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Survey bias occurs when there are errors in the data collection process that systematically influence the results. This can happen due to multiple factors:

• Leading Questions: Questions that suggest a particular answer can sway respondents' answers.
• Non-response Bias: If certain people are more likely to respond than others, the survey results might not be representative of the entire population.
• Sampling Error: Errors that arise when the sample is not a perfect representation of the population.

In the given exercise, respondents answered the question posted online without any control over their selection, which could lead to various forms of survey bias.
Survey bias can make the results unreliable. It's crucial to design surveys carefully to minimize these biases, such as using random sampling and neutral wording for questions.

Selection bias occurs when the participants included in the study are not representative of the broader population. This happens when there's a systematic difference between those who are selected to participate and those who are not. In the exercise, the survey was filled out by Internet users who chose to respond. This group may differ in significant ways from those who didn’t respond.
Here are some factors contributing to selection bias:

• Voluntary Response: When participation is voluntary, it's often the case that only those with strong opinions or particular interests will partake.
• Exclusion Criteria: If a certain segment of the population is omitted from the sample, the results may not be applicable to the entire population.

The 52% 'yes' response in the exercise might not reflect the feelings of all Internet users, just those who felt strongly enough to respond. Researchers must ensure a random and comprehensive sample to avoid selection bias.

Self-selection occurs when individuals select themselves to be part of a survey or study. This can lead to biased results because those who choose to participate may share particular characteristics or opinions that are not representative of the entire population.
In the provided exercise, self-selection was evident as respondents were self-selected Internet users who chose to answer the survey. This can skew results in several ways:

• Motivation: Respondents might have had a personal interest or strong opinion about the question, making them more likely to respond.
• Availability: Only those who saw the survey and had time to respond participated, possibly omitting a significant portion of the population.

Self-selection can significantly affect the reliability and generalizability of study results. To counter self-selection bias, researchers often use random sampling and other techniques to ensure that the sample is representative of the population as a whole.