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: Free Trial
University of California, Santa Cruz
Bayesian Statistics: From Concept to Data Analysis
Skills you'll gain: Bayesian Statistics, Statistical Inference, Data Analysis, Probability, Statistical Modeling, Statistical Analysis, Microsoft Excel, Probability Distribution, R Programming, Regression Analysis
4.6
Rating, 4.6 out of 5 stars
3.2K reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
DeepLearning.AI
Deep Learning
Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Tensorflow, Supervised Learning, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Debugging, Performance Tuning, Keras (Neural Network Library), Python Programming, Machine Learning Algorithms, Analysis, Data Processing
Build toward a degree
4.8
Rating, 4.8 out of 5 stars
146K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
IBM
Tools for Data Science
Skills you'll gain: Jupyter, Data Visualization Software, Data Science, GitHub, Big Data, R Programming, Statistical Programming, Application Programming Interface (API), Machine Learning, Cloud Computing, Git (Version Control System), Version Control, Other Programming Languages, Query Languages
4.5
Rating, 4.5 out of 5 stars
30K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
Duke University
Java Programming and Software Engineering Fundamentals
Skills you'll gain: Object Oriented Programming (OOP), Java, Hypertext Markup Language (HTML), Software Design, Software Design Patterns, Data Structures, HTML and CSS, Debugging, Software Engineering, Cascading Style Sheets (CSS), Web Development, Computer Programming, Programming Principles, Javascript, Encryption, Algorithms, AI Personalization, Web Design, Data Processing, Statistical Analysis
4.6
Rating, 4.6 out of 5 stars
22K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
SAS
SAS Statistical Business Analyst
Skills you'll gain: SAS (Software), Predictive Modeling, Predictive Analytics, Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, Statistical Modeling, Regression Analysis, Exploratory Data Analysis, Statistical Methods, Probability & Statistics, Big Data, Plot (Graphics), Data Analysis, Data Literacy, Data Analysis Software, Advanced Analytics, Statistical Machine Learning, Feature Engineering, Performance Analysis
4.6
Rating, 4.6 out of 5 stars
220 reviews
Intermediate · Professional Certificate · 3 - 6 Months
Status: Free Trial
University of Colorado Boulder
Statistical Inference and Hypothesis Testing in Data Science Applications
Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Probability & Statistics, Data Ethics, Statistical Analysis, Quantitative Research, Statistical Inference, Statistics, Sample Size Determination, Sampling (Statistics)
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
50 reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
IBM
IBM Data Management
Skills you'll gain: Dashboard, Data Storytelling, Data Warehousing, SQL, Data Governance, Data Security, Data Migration, Database Design, Data Literacy, Descriptive Statistics, Extract, Transform, Load, Data Mining, Cloud Storage, Data Visualization Software, Data Store, IBM DB2, Data Management, Relational Databases, MySQL, Excel Formulas
4.7
Rating, 4.7 out of 5 stars
17K reviews
Beginner · Professional Certificate · 3 - 6 Months
University of Cape Town
Understanding Clinical Research: Behind the Statistics
Skills you'll gain: Biostatistics, Statistical Hypothesis Testing, Statistical Methods, Probability & Statistics, Clinical Research, Statistical Analysis, Quantitative Research, Descriptive Statistics, Statistical Inference, Data Collection, Probability
4.8
Rating, 4.8 out of 5 stars
3.6K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
University of Washington
Machine Learning
Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms
4.6
Rating, 4.6 out of 5 stars
16K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
University of Michigan
Fitting Statistical Models to Data with Python
Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Analysis, Statistical Programming, Regression Analysis, Predictive Modeling, Jupyter, Exploratory Data Analysis, Statistical Hypothesis Testing, Correlation Analysis, Probability Distribution
4.4
Rating, 4.4 out of 5 stars
702 reviews
Intermediate · Course · 1 - 4 Weeks
University of London
Probability and Statistics: To p or not to p?
Skills you'll gain: Descriptive Statistics, Statistics, Probability & Statistics, Statistical Hypothesis Testing, Data Visualization, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Probability Distribution, Sampling (Statistics), Risk Modeling, Statistical Inference, Mathematical Modeling
4.6
Rating, 4.6 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
University of Pennsylvania
Fundamentals of Quantitative Modeling
Skills you'll gain: Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Financial Modeling, Business Mathematics, Markov Model, Probability, Predictive Analytics, Process Optimization, Risk Management, Statistics, Probability Distribution, Simulation and Simulation Software, Forecasting
4.6
Rating, 4.6 out of 5 stars
9.1K reviews
Mixed · Course · 1 - 4 Weeks