean (both positive and negative), 95% in 2 deviations, and 99% in 3 deviations.
53
Correlation coefficient
Determines strength of correlation. -1 = perfect negative correlation. 0 = no correlation.
54
Scatter plot
Graphs correlations.
55
Line of best fit/regression line
A line drawn that minimizes the distance of all the points in a scatter plot.
56
Inferential statistics
Analyze samplings to see if they can be applied to everyone in a larger population.
57
Sampling error
Occurs when an analyst does not select a sample that represents the entire population of data.
58
Inferential statistics tests
t-tests, chi-squares, and ANOVAs, which all yield a p-value.
59
p-value
The probability of differences due to change, represents the significance of findings.
60
Statistical significance
A p-value of 0.05 is the cutoff for statistically significant results, which means that there is a 5% chance that the results occurred due to chance, and can also be computed for correlation coefficient.
61
Institutional Review Board (IRB)
Any research must first be proposed to the IRB, which checks for ethical violations and procedural errors.
62
Coercion
No coercion for human participants, only volunteers.
63
Informed consent
Doesn't mean no deception, but deception must be similar to actual experiment.
64
Anonymity/confidentiality
Anonymity preferred.
65
Debriefing
After, participants should be told of the purpose of the study as well as the ways to get results.

Psychology (12 decks)

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