What is statistical inference?

Statistical inference is the process whereby you can draw conclusions about a population based on random samples of that population and the statistics that you draw from those samples. When you rely on statistical inference, you take what you've observed about your samples of that population and apply them to the group as a whole. Applying statistical inference allows you to take what you know about the population as well as what's uncertain to make statements about the entire population based on your analysis.

Why is it important to learn about statistical inference?

If you want to learn about a certain population—whether they're customers or fellow employees—you can use statistical inference to draw conclusions about that population based on your analysis of data about them. You can't always survey or test an entire population to gain insight, but you can sample the population and make educated assumptions based on the data. Understanding statistical inference allows you to take that data and use it to draw conclusions that make sense and prove true.

How can I apply statistical inference in my career?

Statistical inference has plenty of benefits for different business sectors. Statisticians and data analysts use this method often to draw conclusions based on samples of populations. If you're in sales or product development, you can use statistical inference to determine which brands or products are popular with your customers or clients. Scientists use statistical inference to test hypotheses and draw conclusions when it's impossible for them to test or sample an entire population. You can apply statistical inference to analyze the data from surveys of any population that you sample.

How can online courses on Coursera help me learn about statistical inference?

Online courses on Coursera give you both a grasp of the concepts of statistical inference and practical applications. You'll learn from the best instructors in the academic world, and you can learn at a pace and schedule that best suits your schedule and lifestyle. When you finish our courses, you'll know how to use statistical inference in your career, which will give you an advantage whether you're trying to get better at your current job or whether you're looking to make a career change.

What are the benefits of taking an online Statistical Inference course?

Online Statistical Inference courses offer a convenient and flexible way to enhance your knowledge or learn new Statistical Inference skills. Choose from a wide range of Statistical Inference courses offered by top universities and industry leaders tailored to various skill levels.

What Statistical Inference courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Statistical Inference, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Top Statistical Inference Courses - Learn Statistical Inference Online

Explore the Statistical Inference Course Catalog

University of Minnesota
Statistical Molecular Thermodynamics
Skills you'll gain: Physics, Thermal Management, Chemistry, Physical Science, Engineering Calculations, Applied Mathematics, Calculus, Mathematical Modeling
4.9
Rating, 4.9 out of 5 stars
358 reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
Microsoft
Microsoft Data Visualization
Skills you'll gain: Data Storytelling, Data Analysis Expressions (DAX), Data Presentation, Power BI, Data Ethics, Dashboard, Data Visualization Software, Data Modeling, Data Governance, Extract, Transform, Load, Interactive Data Visualization, Business Intelligence, Data Analysis, Statistical Analysis, Data Architecture, Correlation Analysis, Data Cleansing, Data Transformation, Database Design, Statistical Visualization
4.7
Rating, 4.7 out of 5 stars
67 reviews
Beginner · Professional Certificate · 3 - 6 Months
Status: Free Trial
Johns Hopkins University
The R Programming Environment
Skills you'll gain: Tidyverse (R Package), Web Scraping, Data Manipulation, R Programming, Data Transformation, Data Cleansing, Data Science, Big Data, Text Mining, Data Import/Export, Programming Principles, Data Structures, Performance Tuning, Debugging, Application Programming Interface (API)
4.3
Rating, 4.3 out of 5 stars
1.2K reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Imperial College London
Study Designs in Epidemiology
Skills you'll gain: Clinical Trials, Research Design, Epidemiology, Clinical Research, Research Methodologies, Research, Statistical Analysis, Sample Size Determination, Data Analysis
4.8
Rating, 4.8 out of 5 stars
602 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
Johns Hopkins University
Data and Health Indicators in Public Health Practice
Skills you'll gain: Epidemiology, Public Health, Health Policy, Health Care, Infectious Diseases, Health Information Management, Data Analysis, Program Evaluation, Data Collection, Descriptive Analytics, Statistical Methods
4.7
Rating, 4.7 out of 5 stars
1.2K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
Johns Hopkins University
Getting Started with Data Visualization in R
Skills you'll gain: Rmarkdown, Statistical Visualization, Ggplot2, Data Import/Export, Data Visualization Software, R Programming, Tidyverse (R Package), Data Manipulation, Scatter Plots, Data Wrangling, Histogram, Software Installation
4.8
Rating, 4.8 out of 5 stars
289 reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
University of Washington
Machine Learning: Clustering & Retrieval
Skills you'll gain: Unsupervised Learning, Bayesian Statistics, Applied Machine Learning, Data Mining, Statistical Machine Learning, Big Data, Statistical Inference, Text Mining, Statistical Modeling, Machine Learning Algorithms, Unstructured Data, Machine Learning, Sampling (Statistics), Scalability, Probability Distribution, Algorithms
4.7
Rating, 4.7 out of 5 stars
2.4K reviews
Mixed · Course · 1 - 3 Months
Status: Free Trial
University at Buffalo
Intelligent Machining
Skills you'll gain: Control Systems, Machine Controls, Manufacturing Processes, Internet Of Things, Automation, Software Systems, Real Time Data, Artificial Intelligence, Machine Learning, Open Source Technology
4.6
Rating, 4.6 out of 5 stars
1.4K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
Johns Hopkins University
Statistical Methods for Computer Science
Skills you'll gain: Network Analysis, R Programming, Statistical Analysis, Regression Analysis, Statistical Modeling, Statistical Methods, Combinatorics, Bayesian Network, Statistical Hypothesis Testing, Data Analysis, Probability, Probability & Statistics, Bayesian Statistics, Probability Distribution, Simulations, Data Science, Markov Model, Applied Mathematics, Graph Theory, Statistics
Intermediate · Specialization · 3 - 6 Months
Karlsruhe Institute of Technology
Machine Translation
Skills you'll gain: Natural Language Processing, Artificial Neural Networks, Deep Learning, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Language Interpretation, Translation, and Studies, Statistical Modeling, Vocabulary, Analysis, Performance Tuning
4.5
Rating, 4.5 out of 5 stars
177 reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Imperial College London
Linear Regression in R for Public Health
Skills you'll gain: Correlation Analysis, Regression Analysis, Data Analysis, R Programming, Descriptive Statistics, Statistical Modeling, Exploratory Data Analysis, Statistical Analysis, Statistical Programming, Statistical Software, Statistical Methods, Probability & Statistics, Biostatistics, Epidemiology, Data Import/Export
4.8
Rating, 4.8 out of 5 stars
520 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
Imperial College London
Introduction to Digital health
Skills you'll gain: Health Technology, Telehealth, Health Disparities, Health Informatics, Health Care, Health Systems, Electronic Medical Record, Interoperability, Public Health, Epidemiology, Big Data, Digital Transformation, Health Information Management, Machine Learning, Artificial Intelligence
4.5
Rating, 4.5 out of 5 stars
230 reviews
Intermediate · Course · 1 - 4 Weeks