Online surveys commonly suffer from which of the following?
A. poor reliability
B. self-selection
C. probability sampling
D. over-sampling
The Correct Answer and Explanation is :
The correct answer is B. self-selection.
Explanation:
Self-selection bias is a common issue in online surveys because participation is typically voluntary. Individuals who choose to respond often have strong opinions, personal stakes, or particular interests in the survey topic, making the sample unrepresentative of the broader population.
Why Self-Selection Happens:
- Voluntary Participation: Online surveys are often distributed via emails, social media, or websites, and participants decide whether to participate. Those with little interest in the topic may ignore the survey, while those with strong feelings are more likely to respond.
- Accessibility: Only individuals with access to the internet, knowledge of the survey, and motivation to complete it are included. This automatically excludes segments of the population that might differ in demographics or opinions.
Effects of Self-Selection:
Self-selection skews the results, as the data collected does not adequately reflect the diversity or proportionality of the entire target population. For instance, a survey about public transportation conducted online may disproportionately attract users who rely heavily on it, underrepresenting those who do not use public transportation at all.
Other Answer Options:
- A. Poor Reliability: While reliability can be an issue, it is not specific to online surveys. It depends more on survey design and question consistency.
- C. Probability Sampling: Online surveys rarely use probability sampling, but this is not a flaw; it’s a methodological choice.
- D. Over-sampling: This refers to including too many participants from a subgroup to ensure representation. Over-sampling can be intentional and beneficial if handled correctly.
In conclusion, self-selection bias undermines the validity of online surveys by distorting the sample’s representativeness, leading to potentially misleading or skewed results.