Introduction in survey data analysis
18 important questions on Introduction in survey data analysis
What are the six steps of the survey process?
2. Data collection.
3. Data editing.
4. Nonresponse correction.
5. Analysis.
6. Publication.
The first step in the survey proces is the survey design. What are five aspects that have to be addressed in defining a survey design?
2. The exact definition of the population that has to be investigated (the target population).
3. The specification of what has to be measured (the variables) and what has to be estimated (the population characteristics).
4. Where the sample is selected from (the sampling frame).
5. How the sample is selected (the sample design and the sample size).
What are non-observational errors?
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What are three categories of non-observational errors?
2. Sampling error: since just a part of the population is observed (also known as margin of error).
3. Nonresponse error: answer refusals.
What are four sources of non-observational erros?
1. the respondent (e.g. extreme response behaviour: socially desirable response behavior, overreporting/underreporting.
2. the interviewer (can influence respondent's responses)
3. the method of data collection
4. the measurement instrument: questions need to be clear.
Two types of inferences:
1) Of what can the characteristics of a respondent be inferenced?
2) What is inferenced from the characteristics of the sample?
2) From the characteristics of the sample, the characteristics of the populations are inferenced.
From measurement to representation: What kind of errors can be made in A - G?
B) Measurement error
C) Processing error
D) Coverage error
E) Sampling error
F) Nonresponse error
G) Adjustment error
What is a survey population?
What is a sampling frame?
What is important for a sampling frame?
What are two possible problems that influence the representability of the sampling frame?
2. Overcoverage: when the sampling frame contains elements that do not belong to the target population. If such elements end up in the sample and their data are used in the analysis, estimates of population parameters may be affected.
When is a sample representative?
What are characteristics of a probability sample?
2. The selection probability is known for elements in the sample (validity).
3. Pairs have a non-zero probability of being selected.
4. The selection probability for pairs is known for elements in the sample (accuracy).
What are disadvantages of sampling with replacement compared to sampling without replacement?
Sampling with replacement is inconvenient and not the standard.
What are properties of estimators?
Name four properties.
1. Expectation
2. Variance (precision)
3. Bias
4. Mean squared error.
What is the expectation of an estimator?
What is the mean squared error of an estimator?
How is the sampling design connected to an estimator?
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