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Based on the question and the provided table, here is how the fields should be defined:

1. **Population**: The entire group of individuals the study is aiming to understand.  
   **Answer**: All parents of children in the school district.  

2. **Sample**: The subset of the population that was selected and evaluated.  
   **Answer**: The 100 parents who were surveyed.  

3. **Parameter**: The numerical summary describing the population. Since the parameter is not fully known (it's the entire population's true approval rate), we would instead consider it to be **the proportion of all parents who approve of their child's teacher**.  

The **89%** approval rating refers to a statistic derived from the sample, not the parameter.  

Would you like further clarification or details about this solution?

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### Related Questions
1. What is the difference between a population and a sample in statistics?
2. How is a statistic different from a parameter in a study?
3. What methods can be used to ensure a representative sample is collected?
4. Why might the sample approval rate differ from the actual population approval rate?
5. How can margin of error affect the interpretation of survey results?

### Tip:
Always check whether the sample is random and representative of the population to ensure reliable results.

The local school board wants to get parents to evaluate teachers. They select 100 parents and find that 89% approve of their child's teacher. Define the population, sample, and parameter.

Learn how to identify the population, sample, and parameter in a statistical study. This example focuses on a school board survey where 100 parents are sampled, and 89% approve of their child's teacher.

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