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

Status: Free Trial
Johns Hopkins University
Statistical Inference
Skills you'll gain: Statistical Inference, Statistical Hypothesis Testing, Probability & Statistics, Probability, Statistics, Bayesian Statistics, Statistical Methods, Statistical Modeling, Statistical Analysis, Probability Distribution, Sampling (Statistics), Sample Size Determination, Data Analysis
4.2
Rating, 4.2 out of 5 stars
4.4K reviews
Mixed · Course · 1 - 4 Weeks
Status: Free Trial
University of Colorado Boulder
Data Science Foundations: Statistical Inference
Skills you'll gain: Statistical Hypothesis Testing, Probability, Probability & Statistics, Statistical Inference, Statistical Methods, Probability Distribution, Statistics, Bayesian Statistics, Statistical Modeling, Sampling (Statistics), Statistical Analysis, Data Ethics, Data Science, Quantitative Research, Descriptive Statistics, Correlation Analysis
Build toward a degree
4.4
Rating, 4.4 out of 5 stars
323 reviews
Intermediate · Specialization · 3 - 6 Months
Stanford University
Introduction to Statistics
Skills you'll gain: Descriptive Statistics, Statistics, Statistical Methods, Sampling (Statistics), Statistical Analysis, Data Analysis, Statistical Modeling, Statistical Hypothesis Testing, Regression Analysis, Statistical Inference, Probability, Exploratory Data Analysis, Quantitative Research, Data Collection, Probability Distribution
4.6
Rating, 4.6 out of 5 stars
4.1K reviews
Beginner · Course · 1 - 3 Months
Status: Free Trial
University of Michigan
Statistics with Python
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Modeling, Statistical Methods, Statistical Inference, Statistics, Bayesian Statistics, Data Visualization, Data Literacy, Scientific Visualization, Matplotlib, Probability & Statistics, Seaborn, Data Science, Statistical Analysis, Jupyter, Statistical Programming, Regression Analysis, Data Visualization Software, Python Programming
4.6
Rating, 4.6 out of 5 stars
3.3K reviews
Beginner · Specialization · 1 - 3 Months
Status: Free Trial
University of California, Santa Cruz
Bayesian Statistics
Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Statistics, Probability, Statistical Machine Learning, Statistical Analysis, Statistical Methods, Markov Model, Data Analysis, Advanced Analytics, Mathematical Modeling, Microsoft Excel, Data Science, Probability Distribution, Probability & Statistics
4.6
Rating, 4.6 out of 5 stars
3.5K reviews
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
Duke University
Inferential Statistics
Skills you'll gain: Statistical Hypothesis Testing, Statistical Inference, Statistical Reporting, Statistical Methods, R Programming, Statistical Software, Statistical Analysis, Probability & Statistics, Data Literacy, Sampling (Statistics), Probability Distribution, Software Installation
4.8
Rating, 4.8 out of 5 stars
2.7K reviews
Beginner · Course · 1 - 3 Months

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Status: Free Trial
DeepLearning.AI
Mathematics for Machine Learning and Data Science
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Mathematical Modeling, Machine Learning, Machine Learning Methods, Jupyter
4.6
Rating, 4.6 out of 5 stars
2.8K reviews
Intermediate · Specialization · 1 - 3 Months
Status: Free Trial
IBM
Introduction to Data Analytics
Skills you'll gain: Big Data, Data Analysis, Statistical Analysis, Apache Hadoop, Apache Hive, Data Science, Data Warehousing, Data Visualization, Data Cleansing, Apache Spark, Data Lakes, Data Visualization Software, Relational Databases, Microsoft Excel
4.8
Rating, 4.8 out of 5 stars
19K reviews
Beginner · Course · 1 - 3 Months
Eindhoven University of Technology
Improving your statistical inferences
Skills you'll gain: Statistical Inference, Scientific Methods, Statistical Hypothesis Testing, Quantitative Research, Bayesian Statistics, Statistical Analysis, Statistical Methods, Probability & Statistics, Sample Size Determination, Research, Data Collection, R Programming, Data Sharing, Probability Distribution
4.9
Rating, 4.9 out of 5 stars
797 reviews
Intermediate · Course · 1 - 3 Months
Status: Free Trial
Duke University
Data Analysis with R
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Statistical Inference, Exploratory Data Analysis, Regression Analysis, Statistical Reporting, Probability Distribution, Statistical Methods, Data Analysis Software, R Programming, Bayesian Statistics, Statistical Analysis, Data Analysis, Statistical Software, Statistical Modeling, Probability & Statistics, Probability, Statistics, Correlation Analysis, Data Visualization
4.7
Rating, 4.7 out of 5 stars
7.5K reviews
Beginner · Specialization · 3 - 6 Months
Status: Free Trial
Johns Hopkins University
Advanced Statistics for Data Science
Skills you'll gain: Statistical Hypothesis Testing, Sampling (Statistics), Regression Analysis, Bayesian Statistics, Statistical Analysis, Probability & Statistics, Statistical Inference, Statistical Methods, Statistical Modeling, Linear Algebra, Probability, R Programming, Biostatistics, Data Science, Statistics, Probability Distribution, Mathematical Modeling, Data Analysis, Applied Mathematics, Predictive Modeling
4.4
Rating, 4.4 out of 5 stars
763 reviews
Advanced · Specialization · 3 - 6 Months
University of Zurich
An Intuitive Introduction to Probability
Skills you'll gain: Probability, Probability Distribution, Probability & Statistics, Descriptive Statistics, Statistical Methods, Applied Mathematics, Risk Analysis, Finance
4.8
Rating, 4.8 out of 5 stars
1.9K reviews
Beginner · Course · 1 - 3 Months