The correct answer is inferential statistics.

Inferential statistics involves analyzing sample data to make generalizations, predictions, or decisions about a population based on that data. This contrasts with descriptive statistics, which focuses on summarizing and describing the features of a dataset without making conclusions about a larger population.

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Here are some follow-up questions for deeper understanding:

1. What are the differences between inferential and descriptive statistics?
2. How do statisticians ensure that a sample is representative of a population?
3. What are common techniques used in inferential statistics?
4. Can you give examples of when inferential statistics are applied in real-world situations?
5. How does the size of a sample affect the reliability of inferential statistics?

Tip: Always check if the sample used for inferential analysis is random and unbiased, as this ensures more accurate conclusions about the population!