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2.1 Intro to Big Idea 2: Data and Binary Numbers

Minna Chow

Milo Chang

AP Computer Science PrinciplesΒ β¨οΈ

80Β resources
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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.β

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
• abstraction
• analog data
• digital data
• sampling technique
• overflow error
• rounding error

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

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
• cleaning 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 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

Exam Weighing

• 17-22% of the AP Exam
• Practically, this translates to aboutΒ 20 questionsΒ on the test.
Browse Study Guides By Unit
πΉUnit 1 β Creative Development
βοΈUnit 2 β Data
π±Unit 3 β Algorithms & Programming
π₯Unit 4 β Computer Systems & Networks
β¨οΈUnit 5 β Impact of Computing
πExam Prep