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Data Analysis Vocabulary

Total questions: 10

Worksheet time: 7mins

Name
Class
Date
1.

Why completeness important in data analysis?

a)

To summarize

b)

Better decision -making

c)

To make things easier

d)

Audits and compliance

2.

  • If one dataset tracks dates as YYYY-MM-DD and another uses DD/MM/YYYY, you might misinterpret timelines or trends unless everything conforms to a standard. This is an example of:



(a)  

3.

It helps preserve the integrity and usability of a dataset when some values are missing. Without it, missing data can cause all kinds of problems—errors in calculations, biases in models, or even total failure of certain algorithms.

a)

Conformity

b)

Organization

c)

Cleaning

d)

Imputing

4.

  • Pattern recognition

  • Handling non-linear relationships

  • Adaptability

  • End-to-end learning

  • Are advatanges of using (a)  

5.

What can help me try to predict the future?

a)

Prescriptive Analytics

b)

Descriptive Analytics

c)

Predictive Analytics

d)
  1. Diagnostic Analytics

6.

What can help me answer the question: What should we do about it?

a)

Predictive analytics

b)
  1. Descriptive Analytics

c)
  1. Diagnostic Analytics

d)
  1. Prescriptive Analytics

7.

📈 Hotter days → more ice cream sold
📉 Cooler days → fewer ice cream sale

This is an example of...

(a)  

8.

This is an example of...

a)

Data summarizing

b)

Data intepretation

c)

Data wrangling

d)

Data transformation

9.

ETL stands for

a)
  • Engine Torque Limiting

b)
  • Estimated Time of Landing

c)
  • Extract, Transform, Load

d)
  • Event Trace Log

10.

Organize the letters in louriet

(a)