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

Status: New
Johns Hopkins University
Advanced Neural Network Techniques
Skills you'll gain: Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Unsupervised Learning, Data Ethics, Artificial Intelligence, Machine Learning, Markov Model, Natural Language Processing
Intermediate · Course · 1 - 3 Months
University of Colorado System
Particle Filters (and Navigation)
Skills you'll gain: Bayesian Network, Numerical Analysis, Estimation, Simulations, Matlab, Global Positioning Systems, Mathematical Modeling, Applied Mathematics, Algorithms, Computer Programming Tools
Intermediate · Course · 1 - 4 Weeks
Status: New
Status: Free
Maven Analytics
Complete Visual Guide to Machine Learning
Skills you'll gain: Unsupervised Learning, Regression Analysis, Exploratory Data Analysis, Time Series Analysis and Forecasting, Data Analysis, Statistical Analysis, Data Science, Data Mining, Workflow Management, Machine Learning, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Histogram, Data Quality, Anomaly Detection, Feature Engineering, Dimensionality Reduction, Quality Assurance, Random Forest Algorithm
Beginner · Course · 1 - 3 Months
Status: New
LearnKartS
AWS AI Practitioner
Skills you'll gain: Prompt Engineering, Large Language Modeling, AWS SageMaker, Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Computer Vision, AWS Identity and Access Management (IAM), Natural Language Processing, Amazon Web Services, Supervised Learning, Data Governance, OpenAI, Machine Learning Algorithms, Identity and Access Management, Feature Engineering, Machine Learning, Artificial Neural Networks, ChatGPT, Data Ethics, Data Management
Beginner · Specialization · 1 - 3 Months
École Polytechnique Fédérale de Lausanne
Geographical Information Systems - Part 2
Skills you'll gain: Spatial Analysis, Spatial Data Analysis, GIS Software, Geographic Information Systems, Geospatial Mapping, Geostatistics, Interactive Data Visualization, Data Integration, Data Mapping, Augmented Reality, Sampling (Statistics)
Beginner · Course · 1 - 3 Months
Status: New
Coursera Project Network
Scripting with Alteryx: Python and R for Advanced Workflows
Skills you'll gain: Alteryx, Predictive Modeling, Scripting, R Programming, Predictive Analytics, Advanced Analytics, Trend Analysis, Exploratory Data Analysis, Applied Machine Learning, Data Manipulation, Data Analysis, Employee Retention, Data Transformation, Risk Modeling
Intermediate · Guided Project · Less Than 2 Hours
University of Minnesota
Social Determinants of Health: Methodological Opportunities
Skills you'll gain: Community Health, Health Informatics, Health Equity, Health Policy, Statistical Analysis, Research Methodologies, Data Analysis, Public Health, Health Information Management, Program Evaluation, Data Collection, Data Visualization
Beginner · Course · 1 - 3 Months
Status: Free
University of Maryland, College Park
Cómo manejar datos faltantes
Skills you'll gain: Sampling (Statistics), Data Quality, Stata, Statistical Analysis, Statistical Software, Statistical Methods, Data Analysis, Regression Analysis, Data Integrity, R Programming
Mixed · Course · 1 - 3 Months
Status: New
University of Colorado Boulder
BiteSize Python: NumPy and Pandas
Skills you'll gain: Pandas (Python Package), NumPy, Data Structures, Data Import/Export, Data Manipulation, Data Cleansing, Statistical Methods, Data Analysis, Exploratory Data Analysis
Intermediate · Course · 1 - 3 Months
Status: Free
Johns Hopkins University
Mathematics and Democracy Teach Out
Skills you'll gain: Game Theory, Mathematical Modeling, Political Sciences, Combinatorics, Social Sciences, Probability, Applied Mathematics, Statistical Analysis
Beginner · Course · 1 - 4 Weeks
Status: New
University of Glasgow
Fundamental MATLAB Programming for AI
Skills you'll gain: Matlab, Data Manipulation, Artificial Intelligence, Data Cleansing, Programming Principles, Computer Programming, Machine Learning, Scripting, Data Structures, Program Development, Plot (Graphics), Debugging
Beginner · Course · 1 - 4 Weeks
Coursera Project Network
Auto Machine Learning (AutoML) Using AutoGluon
Skills you'll gain: Applied Machine Learning, Machine Learning, MLOps (Machine Learning Operations), Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Amazon Web Services, Prototyping
Beginner · Guided Project · Less Than 2 Hours