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Research Workshop Survey lecture notes

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These are lecture notes for the subject Research Workshop Survey taught at the University of Amsterdam for the course Communication Science.

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survey notes
week 1; errors — inference 1
survey
survey research is about producing statistics and drawing inferences
about a target population

advantages disadvantages

relatively low costs generally limited to scaled or check-list questions

relatively fast delivery no control over response rate

rapid data processing provides information more than understanding

can research large populations increasing public resistance

various modes: phone, mail, internet, face-to-face difficult to explore issues in depth

two inferences
we should be able to measure a certain attitude if we use proper questions
if we pull a proper sample we should assume the sample is representative to the population




survey notes 1

, errors
common sources of error in survey:

poorly worded questions

deviations from the script by the interviewer, mostly with face-to-face or phone
interviews

misunderstanding on the part of the interviewee

memory problems on the part of the interviewee

the way the information is recorded by the interviewer

the way the information is processed, either when answers are coded or when data are
entered into the computer



two types of error

random error: affects findings in unpredictable ways

systematic error: affects findings in predictable ways



error in sample: sample differs from error in question: answers don’t reflect variable
population
1. random = question invalidity
1. random = sampling error
differs only by chance = random
difference only by chance = variability / honest mistake in questions
random variability
2. bias (systematic) = question bias
2. biased (systematic) = sampling
social desirability bias
bias

can lead to overestimation of
the sample

only certain groups respond

question bias




survey notes 2

, difference in what is asked

objective facts

can be biased in one direction

error/validity can be measured bias

subjective states

can not be biased

validity can not be measured

—> validity = difference between answer and true score


level of bias:

bias at respondent level —> only for one

bias at aggregate level —> for everyone



designing questions
general rules

remember your research question

decide exactly what you want to find out

consider your audience

imagine yourself as a respondent ( would you answer the question?)



common mistakes

ambiguous terms ( often, frequently)

long questions

double barrelled questions



survey notes 3

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Uploaded on
September 19, 2023
Number of pages
28
Written in
2022/2023
Type
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Professor(s)
Matthijs mesman
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