Udemy – Essential Statistics for Data Analysis 2022-11

Udemy – Essential Statistics for Data Analysis 2022-11 Downloadly IRSpace

Apr 17, 2025 - 10:41 Updated: Apr 20, 2025 - 19:09

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Udemy – Essential Statistics for Data Analysis 2022-11

This is a hands-on, project-based course designed to help you learn and apply essential statistics concepts for data analysis & business intelligence. Our goal is to simplify and demystify the world of statistics using familiar tools like Microsoft Excel, and empower everyday people to understand and apply these tools and techniques – even if you have absolutely no background in math or stats! We’ll start by discussing the role of statistics in business intelligence, the difference between sample and population data, and the importance of using statistical techniques to make smart predictions and data-driven decisions.

Next we’ll explore our data using descriptive statistics and probability distributions, introduce the normal distribution and empirical rule, and learn how to apply the central limit theorem to make inferences about populations of any type. From there we’ll practice making estimates with confidence intervals, and using hypothesis tests to evaluate assumptions about unknown population parameters. We’ll introduce the basic hypothesis testing framework, then dive into concepts like null and alternative hypotheses, t-scores, p-values, type I vs. type II errors, and more. Last but not least, we’ll introduce the fundamentals of regression analysis, explore the difference between correlation and causation, and practice using basic linear regression models to make predictions using Excel’s Analysis Toolpak.

What you’ll learn

Learn powerful statistics tools and techniques for data analysis & business intelligence
Understand how to apply foundational statistics concepts like the central limit theorem and empirical rule
Explore data with descriptive statistics, including probability distributions and measures of variability & central tendency
Model data and make estimates using probability distributions and confidence intervals
Make data-driven decisions and draw conclusions with hypothesis testing
Use linear regression models to explore variable relationships and make predictions

Who this course is for

Aspiring data professionals who want an intuitive, beginner-friendly introduction to the world of statistics
Business intelligence professionals who want to make confident, data-driven decisions
Anyone using data to make assumptions, estimates or predictions on the job
Students looking to learn powerful, practical skills with unique, hands-on projects and demos