CHAPTER 31**Statistics**

**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)

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

**The number of deaths during a specific time period:**

Mortality

**The proportion of patients alive at some point after the diagnosis:**

Survival

**What is the null hypothesis?**

Denoted by H_{o}; 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:**

Mean

**The middle value that divides the distribution of data:**

Median

**The most common value in data set:**

Mode

**The extent to which a test measures what it claims to measure:**

Validity

**The consistency with which the data collection process measures whatever it measures:**

Reliability

**An estimate of the population mean is:**

Sample mean

**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)?**