Introduction to Statistical Concepts and Describing Data

Introduction to Statistical Concepts and Describing Data is designed to give you a strong foundation in statistics with a focus on real-world healthcare applications. Whether you're pursuing a career in nursing, public health, health informatics, or clinical research, this course will help you build the skills and confidence to understand and apply data in meaningful ways. You’ll begin by exploring essential statistical terms and concepts, including the difference between populations and samples, and the distinction between descriptive and inferential statistics. From there, you’ll learn how to classify variables, recognize common scales of measurement, and understand how data types influence the way results are analyzed and interpreted in healthcare. A major emphasis of the course is learning how to describe and summarize data—using measures such as mean, median, mode, range, and standard deviation—to identify trends and make informed judgments. You’ll also be introduced to the logic of hypothesis testing and walk through the steps used to evaluate claims and draw evidence-based conclusions from sample data. Throughout the course, you will engage in hands-on practice using R, a powerful statistical programming language widely used in healthcare and research. By analyzing real healthcare datasets, you’ll gain experience generating summaries, visualizing distributions, and interpreting results. 3b:T10b7,{"@

• Define key statistical concepts and explain the role of descriptive statistics in healthcare decision-making.
• Differentiate between types of variables and scales of measurement commonly used in healthcare research and practice.
• Interpret measures of central tendency and variability and apply basic hypothesis testing to healthcare-related data.
• Generate and summarize descriptive statistics using R to analyze healthcare datasets.