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

DeepLearning.AI
Advanced Learning Algorithms
Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Supervised Learning, Deep Learning, Random Forest Algorithm, Artificial Neural Networks, Algorithms, Performance Tuning
4.9
Rating, 4.9 out of 5 stars
7.7K reviews
Beginner · Course · 1 - 4 Weeks
Rice University
Business Statistics and Analysis
Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Methods, Statistical Analysis, Statistical Modeling, Statistical Inference, Excel Formulas, Data Analysis, Data Presentation, Statistics, Analytical Skills, Estimation
4.7
Rating, 4.7 out of 5 stars
13K reviews
Beginner · Specialization · 3 - 6 Months
IBM
Data Science Fundamentals with Python and SQL
Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Relational Databases, Statistical Hypothesis Testing, Web Scraping, Databases, Stored Procedure, Automation, Software Development Tools, Data Science, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
71K reviews
Beginner · Specialization · 3 - 6 Months
Duke University
Introduction to Probability and Data with R
Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Statistical Software, Data Science, Descriptive Statistics
4.7
Rating, 4.7 out of 5 stars
5.7K reviews
Beginner · Course · 1 - 3 Months
Status: Free
Stanford University
Game Theory
Skills you'll gain: Game Theory, Business Strategy, Strategic Decision-Making, Mathematical Modeling, Graph Theory, Bayesian Statistics, Statistical Modeling, Bidding, Decision Making, Behavioral Economics, Probability, Economics, Competitive Analysis, Algorithms, Theoretical Computer Science, Human Learning, Probability Distribution
4.6
Rating, 4.6 out of 5 stars
4.8K reviews
Beginner · Course · 1 - 3 Months
University of Michigan
Introduction to Data Science in Python
Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles
4.5
Rating, 4.5 out of 5 stars
27K reviews
Intermediate · Course · 1 - 4 Weeks
University of Colorado Boulder
Statistical Inference and Hypothesis Testing in Data Science Applications
Skills you'll gain: Statistical Hypothesis Testing, Probability & Statistics, Data Ethics, Statistical Analysis, Quantitative Research, Statistical Inference, Sample Size Determination, Sampling (Statistics), Probability Distribution
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
50 reviews
Intermediate · Course · 1 - 3 Months
Status: Free
University of London
Probability and Statistics: To p or not to p?
Skills you'll gain: Descriptive Statistics, Probability & Statistics, Statistical Methods, Statistical Hypothesis Testing, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Statistical Visualization, Probability Distribution, Statistical Analysis, Data Presentation, Sampling (Statistics), Statistical Inference, Mathematical Modeling, Decision Tree Learning, Applied Mathematics
4.6
Rating, 4.6 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 3 Months
Duke University
Bayesian Statistics
Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Analysis, Regression Analysis, Data Analysis, R Programming, Probability, Probability Distribution
3.8
Rating, 3.8 out of 5 stars
796 reviews
Intermediate · Course · 1 - 3 Months
Arizona State University
Experimental Design Basics
Skills you'll gain: Experimentation, Sample Size Determination, Research Design, Statistical Analysis, Statistical Methods, Statistical Hypothesis Testing, Sampling (Statistics), Statistical Software, A/B Testing, Data Analysis, Estimation, Descriptive Statistics, Quality Control, Variance Analysis
4.7
Rating, 4.7 out of 5 stars
294 reviews
Intermediate · Course · 1 - 3 Months
Johns Hopkins University
Mathematical Biostatistics Boot Camp 1
Skills you'll gain: Sampling (Statistics), Bayesian Statistics, Probability & Statistics, Statistical Inference, Statistical Methods, Probability, Probability Distribution, Data Analysis, Statistical Analysis, Biostatistics
4.4
Rating, 4.4 out of 5 stars
513 reviews
Mixed · Course · 1 - 4 Weeks
University of California, Davis
Learn SQL Basics for Data Science
Skills you'll gain: Data Governance, Presentations, Data Cleansing, Feature Engineering, SQL, Apache Spark, A/B Testing, Distributed Computing, Descriptive Statistics, Data Lakes, Data Quality, Data Storytelling, Peer Review, Exploratory Data Analysis, Data Manipulation, Data Pipelines, JSON, Statistical Analysis, Database Design, Query Languages
4.6
Rating, 4.6 out of 5 stars
18K reviews
Beginner · Specialization · 3 - 6 Months