Content and Thematic analysis- RESEARCH METHODS Flashcards

RESEARCH METHODS

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1
Q

Primary data

A
  • Psychologist collects data firsthand from participants directly
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2
Q

Evaluation of Primary data

A

STRENGTH:
- Fits your hypothesis
- Be sure of controlling extraneous variables

Weakness:
- Time- consuming

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3
Q

Secondary data

A
  • Existing sources of data collected by the researcher
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4
Q

Evaluation of Secondary data

A

STRENGTH:
- Less- time consuming

Weakness:
- Might not fit hypothesis
- Might not control extraneous variables

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5
Q

Qualitative data

A

Data is words/ descriptions

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6
Q

Evaluation of Qualitative Data

A

STRENGTH:
- More depth

Weakness:
- It is harder to analyse (than quantitative data)

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7
Q

Quantitative Data

A

Data is numbers

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8
Q

Evaluation of Quantitative data

A

STRENGTH:
- It is easy to analyse (than qualitative data)

Weakness:
- Lacks depth

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9
Q

Content Analysis

A
  • Research tool used to indirectly observe the presence of any recorded communication (media)
  • It is a method of analysing qualitative data

General steps when conducting a content analysis:
Choose a sampling method (event or time)
1. Read through the data
2. Make notes on emerging themes and write behavioural categories
3. Read through the data again
4. Count the instances of each category (quantitative)

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10
Q

Evaluation of a content analysis

A

ADVANTAGE:
- Once you’ve carried out content analysis- allows you to identify patterns and make comparisons
- Ethical to investigate things that may otherwise be public
- Good ecological validity- real- world data
- More reliable than thematic analysis- less subjective

DISADVANTAGE:
- Lose depth and explanations behind behaviour

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11
Q

Thematic analysis

A
  • Method of qualitatively analysing data

General steps when conducting a thematic analysis:
- Read the data and try to understand the meaning
- Make note of the emergent themes
- Describe/ report on the themes

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12
Q

Evaluation of Thematic analysis

A

ADVANTAGES:
- Ethical to investigate things that may otherwise be public
- Good ecological validity- real- world data
- Keep the detail and explanations behind behaviours while able to see patterns

DISADVANTAGES:
- Can become more subjective- bring own expectations to data- research is biased

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