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

Johns Hopkins University
Statistical Inference
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability & Statistics, Probability, Statistics, Bayesian Statistics, Statistical Methods, Statistical Modeling, Statistical Analysis, Probability Distribution, Sampling (Statistics)
4.2
Rating, 4.2 out of 5 stars
4.4K reviews
Mixed · Course · 1 - 4 Weeks
University of Colorado Boulder
Data Science Foundations: Statistical Inference
Skills you'll gain: Statistical Hypothesis Testing, Probability, Statistical Inference, Statistical Methods, Probability Distribution, Probability & Statistics, Statistics, Bayesian Statistics, Data Science, Sampling (Statistics), Statistical Analysis, Data Ethics, Quantitative Research, Sample Size Determination, Descriptive Statistics
Build toward a degree
4.4
Rating, 4.4 out of 5 stars
315 reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free
Stanford University
Introduction to Statistics
Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Probability Distribution, Correlation Analysis
4.6
Rating, 4.6 out of 5 stars
3.9K reviews
Beginner · Course · 1 - 3 Months
Duke University
Inferential Statistics
Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Reporting, Statistical Methods, R Programming, Statistical Software, Statistical Analysis, Probability & Statistics, Data Analysis, Sampling (Statistics), Probability Distribution, Software Installation
4.8
Rating, 4.8 out of 5 stars
2.7K reviews
Beginner · Course · 1 - 3 Months
University of Michigan
Statistics with Python
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Inference, Statistical Methods, Bayesian Statistics, Data Visualization, Statistics, Matplotlib, Statistical Visualization, Statistical Software, Probability & Statistics, Statistical Analysis, Jupyter, Statistical Programming, Regression Analysis, Data Visualization Software, Predictive Modeling, Exploratory Data Analysis, Data Analysis
4.6
Rating, 4.6 out of 5 stars
3.3K reviews
Beginner · Specialization · 1 - 3 Months
University of California, Santa Cruz
Bayesian Statistics
Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Analysis, Probability, Statistical Machine Learning, Statistical Methods, Statistical Analysis, Advanced Analytics, Microsoft Excel, Markov Model, Probability Distribution, Probability & Statistics, Unsupervised Learning, Regression Analysis, Predictive Modeling
4.6
Rating, 4.6 out of 5 stars
3.5K reviews
Intermediate · Specialization · 3 - 6 Months
Google
The Power of Statistics
Skills you'll gain: Sampling (Statistics), Statistical Hypothesis Testing, Probability & Statistics, Advanced Analytics, Descriptive Statistics, Probability Distribution, Data Analysis, Analytics, Statistical Analysis, Probability, Statistical Methods, Data Science, A/B Testing, Statistics, Statistical Inference, Bayesian Statistics, Statistical Programming, Jupyter
4.8
Rating, 4.8 out of 5 stars
742 reviews
Advanced · Course · 1 - 3 Months
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, Statistical Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Modeling, Probability & Statistics, Probability, Statistics, Data Science, Descriptive Statistics, Predictive Modeling
4.7
Rating, 4.7 out of 5 stars
7.5K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free
Eindhoven University of Technology
Improving your statistical inferences
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Quantitative Research, Bayesian Statistics, Statistical Analysis, Statistical Methods, Sample Size Determination, Data Analysis, Research, Research Design, General Science and Research, Research Methodologies, Data Sharing, Probability
4.9
Rating, 4.9 out of 5 stars
791 reviews
Intermediate · Course · 1 - 3 Months
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 Inference, Data Analysis, Quantitative Research, Probability & Statistics, Regression Analysis, Research Design, Graph Theory
4.7
Rating, 4.7 out of 5 stars
561 reviews
Intermediate · Course · 1 - 3 Months
Johns Hopkins University
Advanced Statistics for Data Science
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Analysis, Data Science, Probability Distribution, Mathematical Modeling, Data Modeling, Applied Mathematics, Predictive Modeling
4.4
Rating, 4.4 out of 5 stars
754 reviews
Advanced · Specialization · 3 - 6 Months
Meta
Statistics Foundations
Skills you'll gain: Bayesian Statistics, Descriptive Statistics, Statistical Hypothesis Testing, Statistical Inference, Sampling (Statistics), Data Modeling, Statistics, Probability & Statistics, Statistical Analysis, Statistical Methods, Statistical Modeling, Marketing Analytics, Tableau Software, Data Analysis, Spreadsheet Software, Quantitative Research, Analytics, Descriptive Analytics, Time Series Analysis and Forecasting, Regression Analysis
4.7
Rating, 4.7 out of 5 stars
303 reviews
Beginner · Course · 1 - 3 Months