Types Of Data Flashcards

(17 cards)

1
Q

What are the types of data

A

-Qualitative
-Quantitative
-Primary
-Secondary

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2
Q

What is qualitative data

A

-Detailed data that is expressed in words (non numerical)

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3
Q

What is quantitative data

A

Numerical data

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4
Q

What is primary data

A

First hand data collected for the purpose of the investigation

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5
Q

What is secondary data

A

-Collected by someone other than the person who is conducting the research

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6
Q

Example of secondary data

A

Government statistics like the census

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7
Q

Strengths of qualitative data

A

-Rich in detail so provides broader insights
-More meaningful

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8
Q

Weaknesses of qualitative data

A

-More difficult to analyse than quantitative data, making it hard to identify patterns and make comparisons
-More subjective interpretations are made and researcher bias- makes data less scientific.

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9
Q

Strengths of quantitative data

A
  • Easier to analyse- allows us to draw graphs and calculate average. Allows for easier comparisons between groups
    -More objective and scientific.
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10
Q

Weaknesses of quantitative data

A

-Doesn’t provide as much detailed and rich insights, limiting our understanding

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11
Q

Strengths of primary data

A

-Produces data that is directly relevant to research aims
-More reliable

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12
Q

Weaknesses of primary data

A

-More time consuming (have to design and collate)
-More effort
-More expensive

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13
Q

Strengths of secondary data

A

-Inexpensive and quick- desired information may already exist. No need to conduct research.
Minima effort

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14
Q

Weaknesses of secondary data

A

-May not be directly relevant to research aims
-Could be outdated
= potentially weaker validity

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15
Q

What is a meta analysis

A
  • A type of data that involves combining data from a large number of studies
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16
Q

Strengths of meta analysis

A

-Increases validity of conclusions- the eventual sample size is much bigger the individual samples. increases generalisability

17
Q

Weaknesses of met analysis

A

-Publication bias- researchers may not select all relevant studies, leaving out negative or no significant results= conclusions may lack validity