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Statistics is both a formal science and a practical theory of scientific inquiry, and both aspects are considered in statistics education. Education in statistics has similar concerns as does education in other mathematical sciences, like logic, mathematics, and computer science. At the same time, statistics is concerned with evidence-based ...
A direct parallel between these conceptual levels and grade levels is not made because most students would begin at Level A when they are first exposed to statistics regardless of whether they are in primary, middle, or secondary school. [1] [3] A student's level of statistical maturity is based on experience rather than age. [2] [3]
Medical statistics (also health statistics) deals with applications of statistics to medicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research. [1] 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 ...
Statistical literacy is the ability to understand and reason with statistics and data. The abilities to understand and reason with data, or arguments that use data, are necessary for citizens to understand material presented in publications such as newspapers, television, and the Internet.
An example of an epidemiological question that can be answered using a cohort study is whether exposure to X (say, smoking) associates with outcome Y (say, lung cancer). For example, in 1951, the British Doctors Study was started. Using a cohort which included both smokers (the exposed group) and non-smokers (the unexposed group).
In broad usage, the "practical clinical significance" answers the question, how effective is the intervention or treatment, or how much change does the treatment cause. In terms of testing clinical treatments, practical significance optimally yields quantified information about the importance of a finding, using metrics such as effect size, number needed to treat (NNT), and preventive fraction ...
The validity of a measurement tool (for example, a test in education) is the degree to which the tool measures what it claims to measure. [3] Validity is based on the strength of a collection of different types of evidence (e.g. face validity, construct validity, etc.) described in greater detail below.
The investigators then obtain a standard set of clinical observations on each patient and a test or clinical follow-up to define the true state of the patient. They then use statistical methods to identify the best clinical predictors of the patient's true state. The probability of disease will depend on the patient's key clinical predictors.