Sinopsis
A population is the universe about which an investigator wishes to draw conclusions; it need not consist of people, but may be a population of measurements. Strictly speaking, if an investigator wants to draw conclusions about the blood pressure of Americans, the population consists of the blood pressure measurements, not the Americans themselves.
A sample is a subset of the population—the part that is actually being observed or studied. Researchers can only rarely study whole populations, so inferential statistics are almost always needed to draw conclusions about a population when only a sample has actually been studied. A single observation—such as one person’s blood pressure—is an element, denoted by X. The number of elements in a population is denoted by N, and the number of elements in a sample by n. A population therefore consists of all the elements from X1 to XN, and a sample consists of n of these N elements.
Content
- Descriptive Statistics
- Inferential Statistics
- Hypothesis Testing
- Correlational and Predictive Techniques
- Asking Clinical Questions: Research Methods
- Answering Clinical Questions I: Searching for and Assessing the Evidence
- Answering Clinical Questions II: Statistics in Medical Decision Making
- Epidemiology and Population Health
- Ultra-High-Yield Review
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