- Browse
- Advanced Statistics

- Advanced Statistics for Data Science: Johns Hopkins University
- Data Processing Using Python: Nanjing University
- Materials Data Sciences and Informatics: Georgia Institute of Technology
- Business Analytics for Decision Making: University of Colorado Boulder
- Analyze Survey Data with Tableau: Coursera Project Network
- Create a Custom Marketing Analytics Dashboard in Data Studio: Coursera Project Network
- Data Science: Foundations using R: Johns Hopkins University
- Advanced Learning Algorithms: DeepLearning.AI
- Introduction to Statistics: Stanford University
- TensorFlow: Advanced Techniques: DeepLearning.AI

Advanced statistics are the mathematical tools used to discover and explore complex relationships between different variables in large datasets. In contrast to basic statistics such as average and analysis of variance (ANOVA) that simply describe the characteristics of a dataset, advanced statistical approaches often seek to make predictions about the world. This requires the use of more sophisticated statistical inference tools, such as generalized linear models for regression analysis capable of establishing how multiple interrelated factors may impact projected outcomes.

These advanced statistical methods are increasingly important in the field of data science, which is tasked with uncovering important business insights and developing predictive models from diverse big data-scale datasets. These techniques are also especially important for the proper training and use of machine learning algorithms. As in data science and machine learning more generally, R programming and Python programming skills are typically relied upon to conduct these advanced statistical analyses.

Advanced statistics skills are essential for work in data science, machine learning, and artificial intelligence (AI), as statistical approaches are at the heart of the learning algorithms that make these applications possible. An understanding of statistics is likewise important for professionals in finance, healthcare, and other industries that are increasingly making use of machine learning and AI, as they increasingly need to work closely with data scientists to ensure that these powerful techniques are developed to solve the right business problems.

Those wishing to delve deeper into advanced statistical methods and help develop new mathematical approaches in the field may pursue a master’s or even a PhD in statistics. These experts work in academia, government, or at private sector companies involved in scientific or engineering research. According to the Bureau of Labor Statistics, professional statisticians earn a median annual salary of $91,160, and this specialized career path is expected to be in high demand due to expanding opportunities to use statistics to navigate our data-rich world.

Certainly. Coursera offers a variety of courses in advanced statistics as well as their applications in the context of fields like data science and machine learning. In fact, coursework in statistics is often a prerequisite for data science classes. Regardless of your level of expertise and needs in these areas, Coursera enables you to learn remotely from top-ranked schools like the University of Michigan, Johns Hopkins University, and Duke University. And, since you can view course materials and complete coursework on a flexible schedule, there’s an exceedingly high probability that you can fit online learning about advanced statistics into your existing school or work life.

You need to have strong math skills, especially in basic calculus, linear algebra, and statistics before starting to learn advanced statistics. It's important that you have strong technical skills and are very comfortable on the computer, strong analytical skills, and the ability to carefully examine and question data that is presented to you so that you can organize and draw conclusions from it. For learning some concepts in advanced statistics, you'll need to have experience using the R statistical software package and understand Bayesian estimation, principles of maximum-likelihood estimation, and calculus-based probability.

People who enjoy mathematics are best suited for roles in advanced statistics, especially those who enjoy concepts like probability, linear models, and statistics and how they relate to data science. They can quickly grasp and apply complex technical concepts as well. Those who enjoy testing hypotheses and figuring out uncertain outcomes based on probability are also well suited for roles in advanced statistics. Also, people who have wide-ranging computer skills, the ability to communicate their statistical findings in plain language, problem-solving and analytical skills, and teamwork and collaborative skills are best suited for roles involving advanced statistics.

If you're aspiring to be a biostatistician or data scientist, learning advanced statistics is probably right for you. If you're interested in machine learning and the development of data products, you may also find learning advanced statistics is right for you. People who want to have a career as a statistician, statistical epidemiologist, sports analyst, actuary, market researcher, or investment analyst may also find learning advanced statistics to be the right choice. And if you need to understand how to transform complex sets of data into practical applications, learning advanced statistics is right for you.

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Other topics to explore

- Google Data Analyst
- Google Digital Marketing & E-commerce Professional Certificate
- Google IT Automation with Python Professional Certificate
- Google IT Support
- Google Project Management
- Google UX Design
- Preparing for Google Cloud Certification: Cloud Architect
- IBM Cybersecurity Analyst
- IBM Data Analyst
- IBM Data Engineering
- IBM Data Science
- IBM Full Stack Cloud Developer
- IBM Machine Learning
- Intuit Bookkeeping
- Meta Front-End Developer
- DeepLearning.AI TensorFlow Developer Professional Certificate
- SAS Programmer Professional Certificate
- Launch your career
- Prepare for a certification
- Advance your career
- How to Identify Python Syntax Errors
- How to Catch Python Exceptions
- See all Programming Tutorials

- Free Courses
- Artificial Intelligence Courses
- Blockchain Courses
- Computer Science Courses
- Cursos Gratis
- Cybersecurity Courses
- Data Analysis Courses
- Data Science Courses
- English Speaking Courses
- Full Stack Web Development Courses
- Google Courses
- Human Resources Courses
- IT Courses
- Learning English Courses
- Microsoft Excel Courses
- Product Management Courses
- Project Management Courses
- Python Courses
- SQL Courses
- Agile Certifications
- CAPM Certification
- CompTIA A+ Certification
- Data Analytics Certifications
- Scrum Master Certifications
- See all courses

- Free online courses you can finish in a day
- Popular Free Courses
- Business Jobs
- Cybersecurity Jobs
- Entry-Level IT Jobs
- Data Analyst Interview Questions
- Data Analytics Projects
- How to Become a Data Analyst
- How to Become a Project Manager
- IT Skills
- Project Manager Interview Questions
- Python Programming Skills
- Strength and Weakness in Interview
- What Does a Data Analyst Do
- What Does a Software Engineer Do
- What Is a Data Engineer
- What Is a Data Scientist
- What Is a Product Designer
- What Is a Scrum Master
- What Is a UX Researcher
- How to Get a PMP Certification
- PMI Certifications
- Popular Cybersecurity Certifications
- Popular SQL Certifications
- Read all Coursera Articles

- Google Professional Certificates
- Professional Certificates
- See all certificates
- Bachelor's Degrees
- Master's Degrees
- Computer Science Degrees
- Data Science Degrees
- MBA & Business Degrees
- Data Analytics Degrees
- Public Health Degrees
- Social Sciences Degrees
- Management Degrees
- BA vs BS Degree
- What is a Bachelor's Degree?
- 11 Good Study Habits to Develop
- How to Write a Letter of Recommendation
- 10 In-Demand Jobs You Can Get with a Business Degree
- Is a Master's in Computer Science Worth it?
- See all degree programs
- Coursera India
- Coursera UK
- Coursera Mexico