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 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
Johns Hopkins University
Regression Models
Skills you'll gain: Regression Analysis, Statistical Analysis, Statistical Modeling, Correlation Analysis, Data Analysis, Statistical Methods, Predictive Modeling, Probability & Statistics, Statistical Inference, Statistical Hypothesis Testing
4.4
Rating, 4.4 out of 5 stars
3.4K reviews
Mixed · Course · 1 - 4 Weeks
Coursera Project Network
Essential Causal Inference Techniques for Data Science
Skills you'll gain: Regression Analysis, Data Science, Data-Driven Decision-Making, R Programming, Statistical Inference, Applied Machine Learning, Machine Learning, Statistical Methods, Advanced Analytics, Data Analysis, Predictive Modeling
4.5
Rating, 4.5 out of 5 stars
35 reviews
Beginner · Guided Project · Less Than 2 Hours
Johns Hopkins University
R Programming
Skills you'll gain: Statistical Analysis, R Programming, Statistical Programming, Data Analysis, Debugging, Simulations, Program Development, Software Installation, Computer Programming, Data Structures, Performance Tuning, Data Import/Export
4.5
Rating, 4.5 out of 5 stars
22K reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free
University of Cape Town
Doing Clinical Research: Biostatistics with the Wolfram Language
Skills you'll gain: Descriptive Statistics, Plot (Graphics), Statistical Analysis, Statistical Programming, Biostatistics, Statistical Hypothesis Testing, Data Analysis, Quantitative Research, Data Visualization Software, Probability & Statistics, Deep Learning, Machine Learning
4.7
Rating, 4.7 out of 5 stars
49 reviews
Beginner · Course · 1 - 4 Weeks
Rice University
Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions
Skills you'll gain: Descriptive Statistics, Probability & Statistics, Probability Distribution, Business Analytics, Microsoft Excel, Data Analysis, Statistical Analysis, Box Plots, Sampling (Statistics), Correlation Analysis
4.7
Rating, 4.7 out of 5 stars
2.6K reviews
Mixed · Course · 1 - 4 Weeks
University of California, Santa Cruz
Bayesian Statistics: Mixture Models
Skills you'll gain: R Programming, Statistical Modeling, Bayesian Statistics, Statistical Machine Learning, Markov Model, Statistical Methods, Probability & Statistics, Unsupervised Learning, Statistical Inference, Probability Distribution, Machine Learning Algorithms
4.5
Rating, 4.5 out of 5 stars
60 reviews
Intermediate · Course · 1 - 3 Months
University of Amsterdam
Methods and Statistics in Social Sciences
Skills you'll gain: Qualitative Research, Statistical Hypothesis Testing, Scientific Methods, Descriptive Statistics, Statistical Inference, Statistical Analysis, Statistical Software, Probability Distribution, Research, Correlation Analysis, Research Design, Sampling (Statistics), Research Reports, Science and Research, Probability, Interviewing Skills, Data Analysis, Sample Size Determination, Statistical Methods, Social Sciences
4.6
Rating, 4.6 out of 5 stars
7.6K reviews
Beginner · Specialization · 3 - 6 Months
Johns Hopkins University
What are the Chances? Probability and Uncertainty in Statistics
Skills you'll gain: Statistics, Probability & Statistics, Regression Analysis, Probability, Statistical Hypothesis Testing, Probability Distribution, Statistical Methods, Statistical Analysis, Statistical Inference, Sampling (Statistics), Combinatorics
4.6
Rating, 4.6 out of 5 stars
17 reviews
Intermediate · Course · 1 - 4 Weeks
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
509 reviews
Mixed · Course · 1 - 4 Weeks
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
794 reviews
Intermediate · Course · 1 - 3 Months
University of California, Santa Cruz
Bayesian Statistics: Techniques and Models
Skills you'll gain: Bayesian Statistics, Statistical Modeling, Statistical Methods, Markov Model, Statistical Analysis, Regression Analysis, R Programming, Simulations, Statistical Inference, Probability, Probability Distribution, Algorithms
4.8
Rating, 4.8 out of 5 stars
487 reviews
Intermediate · Course · 1 - 3 Months