Residuals

Residuals (pronunciation: /rɪˈzɪdʒuəlz/) are a statistical concept used in many fields, including medicine. They represent the difference between the observed value of a variable and the value predicted by a statistical model.

Etymology

The term "residual" comes from the Latin word "residuum", which means "what is left over". In statistics, it refers to the "left over" variation in the data after a model has been fitted.

Related Terms

• Regression analysis: A statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables.
• Least squares: The standard method for estimating the unknown parameters in a linear regression model. It minimizes the sum of the squared residuals.
• Outliers: An observation that lies an abnormal distance from other values in a random sample from a population. In a sense, this definition leaves it up to the analyst (or a consensus process) to decide what will be considered abnormal.
• Standard deviation: A measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean of the set, while a high standard deviation indicates that the values are spread out over a wider range.

In Medicine

In the field of medicine, residuals can be used in various ways. For example, in a study investigating the effect of a drug on blood pressure, the residuals would represent the difference between the actual blood pressure measurements and the blood pressure predicted by the model (which might include variables such as dosage, age, and weight). These residuals can then be analyzed to see if there are any patterns or trends that were not captured by the model.

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