
Johns Hopkins University
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, Probability Distribution, R Programming, Biostatistics, Data Analysis, Data Science, Statistics, Mathematical Modeling, Analysis, Data Modeling
★ 4.4 (797) · Advanced · Specialization · 3 - 6 Months

Skills you'll gain: A/B Testing, Sampling (Statistics), Data Analysis, Analytics, Statistics, Descriptive Statistics, Statistical Analysis, Statistical Hypothesis Testing, Probability & Statistics, Statistical Software, Advanced Analytics, Probability Distribution, Data Science, Statistical Inference, Statistical Programming, Statistical Methods, Probability, Python Programming
★ 4.8 (890) · Advanced · Course · 1 - 3 Months

Illinois Tech
Skills you'll gain: Machine Learning Algorithms, Model Evaluation, Statistical Analysis, Bayesian Statistics, Data Visualization, Statistical Inference, Exploratory Data Analysis, Statistical Methods, Data Presentation, Analysis, Probability & Statistics, Data Cleansing, Applied Machine Learning, Regression Analysis, Analytics, Statistical Programming, Data Analysis, Logistic Regression, R Programming, Verification And Validation
★ 4.5 (48) · Intermediate · Specialization · 3 - 6 Months

University of Michigan
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Methods, Statistical Inference, Statistics, Bayesian Statistics, Data Visualization, Plot (Graphics), Matplotlib, Statistical Visualization, Statistical Software, Probability & Statistics, Model Evaluation, Statistical Programming, Data-Driven Decision-Making, Seaborn, Statistical Analysis, Jupyter, Python Programming
★ 4.6 (3.3K) · Beginner · Specialization · 1 - 3 Months

Skills you'll gain: Pivot Tables And Charts, Microsoft Excel, Excel Formulas, Data Validation, Spreadsheet Software, Data Manipulation, Data Analysis, Statistical Analysis, Data Visualization Software, Descriptive Statistics, Interactive Data Visualization, Data Processing, Data Integrity
Intermediate · Course · 3 - 6 Months

University of Colorado Boulder
Skills you'll gain: Probability, Statistical Inference, Estimation, Probability & Statistics, Statistical Methods, Probability Distribution, Statistics, Bayesian Statistics, Markov Model, Statistical Analysis, Sampling (Statistics), Applied Mathematics, Artificial Intelligence, Machine Learning Methods, Generative AI, Data Analysis, Correlation Analysis, Data Science, Machine Learning Algorithms, Mathematical Theory & Analysis
★ 4.4 (350) · Intermediate · Specialization · 3 - 6 Months

Skills you'll gain: Dashboard, Compensation Analysis, Dashboard Creation, Microsoft Excel, Employee Retention, People Analytics, Training and Development, Compensation Management, Recruitment, Excel Macros, Spreadsheet Software, Talent Recruitment, Payroll, Employee Training, Data Visualization, Payroll Processing, Training Programs, Human Resource Strategy, Workforce Planning, Human Resource Management
Mixed · Course · 1 - 3 Months

Macquarie University
Skills you'll gain: Data-Driven Decision-Making, Microsoft Excel, Forecasting, Regression Analysis, Data Literacy, Excel Formulas, Statistical Analysis, Data Analysis Software, Time Series Analysis and Forecasting, Spreadsheet Software, Analytics, Data Visualization, Statistical Methods, Data Analysis, Statistics, Statistical Hypothesis Testing, Probability & Statistics, Statistical Inference, Statistical Modeling, Variance Analysis
★ 4.7 (34) · Advanced · Course · 1 - 3 Months

Vanderbilt University
Skills you'll gain: Prompt Engineering, Prompt Patterns, ChatGPT, Multimodal Prompts, Data Visualization, Plot (Graphics), Data Presentation, Statistical Visualization, File Management, Artificial Intelligence, AI Workflows, File I/O, Generative AI, Marketing Automation, Data Analysis, Business Process Automation, Document Management, Text Mining, Data Transformation, Automation
★ 4.8 (976) · Beginner · Course · 1 - 3 Months

Skills you'll gain: A/B Testing, Statistical Hypothesis Testing, Statistical Methods, Advanced Analytics, Statistical Analysis, Statistical Reporting, Correlation Analysis, Data Analysis, Report Writing, Analytics, Analysis, Analytical Skills, Quantitative Research, People Analytics, Workflow Management, Business Analytics, Data-Driven Decision-Making, Business Process Automation
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: Regression Analysis, Statistical Analysis, Time Series Analysis and Forecasting, Logistic Regression, R Programming, Statistical Hypothesis Testing, Probability & Statistics, Statistical Modeling, R (Software), Statistical Methods, Predictive Modeling, Generative AI, Forecasting, Power BI, Model Evaluation
Beginner · Course · 1 - 3 Months

Duke University
Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Reporting, R (Software), Statistical Methods, Statistics, R Programming, Statistical Software, Statistical Analysis, Probability & Statistics, Statistical Programming, Data Analysis, Sampling (Statistics), Probability Distribution, Software Installation
★ 4.8 (2.8K) · Beginner · Course · 1 - 3 Months
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.‎