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
Google Cloud
Introduction to Trading, Machine Learning & GCP
Skills you'll gain: Machine Learning, Google Cloud Platform, Applied Machine Learning, Supervised Learning, Time Series Analysis and Forecasting, Financial Trading, Deep Learning, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Securities Trading, Technical Analysis, Financial Forecasting, Quantitative Research, Financial Modeling, Forecasting, Regression Analysis
4
Rating, 4 out of 5 stars
875 reviews
Intermediate · Course · 1 - 4 Weeks
Status: Free Trial
Google
Regression Analysis: Simplify Complex Data Relationships
Skills you'll gain: Regression Analysis, Statistical Hypothesis Testing, Statistical Analysis, Advanced Analytics, Correlation Analysis, Data Analysis, Predictive Modeling, Statistical Modeling, Supervised Learning, Variance Analysis, Machine Learning Methods, Python Programming
4.7
Rating, 4.7 out of 5 stars
527 reviews
Advanced · Course · 1 - 3 Months
Status: Free Trial
New York Institute of Finance
Introduction to Risk Management
Skills you'll gain: Risk Management, Business Risk Management, Risk Modeling, Operational Risk, Enterprise Risk Management (ERM), Credit Risk, Risk Analysis, Portfolio Management, Capital Markets, Financial Market, Financial Regulation, Financial Modeling, Probability Distribution
4.6
Rating, 4.6 out of 5 stars
706 reviews
Beginner · Course · 1 - 3 Months
SAS
Statistics with SAS
Skills you'll gain: SAS (Software), Statistical Hypothesis Testing, Statistical Software, Statistical Analysis, Predictive Modeling, Statistical Modeling, Statistical Methods, Regression Analysis, Probability & Statistics, Data Analysis
4.7
Rating, 4.7 out of 5 stars
297 reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Johns Hopkins University
Reproducible Research
Skills you'll gain: Rmarkdown, Knitr, Data Sharing, Statistical Reporting, Data Analysis, Statistical Analysis, Data Validation, R Programming, Verification And Validation, Technical Documentation
4.6
Rating, 4.6 out of 5 stars
4.2K reviews
Mixed · Course · 1 - 4 Weeks
Status: Free Trial
Queen Mary University of London
Market Research
Skills you'll gain: Qualitative Research, Proposal Development, Market Research, Research Reports, Data Collection, Research Design, Research Methodologies, Data Analysis, Statistical Hypothesis Testing, Survey Creation, Statistical Analysis, Surveys, Correlation Analysis, Quantitative Research, Research, Science and Research, Market Analysis, Focus Group, Regression Analysis, Content Performance Analysis
4.6
Rating, 4.6 out of 5 stars
469 reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
EDHEC Business School
Introduction to Portfolio Construction and Analysis with Python
Skills you'll gain: Investment Management, Portfolio Management, Asset Management, Risk Analysis, Financial Modeling, Risk Management, Financial Analysis, NumPy, Probability Distribution, Python Programming, Simulations, Pandas (Python Package), Matplotlib, Data Manipulation
4.8
Rating, 4.8 out of 5 stars
1.4K reviews
Mixed · Course · 1 - 4 Weeks
Status: Free Trial
Wesleyan University
Data Analysis and Interpretation
Skills you'll gain: Regression Analysis, Data Storytelling, Classification And Regression Tree (CART), Statistical Hypothesis Testing, Descriptive Statistics, Data Presentation, Statistical Analysis, Statistical Software, Correlation Analysis, Exploratory Data Analysis, Data Manipulation, Decision Tree Learning, Data Management, Data Analysis, Predictive Modeling, Data Visualization, Data Literacy, Random Forest Algorithm, SAS (Software), Statistical Modeling
4.4
Rating, 4.4 out of 5 stars
1.4K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
University of Colorado Boulder
Modern Regression Analysis in R
Skills you'll gain: Statistical Inference, Statistical Modeling, Regression Analysis, Data Ethics, Statistical Methods, Statistical Hypothesis Testing, Data Science, R Programming, Data Modeling, Statistical Analysis, Predictive Modeling, Probability & Statistics, Correlation Analysis, Forecasting, Linear Algebra
Build toward a degree
4.4
Rating, 4.4 out of 5 stars
30 reviews
Intermediate · Course · 1 - 3 Months
University of Michigan
Mindware: Critical Thinking for the Information Age
Skills you'll gain: Data Analysis, Statistics, Analytical Skills, Experimentation, Critical Thinking, Research Design, Behavioral Economics, Decision Making, Regression Analysis, Probability, Correlation Analysis
4.8
Rating, 4.8 out of 5 stars
1.4K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
University of Alberta
Sample-based Learning Methods
Skills you'll gain: Reinforcement Learning, Sampling (Statistics), Machine Learning Algorithms, Simulations, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Algorithms, Probability Distribution
4.8
Rating, 4.8 out of 5 stars
1.2K reviews
Intermediate · Course · 1 - 3 Months
University of London
Foundations of Data Science: K-Means Clustering in Python
Skills you'll gain: Data Visualization, Matplotlib, Probability & Statistics, Data Science, Unsupervised Learning, Statistics, NumPy, Python Programming, Pandas (Python Package), Data Analysis, Machine Learning Algorithms, Descriptive Statistics, Data Manipulation
4.6
Rating, 4.6 out of 5 stars
718 reviews
Beginner · Course · 1 - 3 Months