What This Document Is
These are lecture notes from the first week of Introduction to Biomedical Statistics (BST 322) at National University. The notes introduce the fundamental role of statistics in evidence-based medical and nursing practice, and lay the groundwork for understanding how statistics is applied throughout the entire research process – not just in data analysis. It also begins to define key concepts related to data itself.
Why This Document Matters
This document is essential for students beginning their study of biomedical statistics. It’s particularly valuable for those in healthcare fields (like nursing) who are transitioning towards research-informed practice. Understanding the core principles presented here will provide a foundation for interpreting research findings and contributing to the growing body of evidence that shapes medical decisions. It’s used at the very beginning of a statistics course to establish context and importance.
Common Limitations or Challenges
This document provides an *introduction* to these concepts. It does not offer detailed instruction on statistical methods, calculations, or data analysis techniques. It’s a high-level overview designed to motivate the study of statistics, not to replace it. Users will still need further coursework and practice to become proficient in applying statistical principles.
What This Document Provides
This document includes:
* An explanation of why statistics is crucial for modern healthcare.
* An overview of the steps involved in research and how statistics fits into each stage.
* Definitions of key terms like “data,” “qualitative data,” and “quantitative data.”
* An introduction to the concepts of variables, including independent and dependent variables, as well as discrete and continuous variables.
* A discussion of measurement in research.
This preview *does not* include detailed examples of statistical tests, formulas, or specific data analysis procedures. It also does not cover advanced topics like probability, distributions, or hypothesis testing.
