Data Science MCQs with Answers
Welcome, tech enthusiast! You’re here because you understand the importance of data science and are interested in multiple-choice questions (MCQs) to test your knowledge or prepare for an exam, right? Let’s dive right in!
Introduction to Data Science MCQs?
Data science MCQs are a series of questions with multiple answers, out of which you choose the most accurate one. They cover different data science topics from statistics and machine learning to data analysis and visualizations.
Sounds simple, right?
Don’t be deceived, though. These MCQs can be quite challenging!
Importance of Data Science MCQs
For Learners
Data science MCQs are an excellent way for learners to test their understanding of concepts and theories. They help you identify areas you’re confident in and areas needing improvement. Plus, they’re a fun way to study, wouldn’t you agree?
For Instructors
For instructors, MCQs provide a convenient method to assess student comprehension. They’re efficient, easy to mark, and can cover a broad range of topics. Let’s just say, they make life a tad bit easier for our beloved educators!
Core Concepts in Data Science MCQs
Statistics
Statistics forms the backbone of data science. It provides the tools to find patterns, make predictions, and drive decision-making. So, expect a generous helping of statistics questions in your MCQs.
Machine Learning
Machine Learning is like the cool kid on the block in the world of data science. It’s the process of teaching a system to make accurate predictions or decisions based on data. Fascinating, isn’t it? This is why it’s a common topic in data science MCQs.
Data Analysis
Data Analysis is the process of inspecting, cleaning, transforming, and modeling data to discover useful information. It’s like the detective work of data science. You’ll undoubtedly encounter MCQs on this topic.
Tips for Answering Data Science MCQs
Remember to read each question thoroughly and consider all the options before answering. Don’t rush; take your time. Some questions may be trickier than they initially appear!
Examples of Data Science MCQs with Answers
Now that we’re equipped with the necessary information, let’s explore some MCQs. The answers are given at the end of quiz.
Statistics MCQs
- What is the median of the following set of numbers? {7, 15, 13, 15, 19, 23, 30, 45, 50}
- A. 15
- B. 19
- C. 23
- D. 30
- In statistics, what is a Type I error?
- A. False Negative
- B. False Positive
- C. True Negative
- D. True Positive
- The Central Limit Theorem is significant for which reason?
- A. It helps to understand the normal distribution
- B. It helps to make predictions
- C. It aids in hypothesis testing
- D. All of the above
Machine Learning MCQs
- Which algorithm is used for variable reduction and getting only a subset of original variables?
- A. Principle Component Analysis
- B. Neural Networks
- C. Random Forest
- D. None of the above
- What is overfitting in the context of machine learning?
- A. When a model learns the training data too well, performing poorly on unseen data
- B. When a model performs poorly on the training data
- C. When a model performs well on unseen data but poorly on training data
- D. When a model does not learn at all
- Which of the following is a supervised learning algorithm?
- A. K-means clustering
- B. Apriori Algorithm
- C. Decision Tree
- D. PCA
Data Analysis MCQs
- What is the process of filtering and cleaning data called?
- A. Data Mining
- B. Data Wrangling
- C. Machine Learning
- D. All of the above
- What is the purpose of a box plot in data analysis?
- A. It shows the correlation between two variables
- B. It presents the frequency of data points
- C. It provides a five-number data summary
- D. It indicates the variance of a data set
- What does “tidy” data mean in data analysis?
- A. Data that has been cleaned
- B. Data where each variable forms a column and each observation forms a row
- C. Data with no missing values
- D. Data with a single table
Python Programming
- How do you create a function in Python?
- A. def function_name():
- B. function function_name():
- C. create function_name():
- D. function = function_name():
- What does the Pandas
df.describe()function do?- A. It describes the type of data
- B. It provides a descriptive statistical summary of the DataFrame
- C. It describes the structure of the DataFrame
- D. It describes the missing values in a DataFrame
Deep Learning
- In the context of artificial neural networks, what is backpropagation?
- A. The process of updating weights and biases by propagating the errors backwards
- B. The process of forwarding inputs through the network
- C. The process of initializing weights and biases
- D. The process of activating neurons
- What is a Convolutional Neural Network most commonly used for?
- A. Tabular data analysis
- B. Natural Language Processing
- C. Image and video recognition tasks
- D. Time series analysis
Data Visualization
- In Matplotlib, what does the
plt.show()function do?
- A. It generates a plot
- B. It displays a plot
- C. It saves a plot
- D. It clears the current plot
- What is a heatmap typically used for in data visualization?
- A. To represent data in a table format
- B. To visualize correlation between variables
- C. To show geographical data
- D. To plot time series data
Data Wrangling
- What is the purpose of the
merge()function in Pandas?
- A. To combine two or more data frames based on a common key
- B. To sort a data frame based on one or more columns
- C. To calculate the mean of a column in a data frame
- D. To rename the columns of a data frame
- What does the Pandas
df.dropna()function do?
- A. It drops the columns containing null values
- B. It drops the rows containing null values
- C. It fills the null values with zero
- D. Both A and B
SQL and Databases
- What does SQL stand for?
- A. Structured Query Language
- B. Sequential Query Language
- C. Simple Query Language
- D. Structured Queue Language
- In SQL, what does the
JOINkeyword do?
- A. It combines rows from two or more tables, based on a related column
- B. It adds a new row to a table
- C. It deletes a row from a table
- D. It updates a row in a table
Big Data
- What is Apache Hadoop?
- A. A JavaScript library for building user interfaces
- B. A Python framework for web development
- C. An open-source software for reliable, scalable, distributed computing
- D. A SQL database management system
- What does the MapReduce programming model do?
- A. It allows for distributed processing of large data sets across clusters of computers
- B. It provides a graphical user interface for programming
- C. It speeds up the data entry process
- D. It provides a method for version control
AI and Ethics
- What is bias in machine learning?
- A. The difference between the average prediction of the model and the correct value
- B. The tendency of a model to consistently learn the wrong thing
- C. The error from erroneous assumptions in the learning algorithm
- D. All of the above
- What is the primary ethical concern with AI and machine learning?
- A. The algorithms might become too powerful
- B. The potential for job displacement
- C. The potential for misuse of technology
- D. All of the above
Data Mining
- What is the goal of Association Rules in Data Mining?
- A. To find interesting associations or correlation relationships among a set of items in data sets
- B. To predict a class for a given data
- C. To find a minimal set of attributes that causes a given relational database to be lossless and dependency-preserving
- D. To fit the data into a mathematical description
R Programming
- In R, what does the
str()function do?
- A. It converts an object to a string
- B. It provides compact information about an object
- C. It concatenates multiple strings together
- D. It checks if an object is a string
Natural Language Processing
- What is a “stop word” in Natural Language Processing?
- A. A word that is used to stop a process
- B. A commonly used word that a search engine has been programmed to ignore
- C. A word that causes an error in processing
- D. A word that signifies the end of a sentence
- What does the TF-IDF measure in text mining?
- A. The frequency of a word in a document
- B. The importance of a word in a collection of documents
- C. The length of a document
- D. The complexity of a word
TensorFlow and Deep Learning
- What is TensorFlow?
- A. A Python library for fast numerical computing
- B. A cloud service for machine learning
- C. An open-source platform for machine learning and artificial intelligence
- D. A JavaScript library for building user interfaces
- What are epochs in deep learning?
- A. The layers in a neural network
- B. The weight adjustments in a network
- C. The iterations over the entire dataset
- D. The learning rate of a network
Data Warehousing
- What is a Fact Table in a Data Warehouse?
- A. A table that contains aggregated data
- B. A table that contains descriptive attributes of objects in a star schema
- C. A table that contains meta-data about the warehouse
- D. A table that contains quantitative information for analysis
Data Security and Privacy
- What does GDPR stand for?
- A. General Data Processing Regulation
- B. General Data Protection Rule
- C. General Data Privacy Regulation
- D. General Data Protection Regulation
Databases
- In a relational database, what is a tuple?
- A. A column in a table
- B. A database query
- C. A row in a table
- D. A database constraint
Cloud Computing
- What is AWS?
- A. A programming language
- B. A data science tool
- C. A cloud services platform
- D. A type of database
Answers
- B. 19
- B. False Positive
- D. All of the above
- A. Principle Component Analysis
- A. When a model learns the training data too well, performing poorly on unseen data
- C. Decision Tree
- B. Data Wrangling
- C. It provides a five-number data summary
- B. Data where each variable forms a column and each observation forms a row
- A. def function_name():
- B. It provides a descriptive statistical summary of the DataFrame
- A. The process of updating weights and biases by propagating the errors backwards
- C. Image and video recognition tasks
- B. It displays a plot
- B. To visualize correlation between variables
- A. To combine two or more data frames based on a common key
- D. Both A and B
- A. Structured Query Language
- A. It combines rows from two or more tables, based on a related column
- C. An open-source software for reliable, scalable, distributed computing
- A. It allows for distributed processing of large data sets across clusters of computers
- D. All of the above
- D. All of the above
- A. To find interesting associations or correlation relationships among a set of items in data sets
- B. It provides compact information about an object
- B. A commonly used word that a search engine has been programmed to ignore
- B. The importance of a word in a collection of documents
- C. An open-source platform for machine learning and artificial intelligence
- C. The iterations over the entire dataset
- D. A table that contains quantitative information for analysis
- D. General Data Protection Regulation
- C. A row in a table
- C. A cloud services platform
More to read
- Introduction to Data Science
- Brief History of Data Science
- Components of Data Science
- Data Science Lifecycle
- 24 Skills for Data Scientist
- Data Science Languages
- 15 Data Science Applications in Real Life
- Statistics for Data Science
- Probability for Data Science
- Linear Algebra for Data Science
- Data Science Interview Questions and Answers
- Data Science Vs. Artificial Intelligence
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