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

IBM
Statistics for Data Science with Python
Skills you'll gain: Descriptive Statistics, Statistical Analysis, Data Analysis, Probability Distribution, Statistics, Data Visualization, Statistical Hypothesis Testing, Regression Analysis, Data Science, Matplotlib, Exploratory Data Analysis, Statistical Inference, Probability, Correlation Analysis, Pandas (Python Package), Jupyter
4.5
Rating, 4.5 out of 5 stars
432 reviews
Mixed · Course · 1 - 3 Months
University of Michigan
Introduction to Data Science in Python
Skills you'll gain: Pandas (Python Package), Jupyter, NumPy, Data Manipulation, Data Science, Data Analysis, Statistical Analysis, Pivot Tables And Charts, Data Cleansing, Data Import/Export, Probability & Statistics, Python Programming, Programming Principles
4.5
Rating, 4.5 out of 5 stars
27K reviews
Intermediate · Course · 1 - 4 Weeks
Imperial College London
Introduction to Statistics & Data Analysis in Public Health
Skills you'll gain: Analytical Skills, Sampling (Statistics), Statistical Hypothesis Testing, Statistical Analysis, Biostatistics, Data Analysis, Statistical Software, Exploratory Data Analysis, Quantitative Research, Probability & Statistics, Statistical Methods, R Programming, Statistics, Statistical Inference, Descriptive Statistics, Probability Distribution, Data Import/Export
4.7
Rating, 4.7 out of 5 stars
1.5K reviews
Beginner · Course · 1 - 4 Weeks
University of California, Davis
Learn SQL Basics for Data Science
Skills you'll gain: Data Governance, Presentations, Data Cleansing, Feature Engineering, SQL, Apache Spark, A/B Testing, Distributed Computing, Descriptive Statistics, Data Lakes, Data Quality, Data Storytelling, Peer Review, Exploratory Data Analysis, Data Manipulation, Data Pipelines, JSON, Statistical Analysis, Database Design, Query Languages
4.6
Rating, 4.6 out of 5 stars
18K reviews
Beginner · Specialization · 3 - 6 Months
Status: AI skills
Meta
Meta Marketing Analytics
Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Marketing Analytics, Bayesian Statistics, Descriptive Statistics, Marketing Effectiveness, Statistical Hypothesis Testing, A/B Testing, Target Audience, Marketing Strategies, Data Cleansing, Pandas (Python Package), Data Modeling, Data Analysis, Data Visualization Software, Spreadsheet Software, Data Collection, Marketing, Interviewing Skills
4.7
Rating, 4.7 out of 5 stars
3.7K reviews
Beginner · Professional Certificate · 3 - 6 Months
Status: New
Multiple educators
Data Science Foundations
Skills you'll gain: Dashboard, Pseudocode, Jupyter, Algorithms, Data Mining, Pandas (Python Package), Correlation Analysis, Web Scraping, NumPy, Probability & Statistics, Predictive Modeling, Big Data, Automation, Data Visualization Software, Data Collection, Software Development Tools, Data Science, GitHub, Machine Learning Algorithms, Unsupervised Learning
4.6
Rating, 4.6 out of 5 stars
112K reviews
Beginner · Specialization · 3 - 6 Months
DeepLearning.AI
Neural Networks and Deep Learning
Skills you'll gain: Deep Learning, Artificial Neural Networks, Tensorflow, Supervised Learning, Keras (Neural Network Library), Artificial Intelligence, Machine Learning, Python Programming, NumPy, Performance Tuning
4.9
Rating, 4.9 out of 5 stars
123K reviews
Intermediate · Course · 1 - 4 Weeks
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 Import/Export, Predictive Modeling, Web Scraping, Interactive Data Visualization, Statistical Analysis, Automation, Python Programming
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
58K reviews
Beginner · 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
Probability & Statistics for Machine Learning & Data Science
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Data Science, Exploratory Data Analysis, Data Analysis, Statistical Visualization
4.6
Rating, 4.6 out of 5 stars
547 reviews
Intermediate · Course · 1 - 4 Weeks
University of Michigan
Fitting Statistical Models to Data with Python
Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Software, Statistical Analysis, Statistical Programming, Regression Analysis, Predictive Modeling, Data Analysis, Exploratory Data Analysis, Statistical Hypothesis Testing, Correlation Analysis, Data Manipulation
4.4
Rating, 4.4 out of 5 stars
699 reviews
Intermediate · Course · 1 - 4 Weeks
IBM
IBM Data Analytics with Excel and R
Skills you'll gain: Data Storytelling, Data Presentation, Interactive Data Visualization, Data Visualization Software, Data Visualization, Shiny (R Package), Data Wrangling, Exploratory Data Analysis, Relational Databases, Big Data, Ggplot2, Database Design, Data Analysis, IBM Cognos Analytics, Data Mining, Dashboard, Excel Formulas, Data Manipulation, Web Scraping, Microsoft Excel
Build toward a degree
4.7
Rating, 4.7 out of 5 stars
28K reviews
Beginner · Professional Certificate · 3 - 6 Months