We may earn an affiliate commission when you visit our partners.
Barsha Saha
In this project you will learn about several visualization techniques and their importance for Statistical Analysis. The project demonstrates different plotting techniques, for example, histograms, scatter plots, box and whiskers plot, violin plot, bar plot, addition of regression line to scatter plot, and creating matrix of multiple plots. It also discusses the suitability of each plots according to the data type of the variables and illustrates multiple ways to achieve the desired plots efficiently. The project refers to 'Palmer Penguins' data set for the illustrative purpose.
Register for this course and see more details by visiting:
OpenCourser.com/course/2lu2k3/visualization
Three deals to help you save
We found three deals and offers that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until December 12
Annual Subscription Savings
Unlock programs from Google, Microsoft, and IBM and join 77% of learners who reported positive career outcomes.
Only $239!
Valid for a limited time only
Future-proof your career
Access O'Reilly books, live events, courses, and more. Save with an annual subscription.
Take
15%
off
What's inside
Syllabus
Project Overview
In this project, you will learn about several visualization techniques and their importance for Statistical Analysis. The project demonstrates different plotting techniques, for example, histograms, scatter plots, box and whiskers plot, violin plot, bar plot, addition of regression line to scatter plot, and creating matrix of multiple plots. It also discusses the suitability of each plots according to the data type of the variables and illustrates multiple ways to achieve the desired plots efficiently. The project refers to 'Palmer Penguins' data set for the illustrative purpose.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers a range of beginner-friendly visualization techniques for statistical analysis
Provides a practical approach to data visualization through hands-on exercises
Demonstrates the appropriate use of various plots based on data types, enhancing the learners' understanding of data representation
Save this course
Save Visualization for Statistical Analysis to your list so you can find it easily later:
Save
Save
Reviews summary
Introduces visualization techniques
Learners describe this course as well-received and appreciate its practical approach to visualization techniques in statistical analysis.
Effective teaching
"Excellent course"
"I had a great time learning from you, Barsha!"
Course is applicable
"The split screen allowed me to follow the instructions and practise along."
"I highly recommend it to anyone interested in learning basic visualisation techniques for statistical analysis."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Visualization for Statistical Analysis with these
activities:
Review basics of data analysis
Show steps
Refresh your understanding of data analysis concepts, such as data types, data manipulation, and statistical measures, to provide a stronger foundation for data visualization.
Show steps
-
Review online resources or books on data analysis
-
Practice data analysis tasks using a programming language or software
-
Participate in discussions or forums related to data analysis
Review Basic Concepts of Statistical Analysis
Show steps
Refreshes and strengthens the foundational knowledge of Statistical Analysis concepts, making it easier to follow the course.
Browse courses on
Statistical Analysis
Show steps
-
Review key definitions and terminologies of Statistical Analysis.
-
Solve practice problems related to basic Statistical Analysis techniques.
-
Read textbooks or online materials to reinforce understanding of statistical concepts.
Review Statistical Concepts
Show steps
This course heavily relies on statistical knowledge. Before jumping into the course, spend some time reviewing statistical concepts.
Browse courses on
Statistical Analysis
Show steps
-
Review notes from a previous statistics course or textbook.
-
Complete practice problems to test your understanding of basic statistical concepts.
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Attend peer-led discussion on data visualization
Show steps
Join a peer-led discussion or study group to share knowledge, ask questions, and engage in collaborative learning about data visualization techniques and best practices.
Show steps
-
Find or organize a peer-led discussion group
-
Actively participate in discussions and share your insights
-
Collaborate with peers to solve problems and learn from each other
Explore Data Visualization Techniques
Show steps
Explore online tutorials that demonstrate various data visualization techniques to get a better understanding of the concepts covered in this course.
Browse courses on
Data Visualization
Show steps
-
Search for online tutorials on data visualization.
-
Choose a tutorial that focuses on the specific techniques covered in the course.
-
Follow the steps in the tutorial to create your own visualizations.
Curate a collection of data visualization resources
Show steps
Gather and organize a comprehensive collection of data visualization resources, including articles, tutorials, tools, and libraries, to serve as a valuable reference for your future data visualization endeavors.
Show steps
-
Conduct online research to identify relevant resources
-
Create a central repository for the resources, such as a website or a document
-
Categorize and organize the resources for easy access
-
Share the collection with others to contribute to the data visualization community
Practice Plotting Techniques
Show steps
Provides hands-on practice in using various plotting techniques, improving proficiency for the course.
Browse courses on
Data Visualization
Show steps
-
Use a data visualization tool (e.g., Python, R) to plot different types of data.
-
Create histograms, scatter plots, box plots, and violin plots using real-world datasets.
-
Explore and interpret the patterns and relationships revealed by these plots.
Review plotting techniques
Show steps
Practice several plotting techniques introduced in the course, covering histograms, scatter plots, box and whisker plots, violin plots, bar plots, and more.
Show steps
-
Practice drawing histograms for different datasets
-
Practice drawing scatter plots to show relationships between variables
-
Practice drawing box and whisker plots to compare distributions
-
Practice drawing violin plots to show the distribution and density of data
-
Practice drawing bar plots to compare categorical data
Practice Creating Data Visualizations
Show steps
Regularly practice creating data visualizations using different techniques to improve your skills and understanding of the concepts covered in this course.
Browse courses on
Data Visualization
Show steps
-
Find a dataset that interests you.
-
Choose a data visualization technique that is appropriate for the dataset.
-
Use a data visualization tool to create the visualization.
Discuss and Analyze Case Studies
Show steps
Facilitates knowledge application and critical thinking by discussing and analyzing real-life case studies in Statistical Analysis.
Browse courses on
Case Studies
Show steps
-
Read and analyze provided case studies on different Statistical Analysis applications.
-
Engage in group discussions to share insights and perspectives.
-
Present findings and recommendations based on the case studies.
Explore additional plotting techniques
Show steps
Go beyond the course material and explore additional plotting techniques, such as heatmaps, contour plots, and 3D visualizations, to expand your understanding of data visualization.
Show steps
-
Find online tutorials or articles on advanced plotting techniques
-
Follow the tutorials and apply the techniques to your own datasets
-
Experiment with different plotting options to create informative and visually appealing graphics
Create a Data Visualization Portfolio
Show steps
Creating a portfolio of your data visualizations will help you showcase your skills and demonstrate your understanding of the concepts covered in this course.
Browse courses on
Data Visualization
Show steps
-
Gather your best data visualizations.
-
Create a website or online portfolio to showcase your work.
-
Share your portfolio with potential employers or clients.
Explore Advance Plotting Techniques
Show steps
Expands knowledge and skills by introducing advanced plotting techniques beyond the course's scope, enabling further data exploration.
Browse courses on
Data Visualization Tools
Show steps
-
Identify and learn specialized plotting techniques for different types of data.
-
Use online tutorials or documentation to understand and implement these techniques.
-
Apply advanced plotting methods to enhance data visualization and communication.
Participate in Data Visualization Competitions
Show steps
Participating in data visualization competitions can help you improve your skills and demonstrate your understanding of the concepts covered in this course while competing with other like-minded individuals.
Browse courses on
Data Visualization
Show steps
-
Find data visualization competitions that interest you.
-
Submit your best data visualizations to the competition.
-
Analyze the feedback on your submissions to identify areas for improvement.
Contribute to an open-source data visualization project
Show steps
Make contributions to an open-source data visualization project to gain hands-on experience, collaborate with the community, and showcase your skills in data visualization software development.
Show steps
-
Identify a suitable open-source data visualization project
-
Review the project's documentation and codebase
-
Implement new features, fix bugs, or improve documentation
-
Submit your contributions for review and merge
-
Engage with the project community and receive feedback
Develop a Data Visualization Portfolio
Show steps
Encourages creativity and strengthens practical skills by creating a portfolio showcasing diverse plotting techniques and data insights.
Browse courses on
Data Storytelling
Show steps
-
Gather and select datasets from various sources.
-
Design and implement different types of plots to represent the data effectively.
-
Provide clear and concise explanations of the plots and their key findings.
Create an interactive data visualization
Show steps
Develop an interactive data visualization that allows users to explore and interact with data in a dynamic and engaging way, demonstrating your mastery of advanced plotting techniques and user experience design.
Show steps
-
Identify a suitable dataset and define the user interactions
-
Design and implement the interactive visualization using appropriate tools and libraries
-
Incorporate features for data filtering, zooming, and drill-down capabilities
-
Ensure the visualization is responsive and adapts to different devices and screen sizes
-
Test and refine the interactive visualization based on user feedback
Review basics of data analysis
Show steps
Refresh your understanding of data analysis concepts, such as data types, data manipulation, and statistical measures, to provide a stronger foundation for data visualization.
Show steps
Show steps
Show steps
- Review online resources or books on data analysis
- Practice data analysis tasks using a programming language or software
- Participate in discussions or forums related to data analysis
Review Basic Concepts of Statistical Analysis
Show steps
Refreshes and strengthens the foundational knowledge of Statistical Analysis concepts, making it easier to follow the course.
Browse courses on
Statistical Analysis
Show steps
Show steps
Show steps
- Review key definitions and terminologies of Statistical Analysis.
- Solve practice problems related to basic Statistical Analysis techniques.
- Read textbooks or online materials to reinforce understanding of statistical concepts.
Review Statistical Concepts
Show steps
This course heavily relies on statistical knowledge. Before jumping into the course, spend some time reviewing statistical concepts.
Browse courses on
Statistical Analysis
Show steps
Show steps
Show steps
- Review notes from a previous statistics course or textbook.
- Complete practice problems to test your understanding of basic statistical concepts.
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Attend peer-led discussion on data visualization
Show steps
Join a peer-led discussion or study group to share knowledge, ask questions, and engage in collaborative learning about data visualization techniques and best practices.
Show steps
Show steps
Show steps
- Find or organize a peer-led discussion group
- Actively participate in discussions and share your insights
- Collaborate with peers to solve problems and learn from each other
Explore Data Visualization Techniques
Show steps
Explore online tutorials that demonstrate various data visualization techniques to get a better understanding of the concepts covered in this course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Search for online tutorials on data visualization.
- Choose a tutorial that focuses on the specific techniques covered in the course.
- Follow the steps in the tutorial to create your own visualizations.
Curate a collection of data visualization resources
Show steps
Gather and organize a comprehensive collection of data visualization resources, including articles, tutorials, tools, and libraries, to serve as a valuable reference for your future data visualization endeavors.
Show steps
Show steps
Show steps
- Conduct online research to identify relevant resources
- Create a central repository for the resources, such as a website or a document
- Categorize and organize the resources for easy access
- Share the collection with others to contribute to the data visualization community
Practice Plotting Techniques
Show steps
Provides hands-on practice in using various plotting techniques, improving proficiency for the course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Use a data visualization tool (e.g., Python, R) to plot different types of data.
- Create histograms, scatter plots, box plots, and violin plots using real-world datasets.
- Explore and interpret the patterns and relationships revealed by these plots.
Review plotting techniques
Show steps
Practice several plotting techniques introduced in the course, covering histograms, scatter plots, box and whisker plots, violin plots, bar plots, and more.
Show steps
Show steps
Show steps
- Practice drawing histograms for different datasets
- Practice drawing scatter plots to show relationships between variables
- Practice drawing box and whisker plots to compare distributions
- Practice drawing violin plots to show the distribution and density of data
- Practice drawing bar plots to compare categorical data
Practice Creating Data Visualizations
Show steps
Regularly practice creating data visualizations using different techniques to improve your skills and understanding of the concepts covered in this course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find a dataset that interests you.
- Choose a data visualization technique that is appropriate for the dataset.
- Use a data visualization tool to create the visualization.
Discuss and Analyze Case Studies
Show steps
Facilitates knowledge application and critical thinking by discussing and analyzing real-life case studies in Statistical Analysis.
Browse courses on
Case Studies
Show steps
Show steps
Show steps
- Read and analyze provided case studies on different Statistical Analysis applications.
- Engage in group discussions to share insights and perspectives.
- Present findings and recommendations based on the case studies.
Explore additional plotting techniques
Show steps
Go beyond the course material and explore additional plotting techniques, such as heatmaps, contour plots, and 3D visualizations, to expand your understanding of data visualization.
Show steps
Show steps
Show steps
- Find online tutorials or articles on advanced plotting techniques
- Follow the tutorials and apply the techniques to your own datasets
- Experiment with different plotting options to create informative and visually appealing graphics
Create a Data Visualization Portfolio
Show steps
Creating a portfolio of your data visualizations will help you showcase your skills and demonstrate your understanding of the concepts covered in this course.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather your best data visualizations.
- Create a website or online portfolio to showcase your work.
- Share your portfolio with potential employers or clients.
Explore Advance Plotting Techniques
Show steps
Expands knowledge and skills by introducing advanced plotting techniques beyond the course's scope, enabling further data exploration.
Browse courses on
Data Visualization Tools
Show steps
Show steps
Show steps
- Identify and learn specialized plotting techniques for different types of data.
- Use online tutorials or documentation to understand and implement these techniques.
- Apply advanced plotting methods to enhance data visualization and communication.
Participate in Data Visualization Competitions
Show steps
Participating in data visualization competitions can help you improve your skills and demonstrate your understanding of the concepts covered in this course while competing with other like-minded individuals.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find data visualization competitions that interest you.
- Submit your best data visualizations to the competition.
- Analyze the feedback on your submissions to identify areas for improvement.
Contribute to an open-source data visualization project
Show steps
Make contributions to an open-source data visualization project to gain hands-on experience, collaborate with the community, and showcase your skills in data visualization software development.
Show steps
Show steps
Show steps
- Identify a suitable open-source data visualization project
- Review the project's documentation and codebase
- Implement new features, fix bugs, or improve documentation
- Submit your contributions for review and merge
- Engage with the project community and receive feedback
Develop a Data Visualization Portfolio
Show steps
Encourages creativity and strengthens practical skills by creating a portfolio showcasing diverse plotting techniques and data insights.
Browse courses on
Data Storytelling
Show steps
Show steps
Show steps
- Gather and select datasets from various sources.
- Design and implement different types of plots to represent the data effectively.
- Provide clear and concise explanations of the plots and their key findings.
Create an interactive data visualization
Show steps
Develop an interactive data visualization that allows users to explore and interact with data in a dynamic and engaging way, demonstrating your mastery of advanced plotting techniques and user experience design.
Show steps
Show steps
Show steps
- Identify a suitable dataset and define the user interactions
- Design and implement the interactive visualization using appropriate tools and libraries
- Incorporate features for data filtering, zooming, and drill-down capabilities
- Ensure the visualization is responsive and adapts to different devices and screen sizes
- Test and refine the interactive visualization based on user feedback
Career center
Learners who complete Visualization for Statistical Analysis will develop knowledge and skills
that may be useful to these careers:
Data Visualization Specialist
Data Visualization Specialist
A Data Visualization Specialist creates visual representations of data to help businesses and organizations make informed decisions. This course may be useful in building a foundation for a career as a Data Visualization Specialist, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses data to help businesses optimize their operations. This course may be useful in building a foundation for a career as an Operations Research Analyst, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data to help businesses and organizations make informed decisions. This course may be useful in building a foundation for a career as a Statistician, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Data Analyst
Data Analyst
A Data Analyst collects, cleans, and analyzes data to help businesses make informed decisions. This course may be useful in building a foundation for a career as a Data Analyst, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses data to model and make predictions for financial markets. This course may be useful in building a foundation for a career as a Quantitative Analyst, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Actuary
Actuary
An Actuary uses data to assess risk and make financial decisions. This course may be useful in building a foundation for a career as an Actuary, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst uses data to help businesses understand their performance and make better decisions. This course may be useful in building a foundation for a career as a Business Intelligence Analyst, as it teaches visualization techniques that are essential for communicating data insights to stakeholders.
Epidemiologist
Epidemiologist
An Epidemiologist studies the distribution and patterns of health events and diseases in populations. This course may be useful in building a foundation for a career as an Epidemiologist, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Biostatistician
Biostatistician
A Biostatistician uses data to design and analyze studies in the field of medicine. This course may be useful in building a foundation for a career as a Biostatistician, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Market Research Analyst
Market Research Analyst
A Market Research Analyst collects and analyzes data to help businesses understand their customers and make better decisions. This course may be useful in building a foundation for a career as a Market Research Analyst, as it teaches visualization techniques that are essential for communicating data insights to stakeholders.
Science Writer
Science Writer
A Science Writer communicates scientific information to the public. This course may be useful in building a foundation for a career as a Science Writer, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Information Architect
Information Architect
An Information Architect designs and organizes websites and other digital content to make it easy for users to find and use the information they need. This course may be useful in building a foundation for a career as an Information Architect, as it teaches visualization techniques that are essential for understanding and communicating data insights.
User Experience Researcher
User Experience Researcher
A User Experience Researcher studies how users interact with websites and other digital products to make them more user-friendly. This course may be useful in building a foundation for a career as a User Experience Researcher, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Data Scientist
Data Scientist
A Data Scientist uses data to build models and make predictions. This course may be useful in building a foundation for a career as a Data Scientist, as it teaches visualization techniques that are essential for understanding and communicating data insights.
Data Journalist
Data Journalist
A Data Journalist uses data to tell stories and communicate information to the public. This course may be useful in building a foundation for a career as a Data Journalist, as it teaches visualization techniques that are essential for understanding and communicating data insights.
For more career information including salaries, visit:
OpenCourser.com/course/2lu2k3/visualization
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Visualization for Statistical Analysis.
This comprehensive textbook on information visualization provides a thorough overview of the field, from the basics of perception to the latest advances in design and evaluation. It is an essential read for anyone who wants to learn more about the theory and practice of information visualization.
Save
This classic work on data visualization provides a comprehensive overview of the principles and techniques of effective graphical communication. It is an essential read for anyone interested in learning more about the art and science of data visualization.
This advanced textbook on statistical graphics provides a rigorous foundation for the theory and practice of data visualization. It valuable resource for anyone who wants to learn more about the mathematical and statistical principles underlying effective graphical communication.
This popular R package for creating graphics is widely used by data scientists and statisticians. It provides a powerful and flexible way to create a wide variety of high-quality visualizations.
Save
This comprehensive textbook on deep learning provides a thorough overview of the field, from the basics of neural networks to the latest advances in deep learning architectures and applications. It is an essential read for anyone who wants to learn more about the theory and practice of deep learning.
This practical guide to machine learning with Python provides step-by-step instructions for building and training machine learning models using Scikit-Learn, Keras, and TensorFlow. It valuable resource for anyone who wants to learn how to apply machine learning to real-world problems.
This comprehensive guide to machine learning with Python provides a thorough overview of the field, from the basics of supervised and unsupervised learning to the latest advances in deep learning. It valuable resource for anyone who wants to learn more about the theory and practice of machine learning using Python.
This practical guide to machine learning with R provides step-by-step instructions for building and training machine learning models using R. It valuable resource for anyone who wants to learn how to apply machine learning to real-world problems using R.
Save
This comprehensive textbook on predictive modeling provides a thorough overview of the field, from the basics of regression and classification to the latest advances in machine learning. It valuable resource for anyone who wants to learn more about the theory and practice of predictive modeling.
Save
This practical guide to data visualization provides step-by-step instructions for creating a wide variety of charts and graphs. It valuable resource for anyone who wants to learn how to communicate data effectively.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/2lu2k3/visualization
Share
Similar courses
Here are nine courses similar to
Visualization for Statistical Analysis.
Data Visualization with R
OpenCourser.com/course/t9uzrv/data
Data Visualization with R
Most relevant
Plots Creation using Matplotlib Python
OpenCourser.com/course/rw9q5o/plots
Plots Creation using Matplotlib Python
Most relevant
Visualizing Data with R
OpenCourser.com/course/gxz3bg/visualizing
Visualizing Data with R
Most relevant
Plots (Graphics) for Data Science
OpenCourser.com/course/l8osve/plots
Plots (Graphics) for Data Science
Most relevant
Cryptocurrency Data Visualization using Plotly Express
OpenCourser.com/course/4tz8h7/cryptocurrency
Cryptocurrency Data Visualization using Plotly Express
Most relevant
Basic Statistics in Python (Correlations and T-tests)
OpenCourser.com/course/yn0t0y/basic
Basic Statistics in Python (Correlations and T-tests)
Most relevant
A Simple Scatter Plot using D3 js
OpenCourser.com/course/sr4bfv/a
A Simple Scatter Plot using D3 js
Most relevant
Visualizing Data in ggplot 2: R Data Playbook
OpenCourser.com/course/m911o2/visualizing
Visualizing Data in ggplot 2: R Data Playbook
Most relevant
Scatter Plot for Data Scientists & Big Data Analysts-Visuals
OpenCourser.com/course/0golws/scatter
Scatter Plot for Data Scientists & Big Data Analysts...
Most relevant
Effort
2
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Barsha Saha
Language
English
Good to know
Covers a range of beginner-friendly visualization techniques for statistical analysis
Provides a practical approach to data visualization through hands-on exercises
Demonstrates the appropriate use of various plots based on data types, enhancing the learners' understanding of data representation
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser