AP Computer Science Principles - Unit 9: Data

AP Computer Science Principles - Unit 9: Data

9th - 12th Grade

10 Qs

quiz-placeholder

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AP Computer Science Principles - Unit 9: Data

AP Computer Science Principles - Unit 9: Data

Assessment

Quiz

Computers

9th - 12th Grade

Easy

Created by

Mister Swagner

Used 46+ times

FREE Resource

10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is scientific research conducted in whole or part by distributed individuals, many of whom may not be scientists, who contribute relevant data to research using their own computing devices?
a) Cleaning Data
b) Correlation
c) Citizen Science
d) Data filtering

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is a process that makes the data uniform without changing its meaning?
a) Correlation
b) Cleaning Data
c) Data filtering
d) Data bias

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following refers to a relationship between two pieces of data, typically referring to the amount that one varies in relation to the other?
a) Crowdsourcing
b) Data bias
c) Correlation
d) Data filtering

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following refers to the practice of obtaining input or information from a large number of people via the Internet?
a) Correlation
b) Crowdsourcing
c) Data bias
d) Cleaning Data

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following refers to the collection of facts and patterns extracted from data?
a) Data filtering
b) Cleaning Data
c) Information
d) Data bias

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following refers to data that does not accurately reflect the full population or phenomenon being studied?
a) Data filtering
b) Data bias
c) Citizen Science
d) Correlation

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following refers to choosing a smaller subset of a data set to use for analysis, for example by eliminating / keeping only certain rows in a table?
a) Data filtering
b) Crowdsourcing
c) Data bias
d) Cleaning Data

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