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Glossary
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A
Addition Rule - The probability of either outcome A or outcome B is the sum of the probability of A and B.
C
Complement Rule - If the probability of outcome A plus the probability of outcome B is 100%, the probability of outcome A is equal to one minus the probability of outcome B.
cumulative probability - The proportion of cases that are equal to or lower than a particular value for a variable.
D
dependence - Two variables are dependent on each other when one variable influences the second variable.
E
Empirical Rule - States that, for any normally distributed variable, a fixed proportion of cases will fall between any given standard deviations from the mean or beyond any given standard deviation from the mean.
I
independence - Two variables are independent of each other when one variable has no influence on the second variable.
M
Multiplication Rule - If the probabilities of outcomes A and B are independent of each other, the probability of both outcome A and outcome B occurring is found by multiplying the probability of outcome A by the probability of outcome B. If outcomes A and B are not independent of each other, then the probability of both outcome A and outcome B occurring is found by multiplying the probability of outcome A by the probability of outcome B, after adjusting the probability of outcome B for its dependence on A.
N
normal distribution - A bell-shaped curve that can be used to find probabilities at specified values or ranges of values for variables that are normally distributed. The basis of inferential statistics.
Z
z-score - Refers to values of the normal distribution; the distance between any value of a normally distributed variable and its mean or between any sample statistic and the population parameter, expressed in standard deviations or standard errors.
