AP CSP - Unit 9 (code.org) Review

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What is data cleaning?

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The process of identifying and correcting or removing inaccurate, incomplete, or irrelevant data from a dataset.

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Why is it important to clean data?

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Cleaning data is important because it ensures that incomplete or incorrect data does not skew results, leading to more accurate analyses.

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What is metadata?

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Metadata is data that provides information about other data, such as its source, format, and context.

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What is correlation in data analysis?

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Correlation refers to a statistical relationship between two variables, indicating how one may change in relation to the other.

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What is causation?

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Causation indicates that one event is the result of the occurrence of another event, implying a direct cause-and-effect relationship.

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What does it mean for data to be incomplete?

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Incomplete data refers to datasets that are missing values or records, which can lead to inaccurate conclusions.

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What is the role of filtering in data analysis?

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Filtering is the process of removing unwanted data from a dataset to focus on specific information.

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What is the difference between correlation and causation?

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Correlation indicates a relationship between two variables, while causation implies that one variable directly affects the other.

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What are some common reasons for data to be cleaned?

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Common reasons include removing duplicates, correcting inaccuracies, and filling in missing values.

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What is the significance of Google Trends data?

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Google Trends data shows the relative popularity of search terms over time, indicating public interest in specific topics.