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, 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
Johns Hopkins University
Summary Statistics in Public Health
Skills you'll gain: Biostatistics, Statistical Visualization, Epidemiology, Medical Science and Research, Quantitative Research, Descriptive Statistics, Statistical Methods, Data Literacy, Probability Distribution, Public Health, Statistical Analysis, Clinical Trials, Sample Size Determination
4.8
Rating, 4.8 out of 5 stars
2K reviews
Beginner · Course · 1 - 3 Months
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
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
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
218 reviews
Intermediate · Professional Certificate · 3 - 6 Months
Stanford University
Probabilistic Graphical Models 2: Inference
Skills you'll gain: Bayesian Network, Bayesian Statistics, Statistical Inference, Markov Model, Graph Theory, Sampling (Statistics), Applied Machine Learning, Statistical Methods, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms, Computational Thinking
4.6
Rating, 4.6 out of 5 stars
488 reviews
Advanced · Course · 1 - 3 Months
Google
Process Data from Dirty to Clean
Skills you'll gain: Data Cleansing, Sampling (Statistics), Data Integrity, Data Quality, Data Validation, Sample Size Determination, Data Analysis, Data Manipulation, SQL, Data Transformation, Spreadsheet Software
4.8
Rating, 4.8 out of 5 stars
18K reviews
Beginner · Course · 1 - 3 Months
University of Michigan
Introduction to Data Science in Python
Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Structures, 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
Rice University
Business Applications of Hypothesis Testing and Confidence Interval Estimation
Skills you'll gain: Statistical Hypothesis Testing, Statistical Methods, Sample Size Determination, Statistical Inference, Estimation, Statistics, Probability & Statistics, Sampling (Statistics), Statistical Analysis, Microsoft Excel, Excel Formulas, Decision Making
4.8
Rating, 4.8 out of 5 stars
1.3K reviews
Mixed · Course · 1 - 4 Weeks
Duke University
Bayesian Statistics
Skills you'll gain: Bayesian Statistics, Statistical Hypothesis Testing, Statistical Modeling, Statistical Methods, Statistical Inference, Statistical Analysis, Regression Analysis, Data Analysis, R Programming, Probability, Data-Driven Decision-Making, Probability Distribution
3.8
Rating, 3.8 out of 5 stars
797 reviews
Intermediate · Course · 1 - 3 Months
University of Pennsylvania
Fundamentals of Quantitative Modeling
Skills you'll gain: Mathematical Modeling, Statistical Modeling, Regression Analysis, Business Modeling, Financial Modeling, Business Mathematics, Markov Model, Probability, Predictive Analytics, Process Optimization, Risk Management, Statistics, Probability Distribution, Simulation and Simulation Software, Forecasting
4.6
Rating, 4.6 out of 5 stars
9.1K reviews
Mixed · Course · 1 - 4 Weeks
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, Web Scraping, Relational Databases, Stored Procedure, Databases, Computer Programming Tools, Automation, Data Analysis Software, Data Science, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
71K reviews
Beginner · Specialization · 3 - 6 Months