research methods eval Flashcards

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1
Q

what are the strengths of lab experiments

A
well controlled (extraneous/confounding variables are minimised) results in higher internal validity
can easily be replicated
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2
Q

what are the limitations of lab experiments

A

Demand Characteristics
Ethics - deception is often used, making informed consent difficult.
Artificial - lacks ecological validity

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3
Q

what are the strengths of field experiments

A

higher mundane realism
ecological validity- field experiments are less artificial
Participants are not usually aware of being studied so less likely for demand characteristics to appear.

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4
Q

what are the limitations of field experiments

A

less control of confounding/extraneous variables - reduces internal validity
more time consuming
more expensive
ethics - often can’t be debriefed.

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5
Q

what are the strengths of natural experiment

A

allows research where IV can’t be manipulated for ethical or practical reasons.
enables psychologists to study “real” problems.
high ecological validity - less artificial
demand characteristics - participants might not know they’re in a study so their behaviour is more natural.

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6
Q

what are the limitations of natural experiments

A

cannot demonstrate causal relationships because IV is not directly manipulated.
random allocation may not be possible

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7
Q

what are the strengths of quasi-experiments

A

allows comparisons between types of people

high ecological validity - often less artificial than lab experiments.

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8
Q

what are the limitations of quasi-experiments

A
  1. Participants may be aware of being observed causing demand characteristics reducing the internal validity of the study.
  2. The dependent variable may be a fairly artificial task, reducing mundane realism.
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9
Q

What are the strengths of naturalistic observation?

A

gives a realistic picture of spontaneous behaviour.

high ecological validity

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10
Q

What are the limitations of naturalistic observation?

A

has little control

observer bias

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11
Q

What are the strengths of participant observation?

A

may provide special insights into behaviour from the “inside” that may not otherwise be gained

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12
Q

What are the strengths of opportunity sampling?

A
  • easiest method

- less time to locate your sample

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13
Q

What are the limitations of opportunity sampling?

A
  • ## inevitably biased since the sample is taken from a small population.
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14
Q

What are the strengths of random sampling?

A

Unbiased- since all members have an equal chance of being chosen

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15
Q

What are the limitations of random sampling?

A

Time consuming

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16
Q

What are the strengths of stratified sampling?

A
  • likely to be more representative than other methods
17
Q

What are the limitations of stratified sampling?

A

Very time consuming to identify subgroups then contact them

18
Q

What are the strengths of systematic sampling?

A

Unbiased since they’re selected from an objective system

19
Q

What are the limitations of systematic sampling?

A

Not truly unbiased unless selected using a random method.

20
Q

What are the strengths of volunteer sampling?

A

Gives access to a variety of participants, which might make it more representative.

21
Q

What are the limitations of volunteer sampling?

A

participants could be more motivated or need the reward after the experiment (e.g money) which results in volunteer bias.

22
Q

evaluate the mean as a measure of central tendency

A
  1. It’s the most sensitive as it takes into account the exact measure of distance between all the values of all the data.
  2. being the most sensitive means that it can easily be distorted by one or a few outliers
  3. it can’t be used for nominal data
  4. doesn’t make sense to use when you have discrete values e.g no.of legs
23
Q

evaluate the median as a measure of central tendency

A
  1. not affected by outliers.
  2. appropriate for ordinal data
  3. it can be easier to calculate than the mean
  4. not as sensitive as the mean since the exact values aren’t reflected in the final calculation
24
Q

evaluate the mode as a measure of central tendency

A
  1. unaffected by outliers
  2. much more useful for discrete data
  3. only method that can be used for nominal data.
  4. not useful when there are several modes.
  5. it tells us nothing. about the other values of the distribution