John C. Pezzullo

To estimate sample size in biostatistics, you must state the effect size of importance, or the effect size worth knowing about. If the true effect size is less than the “important” size, you don’t care if the test comes out nonsignificant. With a few shortcuts, you can pick an important effect size and find out how many participants you need, based on that effect size, for several common statistical tests.

Over the years, many dedicated and talented people have developed statistical software packages and made them freely available worldwide. Although some of these programs may not have the scope of coverage or the polish of the commercial packages, they're high-quality programs that can handle most, if not all, of what you probably need to do.

The range of a set of values in your data is the difference between the smallest value (the minimum value) and the largest value (the maximum value): Range = maximum value – minimum value So for the IQ example in the preceding section (84, 84, 89, 91, 110, 114, and 116), the minimum value is 84, the maximum value is 116, and the range is 32 (equal to 116 – 84).

The unpaired (independent-sample) t tests, one-way ANOVA, ANCOVA, and their nonparametric counterparts deal with comparisons between two or more groups of independent samples of data, such as different groups of subjects, where there's no logical connection between a specific subject in one group and a specific subject in another group.

As you dive deeper into the field of biostatistics, you'll need to develop a firm understanding of pharmacokinetics (PK) and pharmacodynamics (PD) and the differences between the two. The term pharmacokinetics (PK) refers to the study of How fast and how completely the drug is absorbed into the body (from the stomach and intestines if it's an oral drug) How the drug becomes distributed through the various body tissues and fluids, called body compartments (blood, muscle, fatty tissue, cerebrospinal fluid, and so on) To what extent (if any) the drug is metabolized (chemically modified) by enzymes produced in the liver and other organs How rapidly the drug is eliminated from the body (usually via urine, feces, and other routes) The term pharmacodynamics (PD) refers to the study of The relationship between the concentration of the drug in the body and the biological and physiological effects of the drug on the body or on other organisms (bacteria, parasites, and so forth) on or in the body.

Biostatistics, in its present form, is the cumulative result of four centuries of contributions from many mathematicians and scientists. Some are well known, and some are obscure; some are famous people you never would’ve suspected of being statisticians, and some are downright eccentric and unsavory characters.

One of the reasons (but not the only reason) for running a multiple regression analysis is to come up with a prediction formula for some outcome variable, based on a set of available predictor variables. Ideally, you’d like this formula to be parsimonious — to have as few variables as possible, but still make good predictions.

Two quite different ideas about probability have coexisted for more than a century. These probability approaches, which differ in several important ways, are as follows: The frequentist view defines probability of some event in terms of the relative frequency with which the event tends to occur. The Bayesian view defines probability in more subjective terms — as a measure of the strength of your belief regarding the true situation.

Modern statistical software makes it easy for you to analyze your data in most of the situations that you’re likely to encounter (summarize and graph your data, calculate confidence intervals, run common significance tests, do regression analysis, and so on). But occasionally you may run into a problem for which no preprogrammed solution exists.