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- Statistical Inference

- Modern Regression Analysis in R: University of Colorado Boulder
- Data – What It Is, What We Can Do With It: Johns Hopkins University
- Regression Models: Johns Hopkins University
- Statistical Thinking for Industrial Problem Solving, presented by JMP: SAS
- Probabilistic Graphical Models 2: Inference: Stanford University
- Essential Causal Inference Techniques for Data Science: Coursera Project Network
- Introduction to PyMC3 for Bayesian Modeling and Inference: Databricks
- Bayesian Inference with MCMC: Databricks
- Quantifying Relationships with Regression Models: Johns Hopkins University
- Advanced Learning Algorithms: DeepLearning.AI

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.

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.

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.

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.

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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