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 Pennsylvania
Introduction to Finance and Accounting
Skills you'll gain: Financial Statements, Return On Investment, Financial Statement Analysis, Finance, Financial Reporting, Capital Budgeting, Financial Accounting, Financial Modeling, Working Capital, Balance Sheet, Accrual Accounting, Accounting, Cash Flows, Income Statement, Generally Accepted Accounting Principles (GAAP), Financial Analysis, Tax Planning, Equities, Financial Planning, Corporate Finance
4.6
Rating, 4.6 out of 5 stars
14K reviews
Beginner · Specialization · 3 - 6 Months
Rice University
Business Applications of Hypothesis Testing and Confidence Interval Estimation
4.8
Rating, 4.8 out of 5 stars
1.3K reviews
Mixed · Course · 1 - 4 Weeks
Imperial College London
Introduction to Statistics & Data Analysis in Public Health
Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Statistical Analysis, Biostatistics, Data Analysis, Statistical Software, Exploratory Data Analysis, Quantitative Research, Probability & Statistics, Statistical Methods, R Programming, Statistics, Statistical Inference, Descriptive Statistics, Probability Distribution, Data Import/Export
4.7
Rating, 4.7 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 4 Weeks
IBM
Introduction to Data Science
Skills you'll gain: SQL, Jupyter, Data Mining, Peer Review, Data Modeling, Relational Databases, Databases, Stored Procedure, Database Management, Database Design, Data Science, Big Data, Data Cleansing, Data Visualization Software, Software Development Tools, Query Languages, GitHub, Business Analysis, Cloud Computing, Data Analysis
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
98K reviews
Beginner · Specialization · 3 - 6 Months
University of Michigan
Fitting Statistical Models to Data with Python
Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Software, Statistical Analysis, Statistical Programming, Regression Analysis, Predictive Modeling, Data Analysis, Exploratory Data Analysis, Statistical Hypothesis Testing, Correlation Analysis, Data Manipulation
4.4
Rating, 4.4 out of 5 stars
699 reviews
Intermediate · Course · 1 - 4 Weeks
Multiple educators
Data Science Foundations
Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Mining, Pandas (Python Package), Correlation Analysis, Web Scraping, NumPy, Probability & Statistics, Predictive Modeling, Big Data, Automation, Data Visualization Software, Data Collection, Software Development Tools, Data Science, GitHub, Machine Learning Algorithms, Unsupervised Learning
4.6
Rating, 4.6 out of 5 stars
112K reviews
Beginner · Specialization · 3 - 6 Months
DeepLearning.AI
Supervised Machine Learning: Regression and Classification
Skills you'll gain: Supervised Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Feature Engineering, Artificial Intelligence, Classification And Regression Tree (CART), Python Programming, Regression Analysis, Unsupervised Learning, Data-Driven Decision-Making
4.9
Rating, 4.9 out of 5 stars
28K reviews
Beginner · Course · 1 - 4 Weeks
IBM
Statistics for Data Science with Python
Skills you'll gain: Descriptive Statistics, Statistical Analysis, Data Analysis, Probability Distribution, Statistics, Data Visualization, Statistical Hypothesis Testing, Regression Analysis, Data Science, Matplotlib, Exploratory Data Analysis, Statistical Inference, Probability, Correlation Analysis, Pandas (Python Package), Jupyter
4.5
Rating, 4.5 out of 5 stars
432 reviews
Mixed · Course · 1 - 3 Months
University of California, Davis
SQL for Data Science
Skills you'll gain: Data Governance, SQL, Data Quality, Database Design, Query Languages, Data Manipulation, Data Modeling, Relational Databases, Data Science, Data Analysis, Descriptive Statistics
4.6
Rating, 4.6 out of 5 stars
17K reviews
Beginner · Course · 1 - 4 Weeks
Johns Hopkins University
Hypothesis Testing in Public Health
Skills you'll gain: Biostatistics, Sampling (Statistics), Statistical Inference, Scientific Methods, Quantitative Research, Epidemiology
4.8
Rating, 4.8 out of 5 stars
636 reviews
Beginner · Course · 1 - 3 Months
IIMA - IIM Ahmedabad
Pre-MBA Statistics
Skills you'll gain: Sampling (Statistics), Probability, Statistical Hypothesis Testing, Statistics, Probability Distribution, Statistical Methods, Statistical Inference, Estimation, Statistical Analysis, Descriptive Statistics, Sample Size Determination, Data Analysis, Data-Driven Decision-Making
4.6
Rating, 4.6 out of 5 stars
273 reviews
Beginner · Course · 1 - 3 Months
Stanford University
Probabilistic Graphical Models 2: Inference
Skills you'll gain: Bayesian Network, Statistical Inference, Markov Model, Statistical Machine Learning, Graph Theory, Sampling (Statistics), Applied Machine Learning, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms
4.6
Rating, 4.6 out of 5 stars
488 reviews
Advanced · Course · 1 - 3 Months