Research Methods/Statistics Flashcards

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1
Q

Describe tenacity.

A

Belief-based explanations
– “It is the way it is because I SAY SO”
– “Everyone knows it is true” (False consensus effect)

Tenacious beliefs are extremely resistant to modification
by evidence.

Examples:
•Ghosts, validity of horoscopes, concept of luckiness,
superstitions.
•Gender, racial, disability stereotypes

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2
Q

Describe authoritative methods of belief.

A

“It is the way it is because HE SAYS SO”
• Accepting something as true simply because someone in a position of authority says it is true.
• Examples: Parents, Respected elders, Media, Governments, Religions, Lecturers etc.

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3
Q

Describe belief through pure reason.

A

“It is the way it is because it logically must be that way”
• A priori method

Advantages: Social contracts, laws etc.
which do not stem from empirical evidence
Disadvantages: Inability to resolve
arguments when they occur

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4
Q

Describe the scientific method belief.

A

Conclusions should be based on
evidence which is:
• Empirical: information gathered from experience, observation, experimentation.
• Objective: information gathered is free from bias.

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5
Q

What is a pseudoscience?

A

a claim, belief or practise which is presented as scientific, but does not adhere to a valid scientific method, lacks supporting evidence or plausibility, cannot be reliably tested, or otherwise lacks scientific status
– Characterized by the use of vague, contradictory,
exaggerated or un-testable claims

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6
Q

What was the psychoanalyst movement?

A

Based on introspection.

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7
Q

What was the behaviourist movement?

A

Based on observable behaviour.

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8
Q

What is the cognitive movement?

A

Don’t need direct observation, make predictions and subject them to empirical verification.

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9
Q

What is induction?

A

evidence is gathered from multiple observations

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10
Q

Describe Karl Poppers falsifiable theory.

A

Science starts with theories which are subject to scrutiny
• If the evidence contradicts our theory, we formulate an
alternative
• If the evidence supports our theory, we regard it is an
undefeated theory

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11
Q

What is Bayesianism?

A

Bayesians – beliefs come in degrees
• The likelihood of future events can be expressed on
the basis of past knowledge
– e.g. it is likely that 90% of 1st Years will pass PSYC10100
• Revise probability predictions when faced with
evidence in support or against your theory
• Provides a measure of a state of knowledge

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12
Q

What is the Hypothetico-Deductive Method?

A

observation - theory - hypothesis - empirical tests - results

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13
Q

What is Methodological pluralism?

A

Use of multiple methods.

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14
Q

What is Methodological triangulation?

A

convergence of the findings of methodologically varying studies can lend credence to the theory pattern

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15
Q

What does Parsimonious mean?

A

Is the explanation the simplest possible?

Occam’s razor

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16
Q

What is a construct?

A

Theoretical concepts formulated to serve as
causal or descriptive explanations
– e.g. Psychosis: a mental state characterised by a
“loss of contact with reality” (DSM IV)
• Don’t directly indicate a means by which they can be
measured

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17
Q

What is the difference between a construct and a variable?

A

Constructs defined by theoretical definitions
– e.g.: Psychosis: a mental state characterised by a
“loss of contact with reality”
• Variables defined by operational definitions
– e.g.: contact with reality “defined” by a score on a
questionnaire

• Constructs defined by theoretical definitions
– e.g.: Intelligence: The capacity to acquire and apply
knowledge; the faculty of thought and reason
• Variables defined by operational definitions
– e.g.: score on a standardised test of intelligence (for
example, the Wechsler Intelligence Scale)

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18
Q

What is nominal data?

A

Categorical.

e.g. gender, political party, religion

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19
Q

What is orbital data?

A

ranked or ordered.
data can be ranked along a continuum
intervals between ranks are not equal
e.g. race positions, attractiveness

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20
Q

What is interval data?

A

• intervals between successive values are
equal
• but no ‘true’ zero point
•e.g. temperature, shoe size

21
Q

What is ratio data?

A
  • highest level of data
  • equal intervals and a true zero point
  • e.g. height, distance.
22
Q

What is Between-subjects design/cross-sectional?

A

participants each exposed to one level of the IV

23
Q

What is a within subjects design/longitudal?

A

participants exposed to all levels of the IV

24
Q

What is a mixed design?

A

mixture of between and within

25
Q

Describe counterbalancing.

A

Split the group of participants in half (A and B)
– Group A can participate in Level 1 then Level 2
– Group B can participate in Level 2 then Level 1

Order effects will still influence Ps
performance, but the effect of that influence will
be evenly spread across each level of the IV

26
Q

What are Factorial Designs?

A

• Experimental designs with 2 or more IVs

27
Q

What are True experimental designs?

A

experimenter has complete control over the assignment of participants to experimental conditions.

e.g.: Assign participants to groups that consume different
amounts of alcohol: no alcohol vs. 10 units of alcohol

28
Q

What are Quasi-experimental designs?

A

the assignment of participants to experimental conditions is predetermined

– e.g.: compare pre-existing alcohol consumption groups:
alcoholics vs. non-alcoholics

29
Q

Why pick between/within subjects?

A

Between subjects – eliminate order effects

Within subjects – eliminate individual difference effects

30
Q

What is a problem using between subjects?

A

it’s not possible to randomly assign Ps.

Solve by matching.

31
Q

What is a problem with Within subjects?

A

it’s not possible to counterbalance order.

Solve by control group.

32
Q

What are the types of measurement errors?

A

Random errors obscure the results

Constant errors bias the results

33
Q

What are confounding variables?

A

extraneous variables that disproportionately affect one level of the IV more than the other levels.

Confounding variables introduce a threat to the internal validity of our experiments
– Random allocation/counterbalancing spreads the influence of extraneous variables (so that they do not become confounding variables)

34
Q

How can confounding variables effect our results?

A

an effect of the IV on the DV when it is not present

– no effect of the IV on the DV when it is present

35
Q

What can be a threat to internal validity?

A

– Selection
Bias resulting from the selection or assignment of participants to different levels of the IV
– History
Uncontrolled events that take place between testing occasions.
– Maturation
• Intrinsic changes in the characteristics of
participants between different test occasions.
– Instrumentation
Changes in the sensitivity or reliability of
measurement instruments during the course of the
study.

36
Q

Describe reactivity.

A

awareness that they are being observed may alter Ps behaviour

37
Q

What is the difference between precision and accuracy?

A

Precision: exactness (consistency)
Accuracy: correctness (truthfulness)

38
Q

What is the difference between reliability and consistency?

A

Reliability: precision (consistency)
– The extent to which our measure would
provide the same results under the same
conditions

• Validity: accuracy (truthfulness)
– The extent to which it is measuring the
construct we are interested in

39
Q

Describe forms of reliability.

A

Test-retest reliability: measures fluctuations
from one time to another
– If we administered our measure to the same
participants on separate occasions, would we
obtain the same results?

Inter-rater reliability: measures fluctuations
between observers
– If two different raters/observers measured the
variable of interest, would they obtain the same
results?

Parallel forms reliability
– If we administer different versions of our
measure to the same participants, would we
obtain the same results?

Split-half Reliability (internal consistency)
If you randomly split the questions into two
halves do both halves give the same result.

40
Q

Describe forms of validity.

A

Content Validity: Does our test measure the construct fully?
– e.g. the RM exam should cover knowledge of
quantitative and qualitative methods

Face Validity: Does it look like a good test?
– e.g. do the questions in the RM exam reflect the
RM knowledge students should have learnt?

Criterion Validity: Does the measure given results which are in agreement with other measures of the same thing?

– e.g. do RM exam scores relate to lab grades?
• Concurrent: comparison of new test with
established test
• Predictive: does the test predict outcome on
another variable

41
Q

What are the tests of construct validity?

A

Convergent validity: correlates with tests of related
constructs

Discriminant validity: doesn’t correlate with tests of
different constructs

42
Q

What are the types of sampling?

A
Random sample
– the gold standard
– each member of the population has an equal
chance of being selected
– usually quasi-random

• Systematic
– draw from the population at fixed intervals
– problematic in populations with a periodic function.

Stratified sample
– Proportional: specified groups appear in numbers
proportional to their size in the population
– Disproportional: specified groups which are not
equally represented in the population ,are selected
in equal proportions

• Cluster sample
– researcher samples an entire group or cluster from
the population of interest.

Opportunity/Convenience sample
– people who are easily available
– but can lead to a biased sample

• Snowball sampling
– recruit small number of participants and then use
those initial contacts to recruit further participants
– biases the sample, but useful if you want to recruit
very specific populations

43
Q

What is Population validity?

A

is our sample representative?

44
Q

What is Ecological validity?

A

does the behaviour measured reflect naturally occurring behaviour?

45
Q

Describe independent measures design.

A

Independent measures involves using two separate groups of participants; one in each condition.

Pro: Avoids order effects (such as practice or fatigue) as people participate in one condition only. If a person is involved in several conditions they may become bored, tired and fed up by the time they come to the second condition, or becoming wise to the requirements of the experiment!

Con: More people are needed than with the repeated measures design (i.e. more time consuming).

Con: Differences between participants in the groups may affect results, for example; variations in age, sex or social background. These differences are known as participant variables (i.e. a type of extraneous variable).

46
Q

Describe repeated measures design.

A

The same participants take part in each condition of the independent variable. This means that each condition of the experiment includes the same group of participants.

Pro: Fewer people are needed as they take part in all conditions (i.e. saves time)

Con: There may be order effects. Order effects refer to the order of the conditions having an effect on the participants’ behavior. Performance in the second condition may be better because the participants know what to do (i.e. practice effect). Or their performance might be worse in the second condition because they are tired (i.e. fatigue effect).

Counterbalancing.

47
Q

Describe matched pairs design.

A

Each condition uses different participants, but they are matched in terms of certain characteristics, e.g. sex, age, intelligence etc.
One pair must be randomly assigned to the experimental group and the other to the control group.

Pro: Reduces participant (i.e. extraneous) variables because the researcher has tried to pair up the participants so that each condition has people with similar abilities and characteristics.

Pro: Avoids order effects, and so counterbalancing is not necessary.

Con: Very time-consuming trying to find closely matched pairs.

Con: Impossible to match people exactly, unless identical twins!

48
Q

What is face validity?

A

Face validity is simply whether the test appears (at face value) to measure what it claims to.