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 Colorado Boulder
Statistical Inference for Estimation in Data Science
Skills you'll gain: Statistical Inference, Statistical Methods, Probability & Statistics, Sampling (Statistics), Data Science, Statistical Analysis, Probability Distribution
4.1
Rating, 4.1 out of 5 stars
88 reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
University of Michigan
Inferential Statistical Analysis with Python
Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Statistical Inference, Statistics, Bayesian Statistics, Probability & Statistics, Statistical Analysis, Data Analysis, Jupyter, Python Programming, Matplotlib, NumPy
4.6
Rating, 4.6 out of 5 stars
918 reviews
Intermediate · Course · 1 - 4 Weeks
University of Pennsylvania
A Crash Course in Causality: Inferring Causal Effects from Observational Data
Skills you'll gain: R Programming, Statistical Analysis, Statistical Methods, Statistical Software, Statistical Modeling, Statistical Inference, Data Analysis, Probability & Statistics, Regression Analysis, Research Design, Graph Theory
4.7
Rating, 4.7 out of 5 stars
564 reviews
Intermediate · Course · 1 - 3 Months
Duke University
Data Science Math Skills
Skills you'll gain: Probability, Bayesian Statistics, General Mathematics, Calculus, Graphing, Statistics, Data Science, Data Analysis, Plot (Graphics), Algebra, Geometry, Arithmetic, Derivatives
4.5
Rating, 4.5 out of 5 stars
13K reviews
Beginner · Course · 1 - 3 Months
Status: Free
École normale supérieure
Statistical Mechanics: Algorithms and Computations
Skills you'll gain: Sampling (Statistics), Physics, Simulations, Statistical Programming, Computational Logic, Numerical Analysis, Markov Model, Mechanics, Quantitative Research, Algorithms, Programming Principles, Applied Mathematics, Linear Algebra, Integral Calculus
4.8
Rating, 4.8 out of 5 stars
264 reviews
Mixed · Course · 1 - 3 Months
Status: Free Trial
IBM
Introduction to Artificial Intelligence (AI)
Skills you'll gain: Large Language Modeling, Artificial Intelligence, OpenAI, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), ChatGPT, Deep Learning, Business Transformation, Artificial Neural Networks, Digital Transformation, Prompt Engineering, Automation, Machine Learning, Governance, Business Technologies, Natural Language Processing, Computer Vision, Ethical Standards And Conduct, Applied Machine Learning
4.7
Rating, 4.7 out of 5 stars
19K reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
IBM
Introduction to Data Analytics
Skills you'll gain: Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Data Wrangling, Apache Hive, Data Collection, Data Mart, Data Warehousing, Analytics, Apache Spark, Data Cleansing, Data Lakes, Extract, Transform, Load, Data Visualization Software
4.8
Rating, 4.8 out of 5 stars
19K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
IBM
Machine Learning with Python
Skills you'll gain: Supervised Learning, Feature Engineering, Jupyter, Unsupervised Learning, Scikit Learn (Machine Learning Library), Python Programming, Predictive Modeling, Machine Learning, Dimensionality Reduction, Classification And Regression Tree (CART), Matplotlib, NumPy, Regression Analysis, Statistical Modeling
4.7
Rating, 4.7 out of 5 stars
17K reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Duke University
Data Analysis with R
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Literacy
4.7
Rating, 4.7 out of 5 stars
7.5K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
Google
Google Advanced Data Analytics
Skills you'll gain: Exploratory Data Analysis, Data Storytelling, Statistical Hypothesis Testing, Data Ethics, Data Visualization Software, Sampling (Statistics), Data Presentation, Regression Analysis, Feature Engineering, Data Transformation, Descriptive Statistics, Professional Networking, Data Visualization, Tableau Software, Data Manipulation, Statistical Analysis, Statistical Machine Learning, Object Oriented Programming (OOP), Data Analysis, Interviewing Skills
Build toward a degree
4.7
Rating, 4.7 out of 5 stars
6.4K reviews
Advanced · Professional Certificate · 3 - 6 Months
Status: Free Trial
Google
The Power of Statistics
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Descriptive Statistics, Data Analysis, Statistical Analysis, Probability Distribution, Statistical Methods, Advanced Analytics, Analytics, Statistics, Data Literacy, Statistical Inference, Probability, Statistical Software, Statistical Programming, A/B Testing, Sample Size Determination, Jupyter, Technical Communication
4.8
Rating, 4.8 out of 5 stars
790 reviews
Advanced · Course · 1 - 3 Months
Status: Free Trial
Johns Hopkins University
Data Science: Statistics and Machine Learning
Skills you'll gain: Shiny (R Package), Rmarkdown, Regression Analysis, Leaflet (Software), Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Data Visualization, Statistical Machine Learning, Feature Engineering, Statistical Analysis, Statistical Modeling, Probability, Data Science, Data Analysis
4.4
Rating, 4.4 out of 5 stars
7.2K reviews
Intermediate · Specialization · 3 - 6 Months