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

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, Data Science, Exploratory Data Analysis, Data Analysis, Statistical Visualization
4.6
Rating, 4.6 out of 5 stars
533 reviews
Intermediate · Course · 1 - 4 Weeks
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
IBM
Data Analysis and Visualization Foundations
Skills you'll gain: Data Storytelling, Data Presentation, Data Visualization, Interactive Data Visualization, Big Data, Data Visualization Software, Data Analysis, IBM Cognos Analytics, Statistical Analysis, Data Mining, Dashboard, Apache Hadoop, Data Collection, Tree Maps, Excel Formulas, Apache Hive, Microsoft Excel, Data Quality, Data Cleansing, Data Import/Export
Build toward a degree
4.7
Rating, 4.7 out of 5 stars
26K reviews
Beginner · Specialization · 3 - 6 Months
Johns Hopkins University
Data – What It Is, What We Can Do With It
Skills you'll gain: Data Visualization, Data Analysis, Research Design, Data Presentation, Descriptive Statistics, Analytics, Statistical Analysis, Quantitative Research, Statistical Methods, Probability & Statistics
4.6
Rating, 4.6 out of 5 stars
172 reviews
Beginner · Course · 1 - 4 Weeks
Johns Hopkins University
Statistical Methods for Computer Science
Skills you'll gain: Network Analysis, R Programming, Statistical Analysis, Regression Analysis, Statistical Modeling, Combinatorics, Bayesian Network, Statistical Hypothesis Testing, Data Analysis, Probability, Statistics, Applied Machine Learning, Probability & Statistics, Statistical Methods, Probability Distribution, Simulations, Data Science, Markov Model, Applied Mathematics, Mathematical Modeling
Intermediate · Specialization · 3 - 6 Months
IBM
IBM Data Analytics with Excel and R
Skills you'll gain: Data Storytelling, Data Presentation, Interactive Data Visualization, Data Visualization Software, Data Visualization, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Statistical Visualization, Relational Databases, Big Data, Ggplot2, Database Design, Data Analysis, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel
Build toward a degree
4.7
Rating, 4.7 out of 5 stars
27K reviews
Beginner · Professional Certificate · 3 - 6 Months
University of Michigan
Introduction to Data Science in Python
Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles
4.5
Rating, 4.5 out of 5 stars
27K reviews
Intermediate · Course · 1 - 4 Weeks
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
SkillUp EdTech
Advanced Statistical Analysis and Tools
Skills you'll gain: Statistical Process Controls, Statistical Hypothesis Testing, Process Improvement, Lean Methodologies, Kaizen Methodology, Lean Six Sigma, Process Capability, Six Sigma Methodology, Risk Analysis, Quality Improvement, Process Analysis, Statistical Analysis, Statistical Methods, Continuous Improvement Process, Quality Assessment, Risk Management, Business Process, Sampling (Statistics), Statistical Inference, Data Collection
Intermediate · Course · 1 - 4 Weeks
IBM
Introduction to Data Science
Skills you'll gain: SQL, Jupyter, Data Mining, Data Modeling, Databases, Data Science, Stored Procedure, Relational Databases, R Programming, Database Design, Query Languages, Database Management, Big Data, Computer Programming Tools, GitHub, Data Visualization Software, Application Deployment, Data-Driven Decision-Making, Cloud Computing, Data Analysis
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
97K reviews
Beginner · Specialization · 3 - 6 Months
IBM
Data Science Fundamentals with Python and SQL
Skills you'll gain: Dashboard, SQL, Descriptive Statistics, Jupyter, Statistical Analysis, Data Analysis, Probability Distribution, Pandas (Python Package), Data Visualization Software, Statistics, Data Visualization, Databases, Stored Procedure, Web Scraping, Relational Databases, R Programming, Automation, Computer Programming Tools, GitHub, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
70K reviews
Beginner · Specialization · 3 - 6 Months
Illinois Tech
Statistical Learning
Skills you'll gain: Statistical Analysis, Data Analysis, Statistical Programming, Statistical Methods, Regression Analysis, Bayesian Statistics, Supervised Learning, Statistical Inference, Machine Learning, Unsupervised Learning, Predictive Modeling, Classification And Regression Tree (CART), Feature Engineering, Dimensionality Reduction
Build toward a degree
Intermediate · Course · 1 - 3 Months