Which statement about data types is true?

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Multiple Choice

Which statement about data types is true?

Explanation:
The key idea here is understanding the difference between primary data and secondary data. Primary data is collected firsthand and is designed to answer a specific question or meet a particular objective in the study. That’s why the statement that primary data is obtained for a specific purpose is true—it’s tailored to what you’re trying to find out. Secondary data, on the other hand, already exists and was collected by someone else for some other purpose. It can be useful because it’s often cheaper and quicker, but it might not fit exactly what you need and can raise questions about relevance, timeliness, or accuracy. So, the other options don’t fit: saying primary data is obtained for a general purpose is inaccurate because it’s meant to address a specific goal; saying secondary data is data collected by the researcher is incorrect because it’s data collected by others; and saying data has no risks in accuracy ignores potential biases, errors, or outdated information in data sources.

The key idea here is understanding the difference between primary data and secondary data. Primary data is collected firsthand and is designed to answer a specific question or meet a particular objective in the study. That’s why the statement that primary data is obtained for a specific purpose is true—it’s tailored to what you’re trying to find out.

Secondary data, on the other hand, already exists and was collected by someone else for some other purpose. It can be useful because it’s often cheaper and quicker, but it might not fit exactly what you need and can raise questions about relevance, timeliness, or accuracy.

So, the other options don’t fit: saying primary data is obtained for a general purpose is inaccurate because it’s meant to address a specific goal; saying secondary data is data collected by the researcher is incorrect because it’s data collected by others; and saying data has no risks in accuracy ignores potential biases, errors, or outdated information in data sources.

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