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

Pontificia Universidad Católica de Chile
Decisiones Financieras
Skills you'll gain: Financial Statements, Financial Statement Analysis, Portfolio Management, Financial Accounting, Income Statement, Financial Analysis, Balance Sheet, Investments, Financial Market, Business Valuation, Risk Management, Cash Management, Working Capital, Accrual Accounting, Market Liquidity, Cash Flows, Asset Management, Capital Budgeting, Financial Modeling, Investment Management
4.8
Rating, 4.8 out of 5 stars
189 reviews
Intermediate · Specialization · 3 - 6 Months
Duke University
Managing Machine Learning Projects
Skills you'll gain: MLOps (Machine Learning Operations), Data Management, Data Quality, Technical Management, Applied Machine Learning, Data Processing, Software Development Life Cycle, Machine Learning, Data Cleansing, Technology Solutions, Data Collection, Data Science, Systems Architecture, System Design and Implementation, Continuous Monitoring, Software Versioning
4.8
Rating, 4.8 out of 5 stars
241 reviews
Beginner · Course · 1 - 3 Months
SAS
Doing More with SAS Programming
Skills you'll gain: SAS (Software), Data Manipulation, Data Transformation, SQL Server Integration Services (SSIS), Data Processing, Data Integration, Data Cleansing, Statistical Programming, Data Analysis, Debugging
4.8
Rating, 4.8 out of 5 stars
939 reviews
Intermediate · Course · 1 - 3 Months
University of Washington
Data Science at Scale
Skills you'll gain: Feature Engineering, Unsupervised Learning, Data Ethics, Statistical Visualization, Data Storytelling, Big Data, Relational Databases, Supervised Learning, Database Systems, Dataflow, Data Visualization Software, Data Science, Machine Learning Methods, Predictive Analytics, Analytics, Data Governance, Data Analysis, Exploratory Data Analysis, Predictive Modeling, Data Manipulation
4.2
Rating, 4.2 out of 5 stars
915 reviews
Intermediate · Specialization · 3 - 6 Months
SAS
Getting Started with SAS Visual Analytics
Skills you'll gain: SAS (Software), Data Quality, Data Analysis, Exploratory Data Analysis, Data Cleansing, Data Visualization Software, Virtual Environment, Data Manipulation, Statistical Reporting, Business Analysis, Statistical Programming
4.7
Rating, 4.7 out of 5 stars
879 reviews
Beginner · Course · 1 - 4 Weeks
IBM
Data Scientist Career Guide and Interview Preparation
Skills you'll gain: Professional Networking, Interviewing Skills, Professional Development, LinkedIn, Presentations, Data Science, Business Writing, Portfolio Management, Data Analysis, Problem Solving, Communication, Python Programming, Machine Learning
4.7
Rating, 4.7 out of 5 stars
230 reviews
Beginner · Course · 1 - 4 Weeks
University of Michigan
Data Analytics in the Public Sector with R
Skills you'll gain: Data Visualization, Exploratory Data Analysis, Plot (Graphics), Statistical Analysis, Ggplot2, Program Evaluation, Policy Analysis, Data Ethics, Data Analysis, Tidyverse (R Package), Statistical Visualization, R Programming, Statistical Methods, Public Policies, Data Visualization Software, Statistical Hypothesis Testing, Scatter Plots, Demography, Political Sciences, Public Administration
4.8
Rating, 4.8 out of 5 stars
73 reviews
Intermediate · Specialization · 3 - 6 Months
Pontificia Universidad Católica de Chile
Evaluación de Proyectos de Inversión
Skills you'll gain: Financial Analysis, Capital Budgeting, Project Finance, Return On Investment, Financial Modeling, Investment Management, Cash Flows, Risk Analysis, Corporate Strategy, Business Strategy
4.9
Rating, 4.9 out of 5 stars
456 reviews
Mixed · Course · 1 - 4 Weeks
University of Michigan
Questionnaire Design for Social Surveys
Skills you'll gain: Survey Creation, Interviewing Skills, Research Design, Data Collection, Qualitative Research, Research Methodologies, Quantitative Research, Statistical Analysis
4.5
Rating, 4.5 out of 5 stars
458 reviews
Intermediate · Course · 1 - 3 Months
IBM
Unsupervised Machine Learning
Skills you'll gain: Unsupervised Learning, Dimensionality Reduction, Scikit Learn (Machine Learning Library), Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Machine Learning, Statistical Machine Learning, Text Mining, Data Mining, Big Data, Data Analysis, Linear Algebra
4.7
Rating, 4.7 out of 5 stars
310 reviews
Intermediate · Course · 1 - 3 Months
Coursera Project Network
Introduction to Business Analysis Using Spreadsheets: Basics
Skills you'll gain: Google Sheets, Spreadsheet Software, Data Presentation, Data Analysis, Data Visualization Software, Productivity Software, Business Analysis, Data Manipulation, Descriptive Statistics, Statistics, Excel Formulas, Data Cleansing, Mathematical Software
4.3
Rating, 4.3 out of 5 stars
997 reviews
Beginner · Guided Project · Less Than 2 Hours
University of Minnesota
Introduction to Recommender Systems: Non-Personalized and Content-Based
Skills you'll gain: Taxonomy, Spreadsheet Software, Machine Learning, Predictive Analytics, Data Mining, Persona Development, Information Architecture, Statistics, Algorithms, Java
4.4
Rating, 4.4 out of 5 stars
647 reviews
Intermediate · Course · 1 - 3 Months