Lecture 2 Flashcards

1
Q

Experiments

A

IV has two or more levels, you manipulate it to see its effect on the DV

Most common

Can infer causality

Low ecology

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2
Q

Natural observation

A

Watch people in the field
Score their behaviour (or assess in some way)

No causality

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3
Q

Basic assumption for all research

A

Events are governed by some lawful order

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4
Q

The three goals of research

A

Measurement and description (How/why)
Understanding and prediction (How/what will happen)
Application (to help people usually)

If you divide people into two groups and have some play video games and some not, then measure spatial memory, you can describe the changes and caveats

Maybe another study could determine what part of the game accounted for the observed change

Could then predict changes in spatial memory caused by playing the game

Could maybe then prescribe game playing to help people improve spatial memory

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5
Q

Structure of a scientific paper

A

Introduction:
Theories, hypothesis

Methods:
Operational definitions
Acquisition of empirical evidence

Results:
Adherence to the scientific method
Precision
Analysis of empirical evidence

Discussion:
Openness - strengths/weaknesses, unexpected findings (good papers would be honest about this_
Willingness to reject hypothesis and draw correct conclusions (must be willing to say it did not work)

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6
Q

Theories

A

Organized systems of assumptions that aim to explain phenomena and their interrelationships
Should be referenced in the introduction of papers
Organize findings from prior research into a coherent set of ideas.

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7
Q

Hypotheses

A

Attempt to predict or account for something. specify relationships among variables and are explicitly tested
Should be explicitly stated in the intro of papers

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8
Q

Two sources of hypotheses

A

(a) theories
When a hypothesis is derived from a theory, it tests the theory. If the hypothesis is correct this adds supporting data to the theory (but does not prove it). When it is not, the theory must be revised.

(b) Personal experience

If this is for an experiment it is a formal statement that when X is changed this will cause Y to change (both in specific ways) or if there is no causation implied, that X and Y are related predictably.

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9
Q

Operational definitions

A

define terms in hypotheses by specifying the operations for observing and measuring the process or phenomenon

Relatively subjective: ie you define it

Can be very hard

Goes in method of papers

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10
Q

Random sampling/assignment

A

Randomly select people from the population

Randomly assign them to a condition

This way the chances of their being systematic differences between the groups are minimized as the differences should occur in both groups and so cancel out

A true random sample is representative of the population

By making the sample representative of the population, you allow the study to infer something about the population. If it is not, you cannot do this (or should not).

Unrepresentative samples may not apply to everyone.

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11
Q

Convenience sampling

A

Samples that are convenient to get.

Sometimes needed like in rare medical conditions

Often WEIRD which makes findings less generalizable

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12
Q

Skepticism

A

Do not accept ideas based on faith or authority

Do not assume everything was done correctly, treat every aspect of a study with caution.

Assess

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13
Q

Willingness to reject H1

Confirmation bias

A

Hard to do

Conformation bias: the tendency to look for or pay attention only to the things that are consistent with your own belief. Big issue with social media, big issue with data interpretation.

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14
Q

Karly Popper’s Critical Rationalism

Falsifiability

A

A scientific theory must make predictions specific enough to disconfirm the theory. It must predict what will and will not happen.

Often our impressions are wrong.

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15
Q

Example of confirmation bias & the importance of falsifiability: Prefrontal lobotomy

A
Egaz Moniz
Damage PFC
Treatment to schiz
Drops notable psychotic behaviors
Thought of as acceptable, got a Nobel
Controlled studies showed useless
Does not drop non-psychotic schiz symptoms
Drops DIRECTED behavior across board so psychotic directed behaviors (that is disturbing to others) drops but so does non-psychotic directed behavior (like dressing yourself).
Replaced with antipsychotics

Moniz hypothesized it would drop psych symptoms, then focused on the behaviors he wanted to see drop (psychotic one’s) and ignored those that did not confirm this belief. He did not define what changes in behavior might be negative.

If he had defined this better (eg said there would be no cognitive impairment), it would have been falsified. 20k were done.

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16
Q

What makes evidence empirical?

Reliability/Validity

A

What makes evidence empirical?

Evaluate measures based on reliability and validity

A test must be reliable to be valid but a reliable test can be invalid (if the test reliably measures an invalid construct).

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17
Q

Reliability

2 types

A

How consistent is the measurement?

80% is good

(1) test-retest reliability
Are scores similar from one session to another?
Sometimes one may improve if its the same test again and again.

(2) Alternate-forms reliability
Are scores similar on different forms of tests?

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18
Q

Correlational studies

A

Descriptive studies looking for relationships between phenomena

Correlation is a statistical measure of how strongly two variables are related to one another (between -1 and1)

Strengths: Can test predictions, evaluate theories and suggest new hypotheses

CANNOT INFER CAUSALITY

Although often reported that way both in the media and in sloppy discussions

Often shown as scatter diagrams
Stronger correlations yield better predictive power

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19
Q

Random selection of ptps from the population

A

Key for generalizability
Not always possible, aim for it
If not, say so in discussion

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20
Q

Random assignment of ptps

A

To each group
Experiment/control
Give placebos to account for placebo effect (as everyone thinks they have the drug)

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21
Q

Confounds

A

Any difference between the experimental and control group, other than the IV

22
Q

Cause and effect

A

Possible to infer with random assignment and manipulation of IV

23
Q

Placebo effect

A

improvement resulting from the mere expectation of improvement

Subjects must be BLIND; unsure if they are in the experimental or control group

Placebo show many of the same characteristics of real drugs

24
Q

Nocebo effect

A

Harm resulting from the mere expectation of harm,

Women perform worse at math after told women perform badly on the test

25
Q

Experiments

strength/weakness

A

Can establish causality

Can be confounded

Involves variables of interest, IV and DV, control conditions and random assignment

26
Q

Hindsight bias

A

“I knew it all along”

tendency to overestimate how well we could have forecasted a known outcome

27
Q

Overconfidence

A

Our tendency to overestimate our ability to make predictions

28
Q

Experimenter expectancy effect

A

Phenomenon where researchers hypotheses lead them to unintentionally bias a study outcome

29
Q

Example: Facilitated communication

Experimenter effect

A

“revolutionary” treatment for autism
Bikiken thought it was a movement disorder
Sat with autistic child and helped them type
Students made huge progress in communication
Loads of sexual abuse claims which their families denied and were not experienced by their siblings
Turns out, words came from the experimenter
Experimenter wanted it to work, made it work, like a ouiji board

Still done somewhere: VERY hard to get published results out the the publics mind (same with autism vaccine)

30
Q

Hawthorne effect

A

participants knowledge they are being observed changes their behavior

31
Q

Demand charecteristics

A

Cues ptps pick up that allow them to generate guesses of H1

32
Q

How to avoid Hawthorne and demand effects

A

Covert observation (watch without them knowing - ethically challenging)

Experimenter blindness (they do not know which group is which)

33
Q

Double blind design

A

Researchers and ptps do not know what group is what

34
Q

Normal distribution

A

68% are within 1SD

95% within 2

35
Q

Measures of central tendancy and standard deviation

A

Mean, median and mode are the same in a normal distribution.

If the mean is greater than the mode, the distribution is positively skewed.
If the mean is less than the mode, the distribution is negatively skewed.
If the mean is greater than the median, the distribution is positively skewed.
If the mean is less than the median, the distribution is negatively skewed.

SD, how scores are distributed around the mean

36
Q

Inferential statistics: Significance tests

P

A

How likely is it that the study’s results appeared by chance

If NOT by chance, attributed to your manipulation

P,.05 is a convention in psyc

Means 1/20 chance this happened randomly

37
Q

Effect size

A

Effect size is the amount of variance among scores in the study accounted for by the IV

If it is low, small effect

If it accounts for only 1%, do we care? Maybe but that must be reported so people can interpret the thing fully.

38
Q

Misuse of statistics (2 things)

A

Reporting significant results with small effect sizes
(many journals require effect sizes now)

If the distribution is not normal (ie skewed) you cannot use normal dependent statistics to analyze it. You must use stats that account for this

Truncated graphs (that do not start at zero) used to make tiny effects look significant

39
Q

Interpretation of statistics

A

Examine whether the sample is representative before drawing conclusions

Mention ALL results (even those that do not support)

Compare honestly to prior research, if the data disagrees, say so

Discuss limitations and what should be done in future to build on this based on results

40
Q

Cover story

A

mild deception, designed to stop ptps from guessing H1

41
Q

Continuous variables

A

Spectrum, if numerical can be quantitative variables

42
Q

Discrete variables

A

One or the other

If named, categorical/qualitative

43
Q

Indepdenat groups/in-between subjects

A

Different groups

44
Q

Repeated measures/between subjects

A

Same people at different times

45
Q

Stimulus variable

A

If the IV exposed someone to a stimulus, it is a stimulus variable

46
Q

Response variable

A

If the IV exposed someone to a stimulus, it is a stimulus variable and the DV is a response variable

47
Q

Manipulation check

A

is the IV in the right levels in the experimental condition (IE does your manipulation change the IV as you want it to)

48
Q

Quasi experiments

A

IV not manipulated

e.g. one group is male, the other female

Similar to experiments but because the UV is not manipulated, harder to infer causality

49
Q

Content validity

A

(1) Content Validity
Do the items broadly represent the trait in question?
If they miss aspects of the trait, they are invalid, must not focus on only one aspect.

50
Q

Criterion Validity

A

(2) Criterion Validity
Do the tests results predict other measures of the trait?
Compare to other validated ways of assessing the trait. What are the results?