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

Packt
Mathematical Foundations and Quantum Mechanics Essentials
Skills you'll gain: Applied Mathematics, Mathematics and Mathematical Modeling, Linear Algebra, Probability, Mathematical Modeling, Computer Science, Algebra, Probability & Statistics, Statistics, Physics, Mechanics, Emerging Technologies
4.2
Rating, 4.2 out of 5 stars
22 reviews
Beginner · Course · 1 - 4 Weeks
Genentech
Data Sciences in Pharma - Patient Centered Outcomes Research
Skills you'll gain: Clinical Trials, Clinical Research, Pharmaceuticals, Patient Evaluation, Quantitative Research, Patient Safety, Medical Science and Research, Data Analysis, Statistical Analysis
4.4
Rating, 4.4 out of 5 stars
18 reviews
Intermediate · Course · 1 - 4 Weeks
Status: New
University of Illinois Urbana-Champaign
Artificial Intelligence in Finance and Wealth Management
Skills you'll gain: Wealth Management, Supervised Learning, Machine Learning, Financial Services, Applied Machine Learning, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Learning Management Systems, Artificial Intelligence, FinTech, Data Mining, Financial Planning, Investment Management, Regulatory Compliance, Law, Regulation, and Compliance, Relationship Building, Risk Modeling, ChatGPT, Mobile Development, Human Computer Interaction
Intermediate · Specialization · 1 - 3 Months
Coursera Project Network
Cervical Cancer Risk Prediction Using Machine Learning
Skills you'll gain: Exploratory Data Analysis, Data Analysis, Statistical Analysis, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Predictive Modeling, Matplotlib, Data Import/Export, Pandas (Python Package), Applied Machine Learning, Data Visualization Software, NumPy, Data Manipulation, Machine Learning
4.7
Rating, 4.7 out of 5 stars
37 reviews
Beginner · Guided Project · Less Than 2 Hours
University of California, Davis
Introduction to Sensory Science
Skills you'll gain: Food Quality Assurance And Control, Consumer Behaviour, Product Testing, Nutrition and Diet, Quality Assessment, Marketing Psychology, Scientific Methods, Psychology, Product Development, Medical Science and Research, Neurology, Statistical Analysis
4.6
Rating, 4.6 out of 5 stars
39 reviews
Beginner · Course · 1 - 4 Weeks
University of Michigan
AI-Powered Data Analysis: A Practical Introduction
Skills you'll gain: Analytical Skills, Data Analysis, Data Cleansing, Data Manipulation, Generative AI, ChatGPT, Data Visualization Software, Statistical Analysis, Artificial Intelligence, Data Collection, Data Management, GitHub, Technical Support, Git (Version Control System), Integrated Development Environments
4.3
Rating, 4.3 out of 5 stars
13 reviews
Beginner · Course · 1 - 4 Weeks
Status: New
University of Michigan
Data-Oriented Python Programming and Debugging
Skills you'll gain: Debugging, NumPy, Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Pandas (Python Package), Data Structures, Probability & Statistics, Statistical Methods, Probability, Statistics, Probability Distribution, Statistical Analysis, Data Analysis, Program Development, Large Language Modeling, Data Manipulation, Programming Principles, Computer Programming, Python Programming
Intermediate · Specialization · 3 - 6 Months
SAS
Performing Network, Path, and Text Analyses in SAS Visual Analytics
Skills you'll gain: SAS (Software), Network Analysis, Text Mining, Spatial Analysis, Data Visualization, Geospatial Mapping, Data Manipulation, Data Analysis, Business Analysis, Natural Language Processing
4.7
Rating, 4.7 out of 5 stars
193 reviews
Intermediate · Course · 1 - 4 Weeks
Coursera Project Network
Interactive Statistical Data Visualization 101
Skills you'll gain: Plotly, Plot (Graphics), Statistical Visualization, Box Plots, Scatter Plots, Interactive Data Visualization, Data Visualization Software, Histogram
4.9
Rating, 4.9 out of 5 stars
7 reviews
Beginner · Guided Project · Less Than 2 Hours
Whizlabs
Data Engineering in AWS
Skills you'll gain: Data Collection, AWS SageMaker, Feature Engineering, Amazon Web Services, Data Migration, Data Cleansing, Data Manipulation, Jupyter, Dimensionality Reduction, Exploratory Data Analysis, Unsupervised Learning, Machine Learning
3.9
Rating, 3.9 out of 5 stars
21 reviews
Beginner · Course · 1 - 4 Weeks
IBM
AI Workflow: Feature Engineering and Bias Detection
Skills you'll gain: Feature Engineering, Data Ethics, Unsupervised Learning, Dimensionality Reduction, Text Mining, Applied Machine Learning, Data Transformation, Anomaly Detection, Exploratory Data Analysis, Natural Language Processing, Quality Assurance, Data Validation, Machine Learning Algorithms, Data Visualization
4.4
Rating, 4.4 out of 5 stars
72 reviews
Advanced · Course · 1 - 4 Weeks
Fred Hutchinson Cancer Center
Researcher's Guide to Omic Data
Skills you'll gain: Bioinformatics, Molecular Biology, Data Processing, Data Analysis, Data Literacy, Research Design, Exploratory Data Analysis, Metadata Management, Experimentation, Science and Research, R Programming, Scientific Methods, Spatial Analysis, Data Collection, Data Quality, Data Validation, Quantitative Research, Biology, Qualitative Research, Analysis
3.8
Rating, 3.8 out of 5 stars
22 reviews
Intermediate · Specialization · 3 - 6 Months