# Analytics Essentials: Statistics

Master the fundamentals of statistical analysis. This eight-week online course is designed for working professionals or anyone interested in learning how statistics can be applied to transform their business. Develop the introductory skills for data-driven decisions with Miami University’s Foundations of Statistics course.

## Quick Facts

Interested in offering this course to your organization?

8 weeks

Course duration

2-3 hrs/wk

Time commitment

Spring 2023

Next program start date

Cost varies

Get in touch for group pricing

## Learn from data experts

Even though the Analytics Essentials: Foundations of Data Science and Foundations of Statistics courses are entirely self-paced, we've got your back through a variety of supportive resources. As you progress, you have the opportunity to ask questions virtually and receive feedback and help from the course facilitator.

The growing need for data analytics continues to reshape all industries, making it a vital professional skill to obtain. Miami University's Center for Analytics and Data Science offers several opportunities to gain expertise in this exciting field.

By completing both the Foundations of Statistics course and the Foundations of Data Science course, students can then earn the Analytics Essentials Certificate. To grow expertise in big data and statistical analysis, also consider pursuing Miami’s Master of Science in Business Analytics (MSBA) program.

## Curriculum

Foundation of Statistics is an eight-week online course focused on defining common statistics and data science terms and how to perform basic statistical analysis. Students receive a comprehensive introduction to the practical application of statistics. Specifically, concepts covered in the class include:

Descriptive Statistics

Features/Variables

Hypothesis Testing

Confidence Intervals

Probability

Data Plotting

Data Summarization

Regression

Error and Power

Sampling Theory

Inference

Data Visualization

Upon completion, participants will be able to:

• Explain the steps of the statistical framework to answer a research question
• Distinguish quantitative and categorical variables in a dataset
• Identify when to use common data visualizations
• Identify different sampling schemes
• Understand how probability is calculated
• Summarize the results of a hypothesis test
• Interpret a confidence interval in context
• Explain the meaning of p-value in context