A pollster randomly selects 100 people from each town in a certain candidate’s district to see if they support the candidate. Why might this survey not produce a good sample?

This survey might not produce a good sample for a few reasons:

1. Sample size: The sample size of 100 people from each town might not be sufficient to represent the entire district accurately. The district could have a much larger population, and a smaller sample size may not capture the diversity of opinions.

2. Random selection: While the pollster claims to select people randomly, there could still be bias introduced in the selection process. For example, if the pollster only selects people from certain neighborhoods or areas within each town, it may not be truly random and may not reflect the overall population's opinions.

3. Non-response bias: Even if the random selection process is followed, some people may choose not to participate in the survey. This non-response bias can affect the representativeness of the sample if the characteristics of those who choose not to respond differ significantly from those who participate.

4. Self-selection bias: Those who choose to participate in the survey might have different characteristics or opinions compared to those who do not participate. This self-selection bias can introduce skewness into the results and make them less reliable.

5. Homogeneity of towns: If the towns in the district are very similar in terms of demographics, socioeconomic factors, or political leanings, the survey may not capture the full diversity of opinions in the district.

To improve the survey's representativeness and validity, a larger sample size could be considered, ensuring a truly random selection process, implementing measures to reduce non-response bias, and accounting for the potential socio-demographic differences across the towns within the district.

What about people who don't live in a town, but live in the country?