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

Rice University
Business Statistics and Analysis
Skills you'll gain: Statistical Hypothesis Testing, Microsoft Excel, Pivot Tables And Charts, Regression Analysis, Descriptive Statistics, Probability & Statistics, Graphing, Spreadsheet Software, Probability Distribution, Business Analytics, Statistical Analysis, Statistical Modeling, Excel Formulas, Data Analysis, Data Presentation, Statistics, Sample Size Determination, Box Plots, Analytical Skills, Statistical Inference
4.7
Rating, 4.7 out of 5 stars
12K reviews
Beginner · Specialization · 3 - 6 Months
Johns Hopkins University
Data Science: Statistics and Machine Learning
Skills you'll gain: Shiny (R Package), Rmarkdown, Regression Analysis, Leaflet (Software), Exploratory Data Analysis, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Plotly, Machine Learning Algorithms, Interactive Data Visualization, Probability & Statistics, Statistical Machine Learning, Feature Engineering, Statistical Analysis, Statistical Modeling, Probability, Correlation Analysis, Data Science, Data Analysis
4.4
Rating, 4.4 out of 5 stars
7.2K reviews
Intermediate · Specialization · 3 - 6 Months
University of Michigan
Applied Data Science with Python
Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Plot (Graphics), Data Visualization Software, Interactive Data Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Scikit Learn (Machine Learning Library), Network Model, Jupyter, NumPy, Graph Theory, Data Manipulation, Natural Language Processing, Data Analysis, Data Processing, Unstructured Data
4.5
Rating, 4.5 out of 5 stars
34K reviews
Intermediate · Specialization · 3 - 6 Months
DeepLearning.AI
Supervised Machine Learning: Regression and Classification
Skills you'll gain: Supervised Learning, Applied Machine Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Feature Engineering, Artificial Intelligence, Classification And Regression Tree (CART), Python Programming, Regression Analysis, Unsupervised Learning, Statistical Modeling, Data-Driven Decision-Making, Algorithms
4.9
Rating, 4.9 out of 5 stars
27K reviews
Beginner · Course · 1 - 4 Weeks
Coursera Project Network
Essential Causal Inference Techniques for Data Science
Skills you'll gain: Regression Analysis, Data Science, Data-Driven Decision-Making, R Programming, Statistical Inference, Applied Machine Learning, Machine Learning, Statistical Methods, Advanced Analytics, Data Analysis, Predictive Modeling
4.5
Rating, 4.5 out of 5 stars
35 reviews
Beginner · Guided Project · Less Than 2 Hours
SAS
Statistics with SAS
Skills you'll gain: SAS (Software), Statistical Hypothesis Testing, Statistical Software, Statistical Analysis, Predictive Modeling, Statistical Programming, Statistical Modeling, Statistical Methods, Regression Analysis, Probability & Statistics, Data Analysis
4.7
Rating, 4.7 out of 5 stars
296 reviews
Intermediate · Course · 1 - 3 Months
IBM
Applied Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Plotly, Data Wrangling, Data Visualization, Exploratory Data Analysis, Data Cleansing, Jupyter, Matplotlib, Data Analysis, Pandas (Python Package), Data Manipulation, Seaborn, Data Transformation, Data Import/Export, Predictive Modeling, Web Scraping, Interactive Data Visualization, Automation, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
57K reviews
Beginner · Specialization · 3 - 6 Months
Stanford University
Probabilistic Graphical Models 2: Inference
Skills you'll gain: Bayesian Network, Statistical Inference, Markov Model, Statistical Machine Learning, Graph Theory, Sampling (Statistics), Applied Machine Learning, Probability & Statistics, Algorithms, Probability Distribution, Machine Learning Algorithms
4.6
Rating, 4.6 out of 5 stars
487 reviews
Advanced · 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
Johns Hopkins University
Mathematical Biostatistics Boot Camp 2
Skills you'll gain: Statistical Hypothesis Testing, Statistical Analysis, Statistical Methods, Probability & Statistics, Statistical Inference, Biostatistics, Sampling (Statistics), Data Analysis
4.3
Rating, 4.3 out of 5 stars
133 reviews
Mixed · Course · 1 - 4 Weeks
Duke University
Introduction to Probability and Data with R
Skills you'll gain: Sampling (Statistics), Exploratory Data Analysis, Statistical Inference, Probability Distribution, Bayesian Statistics, R Programming, Data Analysis, Probability, Statistics, Statistical Analysis, Statistical Software, Data Science, Descriptive Statistics
4.7
Rating, 4.7 out of 5 stars
5.7K reviews
Beginner · Course · 1 - 3 Months
University of Colorado Boulder
Statistics and Applied Data Analysis
Skills you'll gain: Statistical Hypothesis Testing, Descriptive Statistics, Statistical Visualization, Data Transformation, Data Cleansing, Statistical Analysis, Regression Analysis, Statistical Programming, Probability, Probability Distribution, Sampling (Statistics), Box Plots, Histogram, R Programming, Statistical Methods, Scatter Plots, Microsoft Excel, Probability & Statistics, Statistics, Data Import/Export
4.7
Rating, 4.7 out of 5 stars
30 reviews
Beginner · Specialization · 3 - 6 Months