The One Thing You Need to Know About this Big Idea:

This unit is all about how computers represent data, and how they can store and process ever-increasing quantities of it.

2.1 Binary Numbers

Learning Objective: Explain how data can be represented using bits.

Learning Objective: Explain the consequences of using bits to represent data.

**Learning Objective: For binary numbers, calculate the binary (base 2) equivalent of a positive integer (base 10) and vice versa; compare and order binary numbers. **

Key Ideas

• computers store data in bits
• computers use machine code, which operate on the binary system (digits are either 0 or 1)
• any decimal number can be expressed as a binary number and vice versa
• the same sequence of bits can represent different types of data depending on the context
• abstraction hides irrelevant details from users
• analog / digital representation of data
• overflow and rounding errors result from using bits to represent data

Vocabulary

• data
• bits
• number base
• machine code
• binary system
• byte
• hexadecimal
• abstraction
• analog data
• digital data
• sampling technique
• overflow error
• rounding error

Resources

🔗 2.1: Binary Numbers

2.2 Data Compression

Learning Objective: Compare data compression algorithms to determine which is best in a particular context.

Key Ideas

• data compression can reduce the number of bits when transmitting or storing data
• fewer bits doesn't necessarily mean less information
• lossless data compression is preferred if your main concern is the quality of your file or if you need to be able to reconstruct your original file
• lossy data compression is preferred if your main concern is minimizing how big your file is or how long it'll take to send or receive it

Vocabulary

• lossless compression algorithms
• lossy compression algorithms

Resources

🔗 2.2: Data Compression

2.3 Extracting Information from Data

Learning Objective: Describe what information can be extracted from data.

**Learning Objective: Describe what information can be extracted from metadata. **

Learning Objective: Identify the challenges associated with processing data.

Key Ideas

• by examining data closely, we can identify trends, make connections and address problems
• metadata allow data to be structured and organized
• changes and deletions to metadata don't change the primary data
• cleaning data is a process that makes the data uniform without changing their meaning
• problems of bias are often created by the type or source of data being collected; just collecting more data won't make this problem go away

Vocabulary

• information
• metadata
• cleaning data

Resources

🔗 2.3: Extracting Information from Data

2.4 Using Programs with Data

Learning Objective: Extract information from data using a program.

Learning Objective: Explain how programs can be used to gain insight and knowledge from data.

Key Ideas

• data processing programs can help you acquire information from data
• data filtering systems help with finding information and recognizing patterns
• manipulating data by combining, clustering or classifying it can bring out new information and patterns previously unseen in the raw data, making it a helpful tool for data analysis

Vocabulary

• data transformation
• data filtering

Resources

🔗 2.4: Using Programs with Data

Exam Weighing

• 17-22% of the AP Exam
• Practically, this translates to about 20 questions on the test.