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.

COURSE OUTLINE:

• Why Statistics?

  • Discuss the role of statistics in the context of business intelligence and decision-making, and introduce the statistics workflow

  
  

• Understanding Data with Descriptive Statistics

  • Understand data using descriptive statistics, including frequency distributions and measures of central tendency & variability

  • PROJECT #1: Maven Pizza Parlor

  
  

• Modeling Data with Probability Distributions

  • Model data with probability distributions, and use the normal distribution to calculate probabilities and make value estimates

  • PROJECT #2: Maven Medical Center

  
  

• The Central Limit Theorem

  • Introduce the Central Limit Theorem, which leverages the normal distribution to make inferences on populations with any distribution

  
  

• Making Estimates with Confidence Intervals

  • Make estimates with confidence intervals, which use sample statistics to define a range where an unknown population parameter likely lies

  • PROJECT #3: Maven Pharma

  
  

• Drawing Conclusions with Hypothesis Tests

  • Draw conclusions with hypothesis tests, which let you evaluate assumptions about population parameters using sample statistics

  • PROJECT #4: Maven Safety Council

  
  

• Making Predictions with Regression Analysis

  • Make predictions with regression analysis, and estimate the values of a dependent variable via its relationship with independent variables

  • PROJECT #5: Maven Airlines

Join today and get immediate, lifetime access to the following:

• 7.5 hours of high-quality video

• Statistics for Data Analysis PDF ebook (150+ pages)

• Downloadable Excel project files & solutions

• Expert support and Q&A forum

• 30-day Udemy satisfaction guarantee

If you're an analyst, data scientist, business intelligence professional, or anyone looking to use statistics to make smart, data-driven decisions, this course is for you!

Happy learning!

-Enrique Ruiz (Lead Statistics & Excel Instructor, Maven Analytics)