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.
True positive/(true positive + false negative)
The proportion of truly nondiseased persons who are so identified by the screening test
True negative/(false positive + true negative)
1 – specificity
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:
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:
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:
The number of units in a population to be studied:
The proportion of patients alive at some point after the diagnosis:
What is the null hypothesis?
Denoted by Ho; it is a proposal that there is no difference in a comparison.
What is a Type I error?
Rejecting the null hypothesis tested when it is true (α)
What is a Type II error?
Failing to reject the null hypothesis when a given alternative hypothesis was true (β)
The probability that the test will reject the hypothesis tested when a specific alternative hypothesis is true:
Power (1 – β)
Sum of all results divided by the number of results:
The middle value that divides the distribution of data:
The most common value in data set:
The extent to which a test measures what it claims to measure:
The consistency with which the data collection process measures whatever it measures:
An estimate of the population mean is:
What is central limit theorem?
For a large enough sample size n, the distribution of the sample mean will approach a normal distribution
What is standard deviation (SD)?