Statistical Inference Courses and Certifications

MathTrackX: Statistics

6 ratings at edX

Understand fundamental concepts relating to statistical inference and how they can be applied to solve real world problems.

• edX
• 4 weeks, 3-6 hours/week
• Self-Paced
• Free Online Course (Audit)

Design and Analysis of Experiments | DoE

1080 ratings at Udemy

Design of Experiments: from ANOVA to Factorial Designs using Excel and R.

• Udemy
• 4 hours 2 minutes
• Self-Paced
• Paid Course

MathTrackX: Probability

Understand probability and how it manifests in the world around us.

• edX
• 4 weeks, 3-6 hours/week
• Self-Paced
• Free Online Course (Audit)

Ball State University

Statistical Methods for Data Science

Master statistical methods and probability theory for data science through hands-on applications in R, covering distributions, inference, multivariate analysis, and real-world problem-solving techniques.

• Coursera
• 1 day 15 hours 59 minutes
• Self-Paced
• Paid Course

Variable Selection, Model Validation, Nonlinear Regression

Master advanced regression techniques for data-driven industries. Learn logistic, Poisson, and robust regression, generalized linear models, and model validation using R for practical applications.

• Coursera
• 20 hours 43 minutes
• Self-Paced
• Paid Course

Bayesian Computational Statistics

Rigorous introduction to Bayesian inference, covering theory, computation, and practical implementation using statistical software. Explores advanced topics and applications in data analysis.

• Coursera
• 3 days 16 hours 39 minutes
• Self-Paced
• Paid Course

London School of Economics and Political Science Credential

Statistics Fundamentals

Comprehensive introduction to essential statistical concepts, methods, and techniques for quantitative careers or further study. Covers data analysis, probability, distribution theory, and statistical inference.

• edX
• 21 weeks, 9-12 hours/week
• Self-Paced
• $996.00
• 4 courses

Statistical Methods and Data Analysis

Discover statistical methods and R programming for data analysis, covering visualization, descriptive statistics, probability, sampling, significance tests, regression, and big data techniques.

• Coursera
• 20 hours 23 minutes
• Self-Paced
• Paid Course

Econometrics - Theory and Practice

Master econometric theory and practice through regression analysis, hypothesis testing, and statistical inference for analyzing economic relationships and data.

• Coursera
• 1 day 7 hours 43 minutes
• Self-Paced
• Paid Course

Corporate Finance Institute

Regression Analysis - Fundamentals & Practical Applications

Master linear regression techniques through hands-on practice in Excel and Python, from basic calculations to advanced modeling. Learn to interpret statistical outputs and make data-driven predictions for real business applications.

• Coursera
• 4 hours 8 minutes
• Self-Paced
• Paid Course

Credential

Statistical Analysis in R

Learn applied statistical data analysis using R, from basic inference to advanced modeling, with practical implementation and guidance on method selection.

• edX
• 12 weeks, 5-10 hours/week
• Self-Paced
• $618.00
• 2 courses

Data Science and Machine Learning for Business Professionals

Discover foundational data science and machine learning skills to make confident, data-driven decisions and communicate insights effectively to stakeholders in any professional setting.

• Coursera
• 10 hours 41 minutes
• Self-Paced
• Paid Course

Data Science Fundamentals Part 2: Unit 2

Master statistical inference through hypothesis testing, confidence intervals, and A/B testing while learning to distinguish correlation from causation for robust data analysis.

• Coursera
• 6 hours 9 minutes
• Self-Paced
• Paid Course

EDUCBA

Analyze Business Data Using Statistics Foundations

Master statistical analysis for business decisions through probability models, hypothesis testing, and data interpretation to drive evidence-based strategies.

• Coursera
• 13 hours 32 minutes
• Self-Paced
• Paid Course

Introduction to Probability

Master probability theory fundamentals from MIT, covering random variables, Bayesian inference, statistical analysis, and Markov chains for data analysis applications.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course