Question
Which of the following scenarios would produce an appropriate sample for a cause-and-effect conclusion about the relationship between two variables? Assume the population of interest is Houston residents.
Option #1: sampling the first 20 customers who walk into a shopping mall on a Saturday
Option #2: sampling every member of a local yoga studio
Option #3: sampling staff and students from ten local schools
(1 point)
Option #
would produce an appropriate sample.
Option #1: sampling the first 20 customers who walk into a shopping mall on a Saturday
Option #2: sampling every member of a local yoga studio
Option #3: sampling staff and students from ten local schools
(1 point)
Option #
would produce an appropriate sample.
Answers
Answered by
GPT-4o mini
None of the provided options would produce an appropriate sample for a cause-and-effect conclusion about the relationship between two variables in the population of Houston residents.
All options suffer from sampling biases:
- **Option #1**: Sampling the first 20 customers at a shopping mall likely introduces selection bias, as the sample may only represent certain demographics that frequent the mall on a Saturday.
- **Option #2**: Sampling every member of a local yoga studio would likely miss out on many residents who do not participate in yoga, leading to a non-representative sample of the broader population.
- **Option #3**: Sampling staff and students from ten local schools would focus on a specific demographic (students and school staff) and not represent the overall population of Houston residents.
To establish a cause-and-effect relationship, it's essential to use a random sample that accurately reflects the diversity and characteristics of the entire population of interest. Hence, none of these options are suitable for the requirement.
All options suffer from sampling biases:
- **Option #1**: Sampling the first 20 customers at a shopping mall likely introduces selection bias, as the sample may only represent certain demographics that frequent the mall on a Saturday.
- **Option #2**: Sampling every member of a local yoga studio would likely miss out on many residents who do not participate in yoga, leading to a non-representative sample of the broader population.
- **Option #3**: Sampling staff and students from ten local schools would focus on a specific demographic (students and school staff) and not represent the overall population of Houston residents.
To establish a cause-and-effect relationship, it's essential to use a random sample that accurately reflects the diversity and characteristics of the entire population of interest. Hence, none of these options are suitable for the requirement.