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

Duke University
Java Programming and Software Engineering Fundamentals
Skills you'll gain: Object Oriented Programming (OOP), Java, Hypertext Markup Language (HTML), Software Design, Software Design Patterns, Data Structures, HTML and CSS, Debugging, Software Engineering, Cascading Style Sheets (CSS), Web Development, Computer Programming, Programming Principles, Javascript, Encryption, Algorithms, AI Personalization, Web Design, Data Processing, Statistical Analysis
4.6
Rating, 4.6 out of 5 stars
22K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free
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
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
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
University of Michigan
Fitting Statistical Models to Data with Python
Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Analysis, Statistical Programming, Regression Analysis, Predictive Modeling, Jupyter, Exploratory Data Analysis, Statistical Hypothesis Testing, Correlation Analysis, Probability Distribution
4.4
Rating, 4.4 out of 5 stars
701 reviews
Intermediate · Course · 1 - 4 Weeks
SAS
SAS Statistical Business Analyst
Skills you'll gain: SAS (Software), Predictive Modeling, Predictive Analytics, Statistical Hypothesis Testing, Statistical Analysis, Correlation Analysis, Statistical Modeling, Regression Analysis, Exploratory Data Analysis, Statistical Methods, Probability & Statistics, Big Data, Plot (Graphics), Data Analysis, Data Literacy, Data Analysis Software, Advanced Analytics, Statistical Machine Learning, Feature Engineering, Performance Analysis
4.6
Rating, 4.6 out of 5 stars
219 reviews
Intermediate · Professional Certificate · 3 - 6 Months
IBM
Data Analysis and Visualization Foundations
Skills you'll gain: Data Storytelling, Big Data, Data Visualization Software, Data Analysis, Dashboard, IBM Cognos Analytics, Statistical Analysis, Data Mining, Apache Hadoop, Tree Maps, Excel Formulas, Apache Hive, Microsoft Excel, Data Warehousing, Data Quality, Data Cleansing, Scatter Plots, Apache Spark, Pivot Tables And Charts, Data Import/Export
Build toward a degree
4.7
Rating, 4.7 out of 5 stars
27K reviews
Beginner · Specialization · 3 - 6 Months
IBM
Applied Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Interactive Data Visualization, Exploratory Data Analysis, Data Cleansing, Jupyter, Matplotlib, Data Analysis, Pandas (Python Package), Data Manipulation, Seaborn, Data Import/Export, Predictive Modeling, Web Scraping, Automation, Data Science, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
58K reviews
Beginner · Specialization · 3 - 6 Months
DeepLearning.AI
Probability & Statistics for Machine Learning & Data Science
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization
4.6
Rating, 4.6 out of 5 stars
558 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, Statistical Analysis, Biostatistics
4.4
Rating, 4.4 out of 5 stars
514 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, Data Analysis, Peer Review, Exploratory Data Analysis, Data Manipulation, Data Pipelines, Databricks, Database Design, Query Languages
4.6
Rating, 4.6 out of 5 stars
18K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free
University of London
Probability and Statistics: To p or not to p?
Skills you'll gain: Descriptive Statistics, Statistics, Probability & Statistics, Statistical Hypothesis Testing, Data Visualization, Data-Driven Decision-Making, Statistical Modeling, Data Analysis, Probability, Probability Distribution, Sampling (Statistics), Risk Modeling, Statistical Inference, Mathematical Modeling
4.6
Rating, 4.6 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 3 Months