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  1. AP Computer Science Principles
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Glossary

C

Correlations

Criticality: 3

Relationships between two or more variables where changes in one variable tend to be associated with changes in another.

Example:

A study might find a Correlation between the amount of time students spend studying and their test scores, where more study time generally leads to higher scores.

D

Data Filtering

Criticality: 2

The process of creating and extracting specific subsets of data based on defined criteria, such as time, value, or quality.

Example:

In a spreadsheet of student grades, you might use Data Filtering to show only students who scored above 90% on the last exam.

Data Mining

Criticality: 3

The process of examining large datasets to discover useful information, hidden patterns, or significant relationships that are not immediately obvious.

Example:

A streaming service uses Data Mining to analyze user watch history and recommend new shows you might enjoy, based on what similar viewers have watched.

Data Processing

Criticality: 3

The use of computer programs to record, modify, and organize raw data into a more usable format.

Example:

When you upload photos to a social media site, the platform performs Data Processing to resize them, add metadata, and organize them into your album.

Data Transformation

Criticality: 3

The process of modifying raw data to extract more meaningful information or prepare it for analysis.

Example:

To compare student performance across different grading scales, a teacher might use Data Transformation to convert all scores to a common percentage.

Data Visualization

Criticality: 3

The creation of visual representations, such as tables, graphs, and charts, to make complex data easier to understand and interpret.

Example:

A weather app uses Data Visualization to display temperature changes over a week as a line graph, making it easy to spot warming or cooling trends.

I

Iterative and Interactive Process

Criticality: 2

A method of data analysis where users repeatedly refine their approach, choosing different tools and subsets, and running data through programs multiple times to gain deeper insights.

Example:

When analyzing a large dataset of sales, a business analyst might use an Iterative and Interactive Process, first sorting by region, then filtering by product type, and finally visualizing monthly trends.

O

Outliers

Criticality: 2

Data points that are significantly different from other observations in a dataset, often indicating unusual or exceptional circumstances.

Example:

In a dataset of daily website visitors, a sudden spike of 100,000 visitors on a day when the average is 1,000 would be considered an Outlier, possibly due to a viral social media post.

P

Patterns

Criticality: 3

Recurring sequences or regularities found within data that indicate predictable behavior or relationships.

Example:

Observing that ice cream sales consistently peak in summer months reveals a seasonal Pattern in consumer behavior.

S

Search Tools

Criticality: 1

Applications or features designed to help users find specific information faster and more efficiently within large datasets or the internet.

Example:

When looking for a specific image, you might use a search engine's Search Tools to filter results by color, size, or usage rights.

T

Text Analysis

Criticality: 2

A technique that looks for patterns within written text to categorize, classify, or extract specific insights.

Example:

A company uses Text Analysis on customer feedback surveys to automatically identify common complaints or positive sentiments about their products.

Trends

Criticality: 3

A general direction or movement in which data is changing over time, indicating an increase, decrease, or stability.

Example:

Analyzing global temperature data over the last century shows a clear upward Trend, indicating climate change.