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

American Psychological Association
How to Create and Explore a Data Set
Skills you'll gain: Histogram, Data Analysis, Exploratory Data Analysis, Analysis, Graphing, Data Visualization Software, Descriptive Statistics, Statistics, Probability & Statistics, Data Management, Research, Psychology
Beginner · Course · 1 - 3 Months
DeepLearning.AI
Python for Data Analytics
Skills you'll gain: Time Series Analysis and Forecasting, Descriptive Statistics, Statistical Inference, Pandas (Python Package), Data Visualization Software, Data Analysis, Data Manipulation, Jupyter, Exploratory Data Analysis, Probability & Statistics, Scatter Plots, Python Programming, Statistical Analysis, Programming Principles, Matplotlib, Seaborn, Forecasting, Regression Analysis
Beginner · Course · 1 - 3 Months
Johns Hopkins University
Introduction to Neural Networks
Skills you'll gain: Artificial Neural Networks, Machine Learning Algorithms, Deep Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Network Model, Network Architecture, Linear Algebra, Probability & Statistics
Intermediate · Course · 1 - 3 Months
Status: Free
Ball State University
Introduction to Data Science
Skills you'll gain: Data Ethics, Data Collection, Probability & Statistics, Sampling (Statistics), Data Science, R Programming, Data Structures, Data Analysis, Information Privacy, Data Manipulation, Data Processing, Ethical Standards And Conduct, Big Data
Build toward a degree
Beginner · Course · 3 - 6 Months
University of Minnesota
Social Determinants of Health: Methodological Opportunities
Skills you'll gain: Statistical Analysis, Social Sciences, Research Methodologies, Data Analysis, Policy Analysis, Research, Program Evaluation, Health Assessment, Community and Social Work, Health Care, Health Information Management and Medical Records, Data Visualization
Beginner · Course · 1 - 3 Months
Corporate Finance Institute
Regression Analysis - Fundamentals & Practical Applications
Skills you'll gain: Regression Analysis, Correlation Analysis, Statistical Modeling, Statistical Analysis, Predictive Modeling, Data Analysis, Scikit Learn (Machine Learning Library), Microsoft Excel, Supervised Learning, Pandas (Python Package)
Advanced · Course · 1 - 3 Months
Google Cloud
Google Cloud Product Fundamentals 日本語版
Skills you'll gain: Digital Transformation, Google Cloud Platform, Google Workspace, Business Transformation, Cloud Applications, Platform As A Service (PaaS), Database Application, Artificial Intelligence and Machine Learning (AI/ML), Cost Management, Cloud Computing, Cloud Infrastructure, Cloud Storage, Cloud Services, Machine Learning, Cloud Security, Cross-Functional Collaboration
4.8
Rating, 4.8 out of 5 stars
6 reviews
Beginner · Course · 1 - 3 Months
Packt
Regression Analysis for Statistics & Machine Learning in R
Skills you'll gain: Regression Analysis, Data Cleansing, R Programming, Data Manipulation, Statistical Analysis, Advanced Analytics, Statistical Machine Learning, Classification And Regression Tree (CART), Random Forest Algorithm, Data Transformation, Statistical Modeling, Exploratory Data Analysis, Applied Machine Learning, Feature Engineering, Predictive Modeling, Dimensionality Reduction
Intermediate · Course · 1 - 3 Months
Packt
Foundations of R Programming and Basic Data Manipulation
Skills you'll gain: Rmarkdown, Data Import/Export, R Programming, Data Manipulation, Data Visualization, Web Scraping, Ggplot2, Plotly, Programming Principles, Data Visualization Software, Data Wrangling, Data Cleansing, Statistical Programming, Data Transformation, Data Structures, Scripting Languages, Scripting, Development Environment, Leaflet (Software)
Beginner · Course · 1 - 3 Months
Status: Free
Johns Hopkins University
Exploring Algorithmic Bias as a Policy Issue: A Teach-Out
Skills you'll gain: Algorithms, Policy Analysis, Social Justice, Public Policies, Data Ethics, Diversity Equity and Inclusion Initiatives, Machine Learning, Mitigation, Advocacy
Mixed · Course · 1 - 3 Months
Coursera Project Network
R أساسيات لغة البرمجة
Skills you'll gain: Exploratory Data Analysis, R Programming, Data Manipulation, Statistical Programming, Data Analysis, File Management, Programming Principles, Development Environment, Data Structures
Beginner · Guided Project · Less Than 2 Hours
SAS
머신 러닝 자세히 알아보기: 기술적 팁, 요령, 그리고 함정
Skills you'll gain: Machine Learning, Technical Communication, Predictive Analytics, Supervised Learning, Machine Learning Software, Data Analysis, Feature Engineering, Decision Tree Learning, Artificial Intelligence and Machine Learning (AI/ML), Regression Analysis, Ethical Standards And Conduct, Performance Analysis, Artificial Neural Networks
Beginner · Course · 1 - 4 Weeks