different ways to analyse data, study's, etc Flashcards

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1
Q

meta analysis

A

-method of analysis data which produces an effect size
-examines data from a number of independent studies in the same subject to determine overall trends

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2
Q

effect size

A

quantitative measure of studies effect

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3
Q

case study

A

the detailed study of a single individual, institution or event using info from a range of sources e.g. family friends or person concerned

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4
Q

longitudinal (case studies)

A

follow group over extended amount of time

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5
Q

content analysis

A

-the analysis of the content of something e.g. gender content in magazines

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6
Q

what observation is content analysis

A

indirect, observing the individual from the artifacts they produce e.g songs, books, paintings

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7
Q

meta analysis strengths

A

-reviewing from range of studies increases validity
-reduces contrast in studies by producing statistics

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8
Q

meta analysis weaknesses

A

-research designs in diff studies may vary meaning u cant truly compare them
-so arent always valid

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9
Q

case study strengths

A

-rich in depth data
-overlooked data likely to be identified
-used incases where experiments arent ethical e.g how respond to certain events

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10
Q

case study weaknesses

A

-difficult to generalise data
-as it is identified after the event we cannot be sure the apparent changed weren’t present originally

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11
Q

content analysis strengths

A

-based on what people actually do, real communications that are current and relevant
-high ecological validity
-when sources are obtained, findings can be replicated

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12
Q

content analysis weaknesses

A
  • observer bias may reduce objectivity and validity of findings
    -diff observers interpret the meaning of behavioural categories differently (e.g anger)
    -lack internal validity
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13
Q

types of extraneous variables

A

demand characteristics, investigator effects, situational variables, participant variables

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14
Q

demand characteristics

A

if participant knows/guesses the experiment and changes their behaviour

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15
Q

investigator effects

A

any aspect of the researcher’s behaviour, appearance or gender that could affect participant responses

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16
Q

situational variables

A

features of a research situation that may influence participants behaviour e.g. order effects, heat, time of day

17
Q

participant variables

A

differences between participants (e.g. IQ, age)

18
Q

confounding variable (not extraneous)

A

variables that interfere with the effect of the IV and the DV

19
Q

extraneous variable

A

variable that only effects the DV