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2016 ; 61
(1
): 10-20
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Biostatistics Series Module 1: Basics of Biostatistics
#MMPMID26955089
Hazra A
; Gogtay N
Indian J Dermatol
2016[Jan]; 61
(1
): 10-20
PMID26955089
show ga
Although application of statistical methods to biomedical research began only
some 150 years ago, statistics is now an integral part of medical research. A
knowledge of statistics is also becoming mandatory to understand most medical
literature. Data constitute the raw material for statistical work. They are
records of measurement or observations or simply counts. A variable refers to a
particular character on which a set of data are recorded. Data are thus the
values of a variable. It is important to understand the different types of data
and their mutual interconversion. Biostatistics begins with descriptive
statistics that implies summarizing a collection of data from a sample or
population. Categorical data are described in terms of percentages or
proportions. With numerical data, individual observations within a sample or
population tend to cluster about a central location, with more extreme
observations being less frequent. The extent to which observations cluster is
summarized by measures of central tendency while the spread can be described by
measures of dispersion. The confidence interval (CI) is an increasingly important
measure of precision. When we observe samples, there is no way of assessing true
population parameters. We can, however, obtain a standard error and use it to
define a range in which the true population value is likely to lie with a certain
acceptable level of uncertainty. This range is the CI while its two terminal
values are the confidence limits. Conventionally, the 95% CI is used. Patterns in
data sets or data distributions are important, albeit not so obvious, component
of descriptive statistics. The most common distribution is the normal
distribution which is depicted as the well-known symmetrical bell-shaped Gaussian
curve. Familiarity with other distributions such as the binomial and Poisson
distributions is also helpful. Various graphs and plots have been devised to
summarize data and trends visually. Some plots, such as the box-and-whiskers plot
and the stem-and-leaf plot are used less often but provide useful summaries in
select situations.
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