Data Flashcards

1
Q

What is meant by quantitive data?

A
  • data expressed numerically
  • data can be gained from scores in experiments e.g. number of words recalled
  • or from self report methods
  • uses closed questions
  • can be analysed statistically/easily converted into graphs
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2
Q

What is a strength of quantitative data?

A
  • easier to analyse
  • allows comparisons to be made within data to establish patterns + trends
  • easier to make conclusions abt bhv
  • WHEREAS qualitative is wordy + more difficult to statistically summarise so comparisons within data are harder to make
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3
Q

What is a weakness of quantitative data?

A
  • lacks depth + meaning to bhv
  • prevents ppts from being able to develop their thoughts, feelings and opinions
  • lacks vital detail
  • reduces int val
  • WHEREAS qualitative data is rich in detail providing a greater understanding of human bhv
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4
Q

What is meant by qualitative data?

A
  • expressed in words + descriptive data
  • written description of thought, feelings and opinions of ppts
  • from an interview
  • or open questions in a questionnaire
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5
Q

What is a strength of qualitative data?

A
  • lots of detail + depth
  • allows ppts to develop on thoughts, feelings and opinions
  • provides greater understanding of bhv
  • WHEREAS quantitative data lacks depth + meaning as data is numerical
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6
Q

What is a weakness of qualitative data?

A
  • harder to analyse
  • difficult to statistically summarise to establish patterns + trends
  • could lead to researcher bias as analysis is based on their own subjective interpretations
  • WHEREAS quantitative data can be analysed statistically to provide patterns + trends, so its easier to make objective conclusions abt bhv
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7
Q

What are the 3 levels of measurement?

A

Nominal
Ordinal
Interval

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8
Q

What is nominal level data?

A
  • categories
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9
Q

What is ordinal level data?

A
  • ranked scale
  • doesnt have equal intervals
  • subjective opinions
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10
Q

What is interval level data?

A
  • standardised measurement
  • objective (factual)
  • equal intervals
  • e.g. time, height
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11
Q

What is primary data?

A
  • collected first hand from ppts
  • specifically for aim of research
  • from an experiment, questionnaire or interview
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12
Q

What is a strength of primary data?

A
  • researchers are able to specifically target info they want
  • and organise exp in a way that suits the aim
  • as data is collected first hand from ppts specifically for aim of research
  • inc int val
  • WHEREAS secondary data might not meet direct needs of researcher, less useful
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13
Q

What is a weakness of primary data?

A
  • requires time and effort
  • as researchers obtain the data
  • and analyses results

WHEREAS secondary data is easily accessible, requires minimal effort, reducing time and costs

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14
Q

What is meant by secondary data?

A
  • data has been previously collected by another researcher or source (3rd party)
  • not specific for aim of study
  • then used by researcher
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15
Q

What is a strength of secondary data?

A
  • easily accessible + requires minimal effort to obtain
  • info researcher wants, might already exist
  • no need to collect primary data, reduces time + costs

-WHEREAS primary data takes time + effort to obtain and analyse data

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16
Q

What is a weakness of secondary data?

A
  • may be poor quality or have inaccuracies
  • could be outdates, incomplete or doesnt meet direct needs of researcher
  • WHEREAS primary data is collected 1st hand from ppts + specifically for aim of research, inc int val
17
Q

What is meant by meta - analysis?

A
  • form of research method that uses secondary data
  • gains data from a large number of studies
  • that have investigated the same research and used same methods
  • it combines all this info to make conclusions abt bhv
18
Q

What is a strength of a meta analysis?

A
  • it gathers data from multiple studies
  • so allows us to view data with much more confidence
  • inc generalisability of findings across larger populations
19
Q

What is a weakness of a meta analysis?

A
  • publication bias
  • researcher may not use all relevant studies
  • choosing to leave out studies with negative results
  • so data will be biased as it only represents some of the relevant data
  • incorrect conclusions are drawn