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
Coursera Project Network
Диверсификация портфеля с помощью корреляционной матрицы
Skills you'll gain: Correlation Analysis, Portfolio Management, Investments, Financial Analysis, Asset Management, Financial Market, Risk Analysis
Intermediate · Guided Project · Less Than 2 Hours
Status: Free Trial
Johns Hopkins University
Mastering Neural Networks and Model Regularization
Skills you'll gain: PyTorch (Machine Learning Library), Deep Learning, Supervised Learning, Artificial Neural Networks, Image Analysis, Decision Tree Learning, Machine Learning Algorithms, Machine Learning, Computer Vision
Intermediate · Course · 1 - 3 Months
Coursera Project Network
Job Shop Scheduling Using MILP Optimization on RStudio
Skills you'll gain: R Programming, Analysis, Mathematical Software
Intermediate · Guided Project · Less Than 2 Hours
Johns Hopkins University
Der Werkzeugkasten des Data Scientist
Skills you'll gain: Rmarkdown, Data Science, Version Control, Big Data, R Programming, Software Development Tools, GitHub, Statistical Programming, Git (Version Control System), Data Analysis, Integrated Development Environments, Technical Communication, Software Installation
Mixed · Course · 1 - 4 Weeks
Google Cloud
Introduction to AI and Machine Learning on GC - Português
Skills you'll gain: Generative AI, Google Cloud Platform, Cloud Infrastructure, MLOps (Machine Learning Operations), Cloud Services, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Machine Learning, Predictive Modeling, Natural Language Processing
Beginner · Course · 1 - 3 Months
Status: Free Trial
Codio
Data Analysis in Python
Skills you'll gain: Matplotlib, Statistical Hypothesis Testing, Data Analysis, Data Import/Export, Data Visualization, Data Cleansing, Probability & Statistics, Data Manipulation, Statistics, Descriptive Statistics, Pandas (Python Package), Exploratory Data Analysis, Data Science, Python Programming, Computational Logic
Mixed · Course · 1 - 3 Months
Status: New
Status: Free Trial
University of Pennsylvania
Intro to Predictive Analytics Using Python
Skills you'll gain: Feature Engineering, Unsupervised Learning, Predictive Modeling, Predictive Analytics, Decision Tree Learning, Classification And Regression Tree (CART), Supervised Learning, Forecasting, Random Forest Algorithm, Scikit Learn (Machine Learning Library), Data Analysis, Regression Analysis, Machine Learning, Python Programming
Beginner · Course · 1 - 4 Weeks
University of Illinois Urbana-Champaign
Untersuchen und Erstellen von Daten für Unternehmen
Skills you'll gain: Descriptive Statistics, Statistical Inference, Sampling (Statistics), Histogram, Data Analysis, Probability & Statistics, Data Presentation, Statistical Analysis, Quantitative Research, Microsoft Excel, Statistical Methods, Probability Distribution, Graphing
Beginner · Course · 1 - 3 Months
Coursera Project Network
MLOps in R: Deploying machine learning models using vetiver
Skills you'll gain: MLOps (Machine Learning Operations), Continuous Deployment, Application Deployment, Tidyverse (R Package), R Programming, Dashboard, Health Informatics, Applied Machine Learning, Continuous Monitoring, Predictive Modeling, Machine Learning Methods, Statistical Machine Learning, Docker (Software), Application Programming Interface (API)
Intermediate · Guided Project · Less Than 2 Hours
Status: New
Status: Free Trial
University of Glasgow
Machine Learning and its Applications
Skills you'll gain: Artificial Neural Networks, Matlab, Supervised Learning, Applied Machine Learning, Machine Learning, Data Cleansing, Feature Engineering, Data Transformation, Classification And Regression Tree (CART), Predictive Modeling, Regression Analysis
Beginner · Course · 1 - 3 Months
Status: Free Trial
Edureka
Machine Learning with PySpark
Skills you'll gain: PySpark, Apache Spark, Unsupervised Learning, Data Processing, Distributed Computing, Big Data, Feature Engineering, Machine Learning, Machine Learning Algorithms, Supervised Learning, Scalability, Regression Analysis
Intermediate · Course · 1 - 4 Weeks
Status: Free
O.P. Jindal Global University
Econometrics - Theory and Practice
Skills you'll gain: Econometrics, Regression Analysis, Statistical Hypothesis Testing, Statistical Modeling, Quantitative Research, Statistical Methods, Stata, Time Series Analysis and Forecasting, Correlation Analysis, Statistical Inference, Statistical Analysis, Probability & Statistics, Data Manipulation, Probability Distribution
Beginner · Course · 1 - 3 Months