Biostatistics is a branch of statistics that applies statistical methods to a wide range of topics in biology. It encompasses the design of biological experiments, the collection and analysis of data from those experiments and the interpretation of the results.
In statistics, the Kolmogorov–Smirnov test is a nonparametric test of the equality of continuous, one-dimensional probability distributions that can be used to test whether a sample came from a given reference probability distribution, or to test whether two samples came from the same distribution. Intuitively, the test provides a method to qualitatively answer the question "How likely is it that we would see a collection of samples like this if they were drawn from that probability distribution?" or, in the second case, "How likely is it that we would see two sets of samples like this if they were drawn from the same probability distribution?". It is named after Andrey Kolmogorov and Nikolai Smirnov.
Kuiper's test is used in statistics to test that whether a data sample come from a given distribution, or whether two data samples came from the same unknown distribution. It is named after Dutch mathematician Nicolaas Kuiper.
In statistical hypothesis testing, a result has statistical significance when a result at least as "extreme" would be very infrequent if the null hypothesis were true. More precisely, a study's defined significance level, denoted by , is the probability of the study rejecting the null hypothesis, given that the null hypothesis is true; and the p-value of a result, , is the probability of obtaining a result at least as extreme, given that the null hypothesis is true. The result is statistically significant, by the standards of the study, when . The significance level for a study is chosen before data collection, and is typically set to 5% or much lower—depending on the field of study.
The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question. Such measures can be used in statistical hypothesis testing, e.g. to test for normality of residuals, to test whether two samples are drawn from identical distributions, or whether outcome frequencies follow a specified distribution. In the analysis of variance, one of the components into which the variance is partitioned may be a lack-of-fit sum of squares.
In statistics, the Lilliefors test is a normality test based on the Kolmogorov–Smirnov test. It is used to test the null hypothesis that data come from a normally distributed population, when the null hypothesis does not specify which normal distribution; i.e., it does not specify the expected value and variance of the distribution. It is named after Hubert Lilliefors, professor of statistics at George Washington University.
The Shapiro–Wilk test is a test of normality. It was published in 1965 by Samuel Sanford Shapiro and Martin Wilk.
Medical statistics deals with applications of statistics to medicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research. Medical statistics has been a recognized branch of statistics in the United Kingdom for more than 40 years, but the term has not come into general use in North America, where the wider term 'biostatistics' is more commonly used. However, "biostatistics" more commonly connotes all applications of statistics to biology. Medical statistics is a subdiscipline of statistics.
It is the science of summarizing, collecting, presenting and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses. It has a central role in medical investigations. It not only provides a way of organizing information on a wider and more formal basis than relying on the exchange of anecdotes and personal experience, but also takes into account the intrinsic variation inherent in most biological processes.
Minimum-distance estimation (MDE) is a conceptual method for fitting a statistical model to data, usually the empirical distribution. Often-used estimators such as ordinary least squares can be thought of as special cases of minimum-distance estimation.
Maria Deloria Knoll is an expert in the fields of epidemiology, disease surveillance, vaccine trial conduct, and biostatistics. She currently serves as associate director of Science at the International Vaccine Access Center (IVAC), an organization dedicated to accelerating global access to life-saving vaccines, at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland.
Pranab Kumar Sen was an Indian-American statistician who was a professor of statistics and the Cary C. Boshamer Professor of Biostatistics at the University of North Carolina at Chapel Hill.
Kathryn Mary Chaloner was a British-born American statistician.
Elizabeth Ray DeLong is an American biostatistician. She is a professor of biostatistics and bioinformatics at Duke University, where she chairs the Department of Biostatistics and Bioinformatics and is affiliated with the Duke Clinical Research Institute and Duke Cancer Institute.
Susan S. Ellenberg is an American statistician specializing in the design of clinical trials and in the safety of medical products. She is a professor of biostatistics, medical ethics and health policy in the Perelman School of Medicine at the University of Pennsylvania. She was the 1993 president of the Society for Clinical Trials and the 1999 President of the Eastern North American Region of the International Biometric Society.
Keith A. Crandall is an American computational biologist, bioinformaticist, and population geneticist at George Washington University, where he is the founding director of the Computational Biology Institute, and professor in the Department of Biostatistics and Bioinformatics.
Lori Elizabeth Dodd is an American mathematical statistician specializing in clinical trials methodology, statistical analysis of genomic data, design of clinical trials using biomarkers and imaging modalities, and statistical methods for analyzing biomarkers. She is a statistician in the biostatistics research branch at the National Institute of Allergy and Infectious Diseases.
Clarice Ring Weinberg is an American biostatistician and epidemiologist who works for the National Institute of Environmental Health Sciences as principal investigator in the Biostatistics and Computational Biology Branch. Her research concerns environmental epidemiology, and its combination with genetics in susceptibility to disease, including running the Sister Study on how environmental and genetic effects can lead to breast cancer. She has also published highly cited research on fertility.
Misrak Gezmu is an Ethiopian-American statistician who works as a mathematical statistician and grant officer for the Biostatistics Research Branch of the National Institute of Allergy and Infectious Diseases. She is known for her pioneering doctoral research on the statistics of up-and-down designs.
Lu Wang is a Chinese-American biostatistician whose research topics have included causal inference, dynamic decision-making for medical treatments, missing data, and environmental health. She has also studied the correlation between mercury from seafood and autoimmune disease, and the benefits of providing improved transportation services for healthcare, as a member of the Michigan Institute for Healthcare Policy & Innovation. She is a professor of biostatistics and associate chair for research in biostatistics in the University of Michigan School of Public Health.
Tanya Pamela Garcia is a Peruvian-American biostatistician whose research applies robust statistics to understand the progression of neurodegenerative diseases including Huntington's disease, and to classify gut microbiota. She is an associate professor of biostatistics in the UNC Gillings School of Global Public Health in Chapel Hill, North Carolina. She is the 2025 chair of the Biometrics Section of the American Statistical Association.
