AP CSP - Unit 9 (code.org) Review

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What is data cleaning?

Back

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

Front

Why is it important to clean data?

Back

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

Front

What is metadata?

Back

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

Front

What is correlation in data analysis?

Back

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

Tags

CCSS.HSS.ID.C.9

Front

What is causation?

Back

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

Tags

CCSS.RI.4.3

CCSS.RI.5.3

CCSS.RI.6.3

CCSS.RI.7.3

CCSS.RI.8.3

Front

What does it mean for data to be incomplete?

Back

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

Front

What is the role of filtering in data analysis?

Back

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

Front

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.

Tags

CCSS.RI.7.7

CCSS.RI.8.7

CCSS.RI.9-10.7

CCSS.RL.8.7

CCSS.RL.9-10.7

Front

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.

Front

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.