6B Flashcards

1
Q

What is a sample in research?

A

A subset of cases from a larger population used to draw conclusions about that population.

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2
Q

What are the two key characteristics of a good sample?

A
  1. Large enough to provide reliable estimates.
  2. Representative enough to generalize findings.
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3
Q

What are the two core questions when recruiting a sample?

A
  1. How many cases should be recruited?
  2. How will these cases be selected?
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4
Q

What determines the required sample size?

A
  1. Effect size – Smaller effects require larger samples.
  2. Desired statistical power – Larger samples reduce the risk of missing a real effect.
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5
Q

Does the required sample size depend on population size?

A

No, sample size depends on effect size and statistical power, not on population size.

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6
Q

What is a convenience sample?

A

A sample based on availability, such as recruiting participants from friends, social media, or self-selected online polls.

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7
Q

What are the strengths and limitations of convenience sampling?

A

Strengths – Cheap, easy, allows larger sample sizes.

Limitations – Highly unrepresentative, difficult to generalize results.

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8
Q

What is quota sampling?

A

A method where researchers set quotas for certain characteristics (e.g., gender, political preference) to ensure representation in the sample.

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9
Q

What are the strengths and limitations of quota sampling?

A

Strengths – More representative than convenience sampling at a lower cost.

Limitations – Only ensures representativeness on chosen characteristics, requires knowledge of population distributions.

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10
Q

What is a probability sample?

A

A sample where all members of the population have an equal chance of selection, ensuring representativeness.

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11
Q

What are the strengths and limitations of probability sampling?

A

Strengths – Gold standard for representativeness.

Limitations – Expensive, requires a complete population register, affected by non-response bias.

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12
Q

What is non-response bias?

A

When certain groups systematically refuse to participate, making the sample unrepresentative (e.g., politically uninterested people are less likely to respond to election surveys).

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13
Q

What is weighting in survey research?

A

A statistical adjustment that assigns different weights to respondents to correct for underrepresentation of certain groups.

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14
Q

When should data be weighted?

A
  1. When analyzing mean levels (e.g., percentage of voters) rather than relationships.
  2. When examining variables affected by non-response bias (e.g., voter turnout).
  3. When using unrepresentative samples (e.g., convenience samples).
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15
Q

What is an example of data weighting?

A

If non-voters are underrepresented, their responses can be given higher statistical weight to better reflect the actual population.

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16
Q

What is a criticism of extreme data weighting?

A

If the original sample is highly unrepresentative, weighting may not fully correct for bias and can even introduce new biases.

17
Q

What are the three main survey modes?

A
  1. Structured interviews (in-person)
  2. Paper questionnaires (mail surveys)
  3. Web-based surveys (online surveys)
18
Q

What are the advantages and disadvantages of structured interviews?

A

Advantages – Allows clarification of questions, accessible to illiterate respondents.
Disadvantages – Expensive, time-consuming, risk of social desirability bias.

19
Q

What are the advantages and disadvantages of paper questionnaires?

A

Advantages – No interviewer bias, can reach offline populations.
Disadvantages – Expensive, inconvenient for respondents.

20
Q

What are the advantages and disadvantages of web-based surveys?

A

Advantages – Cheap, efficient, easy to administer.
Disadvantages – Excludes people without internet access (mostly elderly).

21
Q

Which survey mode is now the most common?

A

Web-based surveys – Research shows they produce results as reliable as traditional methods.

22
Q

What is an expert survey?

A

A survey where experts rate a topic instead of collecting responses from the general public.

23
Q

What are the strengths and limitations of expert surveys?

A

Strengths – Cost-effective, provides insight into topics where public surveys are impractical.
Limitations – Subjective, potential for bias, results can be circular.

24
Q

What is quantitative content analysis?

A

A method for systematically analyzing text or media by converting qualitative data into numerical data (coding).

25
Q

What are examples of sources used in content analysis?

A

Election manifestos, parliamentary speeches, newspaper articles, social media posts (e.g., tweets).

26
Q

What is coding in content analysis?

A

The process of assigning numerical values to pieces of text based on predefined categories.

27
Q

What are the two types of content analysis?

A
  1. Manual content analysis – Human coders classify text using a coding scheme.
  2. Automated content analysis – Computers analyze text using AI and machine learning.
28
Q

What is inter-coder reliability?

A

A measure of how consistently different coders classify the same content – a key quality criterion in manual content analysis.

29
Q

What is automated content analysis?

A

A computational method where a computer algorithm analyzes text, counts word occurrences, or applies machine learning to detect patterns.

30
Q

What are the advantages of automated content analysis?

A

Faster than manual coding, can analyze large datasets, can include advanced AI methods like sentiment analysis and topic modeling.

31
Q

What is web scraping in content analysis?

A

The process of automatically collecting large amounts of online content (e.g., all tweets from a political leader) for analysis.