Statistical Inference

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Statistical Inference for Estimation in Data Science (Coursera) Coursera
University of Colorado Boulder

Statistical Inference for Estimation in Data Science (Coursera)

Dive into Statistical Inference for Estimation in Data Science—a course that equips you with the essential skills needed to make accurate predictions and draw reliable conclusions from your data. This course covers key topics like sampling distributions, confidence intervals, method of moments estimation, maximum likelihood estimation, and more, providing a strong foundation in statistical inference techniques.

May 18th 2026
5-12 Weeks
Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera) Coursera
University of Colorado Boulder

Statistical Inference and Hypothesis Testing in Data Science Applications (Coursera)

Dive into the world of Statistical Inference and Hypothesis Testing with this engaging online course tailored for aspiring and professional data scientists. This course will equip you with a deep understanding of hypothesis testing, enabling you to make accurate decisions based on your data analysis. Explore key concepts such as error rates, power of tests, p-values, and their practical applications in real-world scenarios. Whether you're looking to refine your analytical skills or seeking to advance in the field of data science, this course offers a pathway to mastering statistical inference techniques crucial for making informed decisions from data.

May 18th 2026
5-12 Weeks
Data Modeling and Regression Analysis in Business (Coursera) Coursera
University of Illinois at Urbana-Champaign

Data Modeling and Regression Analysis in Business (Coursera)

Dive into the world of Data Modeling and Regression Analysis in Business with this specialized Coursera course. Whether you're a manager looking to harness the power of data or an aspiring analyst eager to refine your skills, this course offers a structured pathway to understanding key concepts like data description, statistical inference, and regression analysis. By the end of this course, you'll be equipped with the tools needed for effective prediction and decision-making in business settings.

Sep 11th 2023
4 Weeks
Preparing for the AP* Statistics Exam (edX) EdX
Tennessee Board of Regents - TBR

Preparing for the AP* Statistics Exam (edX)

Dive into a detailed exploration of statistical concepts and tools designed to enhance your ability to collect, analyze, and draw meaningful conclusions from data. This course is perfect for students preparing for the AP* Statistics Exam, aiming to build a strong foundation in statistics and improve their analytical skills.

No sessions available
+25 Weeks
Big Data: Statistical Inference and Machine Learning (FutureLearn) FutureLearn
Queensland University of Technology

Big Data: Statistical Inference and Machine Learning (FutureLearn)

Dive into the world of big data analytics with our expert-led course on Statistical Inference and Machine Learning. This course is designed to equip you with the essential skills needed to navigate, analyze, and derive actionable insights from vast and complex datasets. Whether you're a beginner or looking to advance your expertise, this program offers a structured approach to understanding and applying statistical methods and machine learning techniques in real-world scenarios.

No sessions available
2 Weeks
Statistics and R (edX) EdX
HarvardX,Harvard University

Statistics and R (edX)

Dive into the world of data analysis with 'Statistics and R' on edX. This course is perfect for beginners in the life sciences who want to understand basic statistical concepts and learn how to use R programming to analyze data. Gain proficiency in computing p-values and constructing confidence intervals, all while enhancing your R skills.

Self Paced
Self-Paced
Statistical Inference and Modeling for High-throughput Experiments (edX) EdX
HarvardX,Harvard University

Statistical Inference and Modeling for High-throughput Experiments (edX)

Dive into Statistical Inference and Modeling for High-throughput Experiments to gain a deep understanding of statistical techniques applied to large-scale biological datasets. This course covers essential topics such as error rate controlling procedures, false discovery rates, q-values, and parametric modeling with applications in high-throughput data analysis.

Self Paced
Self-Paced