2.1 Intro to Big Idea 2: Data and Binary Numbers

3 min read•january 12, 2023

Minna Chow

Milo Chang

AP Computer Science Principles ⌨️

80 resources

See Units

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