Data analysis is not important in their computer science project

Data analysis is only important in other fields, not in their computer science project

Data analysis is only important for large companies, not for their small project

Data analysis is important in their computer science project because it helps in making informed decisions, identifying patterns and trends, detecting anomalies, improving performance, and optimizing processes.

Collect the data, Analyze the data, Draw conclusions, Communicate the results, Evaluate the results

Define the problem and objectives, Collect and prepare the data, Analyze the data, Present the data, Evaluate the data

Define the problem and objectives, Collect and prepare the data, Explore and analyze the data, Draw conclusions and make predictions, Communicate the results.

Define the problem and objectives, Analyze the data, Draw conclusions, Communicate the results, Evaluate the results

The representation of data or information in a graphical or pictorial format.

The process of encrypting data

The analysis of data using statistical methods

The process of converting data into audio format

Data visualization is only useful for presenting data to a large audience

Data visualization is time-consuming and not worth the effort

Data visualization helps in understanding complex data, identifying patterns and trends, making data-driven decisions, and communicating information effectively.

Data visualization is only applicable to certain industries

bar graphs, line plots, scatter diagrams, pie diagrams, heat charts, bubble charts

bar charts, histograms, scatter plots, cross tab

bar graphs, line plots, scatter diagrams, pie diagrams, heat charts, network diagrams

bar graphs, line plots, scatter diagrams, pie diagrams, heat charts, tree diagrams

Identify the purpose, choose appropriate type, simplify design, use clear labels, ensure accessibility

Use small font sizes and unclear labels to save space

Use as many colors as possible, even if they don't relate to the data

Make the design as complex as possible to impress viewers

Data visualization helps in decision-making by presenting complex data in a visual format that is easy to understand and interpret.

Data visualization has no impact on decision-making.

Data visualization only works for small datasets.

Data visualization makes decision-making more complicated.

Bar charts and Histograms

Bar charts

Histograms

Scatter plots and Cross tab

When their data is not uniform

When they have collected a large amount of data

When they are analyzing data from one column only

When they need to analyze multiple values

scatter plot

histogram

bar chart

cross tab

Data cleaning is not necessary in data analysis.

Data cleaning is the process of collecting data for visualization.

Data cleaning is the process of identifying and correcting errors in the data, which is crucial for ensuring the accuracy of the analysis.

Data cleaning is the process of collecting data from various sources.

The choice of visualization technique has no impact on their project.

Choosing the right visualization technique can help them in effectively communicating the results of their project to the class.

Choosing the right visualization technique can make their project look more appealing.

Choosing the right visualization technique can help them in understanding their data better, identifying patterns and trends, and making informed decisions about their project.

Data cleaning is the process of encrypting data for security purposes

Data cleaning is the process of deleting all data to start fresh

Data cleaning is the process of identifying and correcting errors or inconsistencies in data to improve its quality.

Data cleaning is the process of creating new data from scratch

Data cleaning is important in AP CSP to ensure accurate, complete, and reliable data for analysis.

Data cleaning only applies to certain types of data in AP CSP

Data cleaning can be done after analysis in AP CSP

Data cleaning is unnecessary in AP CSP

Ignoring missing values completely

Adding more noise to the data

Mixing up data formats further

Removing duplicates, handling missing values, correcting inconsistent data formats, standardizing data values, detecting outliers

Missing data in data cleaning refers to the presence of values in a dataset

Missing data in data cleaning refers to the absence of values in a dataset, which can occur due to various reasons such as human error, equipment malfunction, or data corruption.

Missing data in data cleaning is always due to software bugs

Missing data in data cleaning is intentional and does not affect the analysis

Remove outliers if they are due to errors or extreme values, or transform them using techniques like winsorization or log transformation.

Create a separate dataset for outliers

Replace outliers with the mean of the dataset

Ignore outliers completely and proceed with analysis

Data validation is not necessary in data cleaning

Data validation is only useful for data analysis, not cleaning

Data validation only adds complexity to the process

Data validation plays a crucial role in ensuring the accuracy and quality of the data being cleaned.

Data normalization is not necessary for data cleaning

Data normalization can introduce errors in the data

Data normalization slows down the data cleaning process

Data normalization is crucial in data cleaning as it reduces redundancy, improves data consistency, and facilitates data analysis.

Microsoft Word

Excel, Google Sheets, OpenRefine, Python libraries like Pandas

Tableau

Photoshop

Data cleaning involves adding noise to the dataset, while data preprocessing involves removing noise.

Data cleaning is done before data preprocessing in the data analysis pipeline.

Data cleaning focuses on transforming the data for analysis, while data preprocessing focuses on handling errors in the dataset.

Data cleaning focuses on handling errors in the dataset, while data preprocessing focuses on transforming the data for analysis.

Data cleaning ensures data is encrypted before analysis.

Data cleaning ensures accurate, complete, and formatted data for reliable analysis.

Data cleaning involves creating duplicate data for analysis.

Data cleaning focuses on removing outliers from the dataset.

110000

110001

110111

111111

111111

11101

11100

11011

1

2

3

4

2/9

2*6

6-2

3+5

14

34

255

256

The human voice in air

The varying temperature during the day

Volume due to a train honking its horn

The varying grades of a student during the school year

Smaller file size (bytes)

Speed of transmitting file

Image quality

Image size (number of pixels)

About how many miles did the animal travel in one week?

Does the animal travel in groups with other tracked animals?

Do the movement patterns of the animal vary according to the weather?

In what geographic location does the animal typically travel?

High-level languages tend to be written by smarter people

High-level languages tend to be closer to basic computer code, which makes them easier to translate.

High-level languages tend to be written for more experienced programmers to use, which implicitly makes them easier to read.

High-level languages tend to be closer to natural language by utilizing simplified abstractions with descriptive names.

77

74

73

70

To make decisions based on certain conditions

To repeat a block of code multiple times

To store and organize data

To perform mathematical calculations

if statement

for statement

while statement

switch statement

if (condition) { code }

if (code) { condition }

condition { if (code) }

code { if (condition) }

The code inside the else block is executed

The code inside the if block is executed

The code inside both the if and else blocks is executed

The code inside neither the if nor else block is executed

A conditional statement that is inside a loop

A conditional statement that is inside another conditional statement

A conditional statement that is inside a function

A conditional statement that is inside a class

To store text data

To store numeric data

To store true or false values

To store complex data structures

true

false

null

undefined

x is greater than y

x is less than y

x is equal to y

x is less than or equal to y

You are eligible to vote

You are not eligible to vote

The code does not compile

The code produces an error

It's cool.

It's warm.

It's hot.

It's very hot.

a series of steps to complete a task that a computer can understand.

Python, JavaScript, Java, PHP, and Ruby

the action we want the program to take.

a condition that is false.

Python, JavaScript, Java, PHP, and Ruby

the action of writing instructions for a computer in a language that it can understand.

a language that is more precise than English but less precise than a coding language.

a specific action to be taken if the condition is false.

a catch-all for every other situation besides true.

pieces of code that direct the program to run in different ways depending on what else is happening.

a set of rules for how a language is written.

English, Chinese, or Spanish.

pieces of code that direct the program to run in different ways depending on what else is happening.

determine which code is being carried out at a given time.

give the program the flexibility to go down more than one path.

all of these.

conditional statements

control flow statments

syntax

variables

JavaScript

Something that has to be true in order for an action to be carried out.

syntax

pseudocode

then

do

else

if

somewhere between English and a coding language.

more precise than English but less precise than a coding language.

used by programmers to figure out the logic and flow of their programs without having to worry about syntax.

all of these

is a placeholder for a piece of information that can change.

is like a bucket for holding information.

can be written as letters or with longer words.

all of these

==

<=

>=

!=

color = sprite.ask("What's your favorite color?")

sprite.say("So your favorite color is " + color.")

if color == "red":

color = "red"

This part is the code that runs in a conditional if the condition is true

This is the part of the code that checks whether a condition is true or false

This is a code that shows how many times a loop should run

This is a code that saves multiple pieces of information in one place

This part is the code that runs in a conditional if the condition is true

This is the part of the code that checks whether a condition is true or false

This is a code that shows how many times a loop should run

This is a code that saves multiple pieces of information in one place

1

2

3

4

The background changes to a winter background

The user is asked another question

The sprites says "Sad..."

The sprite says "Me too!"

A diagram that shows each step of a process or algorithm

Conventions for making code easier for people to read

The line of code in a conditional that checks if something is true or false.

The line of code in a conditional that's indented over

=

[ ]

==

""

The sprite will ask "Would you like to choose the red door, or the blue door?"

The sprite will say "You win a car!"

The sprite will say "You win a house!"

The sprite will say "Thanks for playing!"

If the user chooses "red"

If the user chooses "blue"

All of the above

None of the above

"Cool!"

"Mindblowing!"

"Sweet!"

"Far out!"

When you want to repeat some code

When you want to save a value

When you want the program to do different things depending on user input

When you want to add a certain amount to your variable

If-else

If-And

If statement

For Counter

1

3

5

6

If else

If

If And

For Counter

If else

If

If And

For Counter

If else

If

If And

For Counter

var 10 =10;

var num = 10;

var name = "Bob";

var number 10 = 10;

I am 5

I am not 5

I'm not sure

Nothing will be printed

I am less than or equal to 10

I am none of the options

I am 5

You are in elementary school

You are in high school

You are in some other school

You passed

You failed

None of the options

You got the average

You failed

Congrats you get ice cream!