Data Science Quiz

What is the first step in the data science process?

• Collecting data and preparing it for analysis

• Experimenting with and tuning different analytical models

• Defining an analytical hypothesis that could provide business value

Which of the following programming languages are most widely used by data scientists?

• C and C++

• Python, R and SQL

• Java and JavaScript

True or false? Data scientists typically need a combination of technical skills, nontechnical ones and suitable personality traits to be successful.

• True

• False

Why is data sampling useful for data scientists?

• It lets them analyze data sets in small batches to reduce their use of system resources.

• It reduces the amount of data storage space that's required for data science applications.

• It enables them to use a representative subset of data to build accurate analytical models more quickly.

Which of the following best describes the principal goal of data science?

• To collect and archive exhaustive data sets from various source systems for corporate record keeping uses.

• To mine and analyze large amounts of data in order to uncover information that can be used for operational improvements and business gains.

• To collect and prepare data for use as part of analytics applications.

True or false? Bias is a common problem in data science applications.

• True

• False

What is a common maxim about data scientists?

• They spend 80% of their time finding and preparing data and 20% analyzing it.

• They spend 80% of their time analyzing data and 20% finding and preparing it.

• They spend 80% of their time on failed analytics projects and 20% doing useful work.

Which of the following analytical and statistical techniques do data scientists commonly use?

• Classification

• Regression

• Clustering

• All of the above

What is the primary difference between a data scientist and a data engineer?

• A data engineer collects and prepares data, and a data scientist then analyzes it.

• A data engineer analyzes data after a data scientist collects and prepares it.

• A data engineer builds data pipelines and helps prepare data, while a data scientist is responsible for data collection, preparation and analysis.

In machine learning, what is the primary difference between supervised and unsupervised learning?

• Supervised learning involves data that has been labeled and classified, while unsupervised learning data is unlabeled and unclassified.

• Supervised learning is monitored closely by data scientists, while they don't play a role in unsupervised learning.

• Supervised learning is only used for image recognition, while unsupervised learning can be used for various analytics applications.