A series of basic statistics by Tom Lang

An Introduction to Basic Statistical Concepts
-Basic medical statistics by the world-renowned Tom Lang

My goal in this series of articles is to introduce readers to the concepts that underlie statistical reasoning, which is what clinicians need to know to understand the literature.
The first article, "Understanding Variables, Levels of Measurement, and Descriptive Statistics," talks about different types of variables, how much information is collected about a variable, and how this information is communicated to others.
The second and third articles, "Estimates and Confidence Intervals" and "Hypothesis Testing" are about one of the most important concepts in statistics: how research results are reported. Many results are the differences between a treatment and a control group. This difference is actually an estimate of what we would expect to happen if the treatment
were to be widely applied. However, estimates are meaningful only when accompanied by a measure of precision, which in medicine is usually the 95% confidence interval. These differences between groups are also often interpreted with P values, which are the result of hypothesis testing. An understanding of these related concepts is necessary to evaluate research outcomes.
The purpose of any medical treatment is to reduce the patient's risk of harm and to increase the probability of benefit. Various measures of these probabilities are described in the fourth article, "Understanding Measures of Risk."
Medical research also tries to determine relationships between variables. Articles five, "Tests and Measures of Association" and six "Correlation and Linear Regression Analysis," describe various ways in which relationships can be identified and measured.

Although these articles are short and present only basic information, they will help you understand the statistical analyses in the literature. They should also prepare you to learn more about statistics, which will be necessary if you are to understand and practice "evidence-based" medicine, which is founded on high-quality research and statistical analyses.