Biostatistics for the Clinician

• Welcome. You are among the first in the world to have the opportunity to participate in Web-based biostatistics instruction. Your participation will help to assess how different kinds of Web-based instruction compare with traditional lectures. You will participate in three lessons. Each lesson has multiple sections. A complete lesson corresponds to a complete class lecture by Dr. George Oser. The research depends on your responses to the pretest, posttest, and a brief attitudinal survey as well as to the instruction itself. All data is confidential and has no effect on your grade. Use any computer in the first floor medical school computer lab or the LRC. If you experience a problem with your computer consult the lab or LRC attendant.
• Texts. Use your texts and any other assigned materials just as you would if you were attending the lectures. But, do not attend the lectures. Instead, use this Web-based instruction.
• How to Use These Lessons.
  • Navigation. Use Netscape 3 in the typical Windows/Macintosh point and click fashion. Use the mouse to point and click the scroll bar and arrows at the right side of the window, or use the cursor control keys on the keyboard, to move forward and backward through the document.
  • Table of Contents. Click on Table of Contents entries to choose lessons or sections of lessons.
  • Section Instructions. Follow section instructions carefully to make sure you obtain credit for each section. Section instructions appear at the start and end of each section.
  • Practice Exercises. When Practice Exercises appear, click the appropriate button to choose your answer. Then press the "Get Feedback..." button to find out how you did. Feel free to change and correct your incorrect responses.
  • Hyperlinks. A hyperlink allows you to instantly access more information about a given topic simply by clicking the mouse button while pointing to the hyperlink with the mouse cursor. The phrase "Additional Instructions" here is a hyperlink.
  • More Information. Just click a hyperlink for more information about any hyperlinked topic. After visiting the hyperlink, press the "Back" button (leftmost on the toolbar) one or more times to return to your previous position. Press the "Forward" button (next to the "Backl" button) to revisit a previously backed-out-of hyperlink. Hyperlinks in Biostatistics for the Clinician provide instant access to a context-sensitive hypertext glossary. Use the hypertext glossary anytime you want more information or further detail about any hyperlinked concept.

These three lessons provide a brief yet comprehensive overview of the most frequently used and most important descriptive and inferential biostatistical methods as they are relevant for the clinician. The goal is that the you will appreciate how the application of the theories of measurement, statistical inference, and decision trees contributes to better clinical decisions and ultimately to improved patient care and outcomes.

Conceptual understanding, rather than computational ability, will be the focus. Development of an adequate vocabulary, an examination of fundamental principles and a survey of the widely used procedures or tools to extract information from data, will form a basis for fruitful collaboration with a professional biostatistician when appropriate.

The object, then, is to help you understand the tools and procedures that are used in statistics enough to be an intelligent consumer of the research literature and to know when to ask a biostatistician to help you when you actually need to compute some statistics. So the objective is not to make you into a biostatistician, but into an appreciator of the contributions biostatistics can make to the appropriate care of your patients, and into an intelligent decision maker as to when to seek the appropriate help from a professional biostatistician. The needs of practicing physicians, not the skills to be a biostatistician or for sophisticated medical research, will inform the instruction.

To prove that the treatment and only the treatment caused the effect.

Place limits on effects of chance in small sample experiments - (Alpha or False Positives).
Determine sample size needed to detect clinically relevant effects - (Beta or False Negatives).
Control for effects of one or more confounding variables.
Assist in developing alternative designs for human experiments.
Use maximum information content measurement.
Measure intangibles such as intelligence, depression, and well-being.

1: Summary Measures of Data (Descriptive Statistics)

2: Inferential Statistics

3: Clinical Decision Making in a Multi-variable Environment