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CADS Stats 101 is a Course

CADS Stats 101

Time limit: 60 days

Full course description

Master the fundamentals of statistical analysis. This seven-week course is designed for working professionals or anyone interested in learning how statistics can be applied to transform their business. Develop the skills for data-driven decision making.

Master key statistical concepts

Develop the skills to describe, summarize, and analyze data in ways that are meaningful and useful for decision-making. Each week, you'll explore an interactive module and complete a set of Lab Practice questions. Check your progress by completing quizzes each week as you go.

Get expert support

Even though this course is entirely self-paced, we've got your back. Learners will have the opportunity to ask questions virtually and receive feedback and help from the course facilitator.

Expand your opportunities

Data analytics continues to reshape all industries. Miami University's Center for Analytics and Data Science offers several opportunities to gain expertise in this exciting field. Earn the Analytics Institute Certificate by completing both Foundations of Statistics and Foundations of Data Science, or go deep into big data with Miami's Master of Science in Business Analytics.

Curriculum

Foundation of Statistics is a 7-week course focused on defining common statistics data science terms. Concepts covered 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