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Test Taking Tips

  1. Memorize the table below for easy calculation of sensitivity, specificity, and positive and negative predictive values.

  2. Know the differences between different types of statistical tests.


What is sensitivity?

  • Proportion of truly diseased persons in a screened population who are identified as being diseased by the test. It is a measure of the probability of correctly diagnosing a condition.

Sensitivity equation:

  • True positive/(true positive + false negative)

What is specificity?

  • The proportion of truly nondiseased persons who are so identified by the screening test

Specificity equation:

  • True negative/(false positive + true negative)

False-positive rate:

  • 1 – specificity

False-negative rate

  • 1 – sensitivity

What is positive predictive value?

  • The probability that a person with a positive test result has the disease

What is the positive predictive equation?

  • True positive/(true positive + false positive)

What is the negative predicted value?

  • The probability that a patient with a negative test result really is free of the disease

What is the negative predicted value equation?

  • True negative/(false negative + true negative)

Definition of prevalence:

  • The total number of cases of a given disease in a specified population at a designated time

Definition of incidence:

  • The number of new cases of a given disease during a given period in a specified population

What is the absolute risk reduction?

  • The absolute arithmetic difference in outcome rates between control and experimental patients in a trial

What is relative risk reduction?

  • The proportional reduction in outcome rates between control and experimental patients in a trial

A range of values that has a specified probability of containing the rate or trend:

  • Confidence intervals

A method of studying a drug or procedure in which both the subjects and investigators are kept unaware of who is actually getting which specific treatment:

  • Double-blind method

The number of patients who need to be treated to prevent one adverse outcome:

  • Number Needed To Treat

The probability that an event will occur:

  • Risk

The number of units in a population to be studied:

  • Sample size

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