Essential Statistics for Data Analysis

What you’ll learn in Essential Statistics for Data Analysis

• 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

Description of Essential Statistics for Data Analysis

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.

Throughout the course, you’ll play the role of a Recruitment Analyst for Maven Business School. Your goal is to use the statistical techniques you’ve learned to explore student data, predict the performance of future classes, and propose changes to help improve graduate outcomes.

You’ll also practice applying your skills to 5 real-world BONUS PROJECTS, and use statistics to explore data from restaurants, medical centers, pharmaceutical companys, safety teams, airlines, and more.

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

Requirements

• No math or stats background is required – we’ll start with the absolute basics!
• We’ll use Microsoft Excel (Office 365) for course projects and demos

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