AP STATS VOCABULARY TERMS
Bar chart A graph used for qualitative data in which the classes are reported on the horizontal axis and the class frequencies on the vertical axis.
Class interval The size or width of the class.
Class frequency The number of observations in each class.
Class midpoint The point halfway between the lower limits of two consecutive classes.
Cumulative frequency distribution A grouping of data into mutually exclusive classes showing the number of observations at or below the upper limit of each class.
Cumulative frequency polygon A graph that consists of line segments connecting the points formed by the intersection of the class upper limit and the class cumulative frequency.
Frequency distribution A grouping of quantitative data into classes showing the number of observations in each mutually exclusive class.
Frequency table A grouping of qualitative data into mutually exclusive categories showing the number of observations in each category.
Frequency polygon A graph that consists of line segments connecting the points formed by the intersection of the class midpoint and the class frequency.
Histogram A graph in which the classes are marked on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are represented by the heights of the bars and the bars are drawn adjacent to each other.
Pie Chart A chart that shows the proportion or percent that each class represents of the total.
Relative class frequency Shows what fraction each class is of the total number of observations.
Arithmetic mean The sum of observations divided by the total number of observations.
Chebyshev’s theorem For any set of observations (sample or population), the minimum proportion of the values that lie within k standard deviations of the mean is at least 1 – 1/k2, where k is any constant greater than 1.
Empirical Rule For a symmetrical, bell-shaped frequency distribution, approximately 68 percent of the observations will lie within plus and minus one standard deviation of the mean; about 95 percent of the observations will lie within plus and minus two standard deviations of the mean; and practically all (99.7 percent) will lie within plus and minus three standard deviations of the mean.
Geometric mean The nth root of the product of n values.
Mean Deviation The mean of the absolute values of the deviations from the arithmetic mean.
Measure of location A single value that summarizes a set of data. It locates the center of the values.
Median The midpoints of the values after all observations have been ordered from the smallest to the largest, or from largest to smallest. Fifty percent of the observations are above the median and 50 percent are below the median.
Mode The value of the observation that appears most frequently.
Negatively skewed distribution The long tail is to the left or in the negative direction. The mean is smaller than the median or mode.
Parameter A characteristic of a population.
Positively skewed distribution The long tail is to the right; that is, in the positive direction. The mean is larger than the median or the mode.
Range The difference between the largest and smallest values in a data set.
Standard Deviation The square root of the variance.
Statistic A characteristic of a sample.
Symmetrical distribution A distribution that has the same shape on either side of the median.
Variance The arithmetic mean of the squared deviations from the mean.
Weighted mean The value of each observation is multiplied by the number of times it occurs. The sum of these products is divided by the total number of observations to determine the weighted mean.
Classical Probability A probability based on the assumption that the outcomes for an experiment are equally likely.
Collectively exhaustive At least one of the events must occur when an experiment is conducted.
Combination The number of ways to choose r objects from a group of n possible objects without regard to order.
Complement rule A way to determine the probability of an event occurring by subtracting the probability of an event not occurring from 1.
Conditional probability The probability of a particular event occurring, given that another event occurred.
Contingency table A table used to classify sample observations according to two or more identifiable characteristics.
Event A collection of one or more outcomes of an experiment.
Experiment A process that leads to the occurrence of one and only one of several possible observations.
Independence The occurrence of one event has no affect on the probability of the occurrence of another event.
Joint probability A probability that measures the likelihood two or more events will happen concurrently.
Law of large numbers Over a large number of trials the empirical probability of an event will approach its true probability.
Multiplication formula If there are m ways of doing one thing, and n ways of doing another thing, there are m × n ways of doing both.
Mutually exclusive The occurrence of one event means that none of the other events can occur at the same time.
Outcome A particular result of an experiment.
Permutation Any arrangements of r objects selected from a single group of n possible objects.
Posterior probability A revised probability based on additional information.
Prior probability The initial probability based on the present level of information.
Probability A value between zero and one, inclusive, describing the relative possibility (chance or likelihood) an event will occur.
Subjective concept of probability The likelihood (probability) of a particular event happening that is assigned by an individual based on whatever information is available.
Binomial probability distribution Describes the number of successes, x, in n independent trials of a statistical experiment. The probability of a success on a single trial, π, is the same for each trial.
Continuous random variable A variable that can assume one of an infinitely large number of values within certain limitations.
Discrete random variable A random variable that can assume only certain clearly separated values.
Finite population A population consisting of a small number of individuals, objects, or measurements.
Hypergeometric probability distribution. Describes the number of successes, x, in n trials of a statistical experiment. Each trial is conducted by selecting an item without replacement from a finite population of size N.
Poisson probability distribution Describes the number of times some event occurs during a specified interval. Also used to approximate a binomial probability distribution when the probability of success, π, is small, and n, the number of trials, is relatively large.
Probability distribution A listing of all the outcomes of an experiment and the probability associated with each outcome.
Random Variable A random variable whose value is determined by the outcome of a random experiment.
Continuity correction factor The value 0.5 subtracted or added, depending on the question, to a selected value when a discrete probability distribution is approximated by a continuous probability distribution.
Normal approximation to the binomial A binomial probability can be estimated using the normal probability distribution.
Normal probability distribution A continuous probability distribution uniquely determined by μ and σ.
Standard normal probability distribution A normal probability distribution with a mean of 0 and a standard deviation of 1.
Uniform probability distribution A continuous probability distribution with its values spread evenly over a range of values that are rectangular in shape and are defined by minimum and maximum values.
z value The distance between a selected value and the population mean in units of the standard deviation.
Bar chart A graph used for qualitative data in which the classes are reported on the horizontal axis and the class frequencies on the vertical axis.
Class interval The size or width of the class.
Class frequency The number of observations in each class.
Class midpoint The point halfway between the lower limits of two consecutive classes.
Cumulative frequency distribution A grouping of data into mutually exclusive classes showing the number of observations at or below the upper limit of each class.
Cumulative frequency polygon A graph that consists of line segments connecting the points formed by the intersection of the class upper limit and the class cumulative frequency.
Frequency distribution A grouping of quantitative data into classes showing the number of observations in each mutually exclusive class.
Frequency table A grouping of qualitative data into mutually exclusive categories showing the number of observations in each category.
Frequency polygon A graph that consists of line segments connecting the points formed by the intersection of the class midpoint and the class frequency.
Histogram A graph in which the classes are marked on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are represented by the heights of the bars and the bars are drawn adjacent to each other.
Pie Chart A chart that shows the proportion or percent that each class represents of the total.
Relative class frequency Shows what fraction each class is of the total number of observations.
Arithmetic mean The sum of observations divided by the total number of observations.
Chebyshev’s theorem For any set of observations (sample or population), the minimum proportion of the values that lie within k standard deviations of the mean is at least 1 – 1/k2, where k is any constant greater than 1.
Empirical Rule For a symmetrical, bell-shaped frequency distribution, approximately 68 percent of the observations will lie within plus and minus one standard deviation of the mean; about 95 percent of the observations will lie within plus and minus two standard deviations of the mean; and practically all (99.7 percent) will lie within plus and minus three standard deviations of the mean.
Geometric mean The nth root of the product of n values.
Mean Deviation The mean of the absolute values of the deviations from the arithmetic mean.
Measure of location A single value that summarizes a set of data. It locates the center of the values.
Median The midpoints of the values after all observations have been ordered from the smallest to the largest, or from largest to smallest. Fifty percent of the observations are above the median and 50 percent are below the median.
Mode The value of the observation that appears most frequently.
Negatively skewed distribution The long tail is to the left or in the negative direction. The mean is smaller than the median or mode.
Parameter A characteristic of a population.
Positively skewed distribution The long tail is to the right; that is, in the positive direction. The mean is larger than the median or the mode.
Range The difference between the largest and smallest values in a data set.
Standard Deviation The square root of the variance.
Statistic A characteristic of a sample.
Symmetrical distribution A distribution that has the same shape on either side of the median.
Variance The arithmetic mean of the squared deviations from the mean.
Weighted mean The value of each observation is multiplied by the number of times it occurs. The sum of these products is divided by the total number of observations to determine the weighted mean.
Classical Probability A probability based on the assumption that the outcomes for an experiment are equally likely.
Collectively exhaustive At least one of the events must occur when an experiment is conducted.
Combination The number of ways to choose r objects from a group of n possible objects without regard to order.
Complement rule A way to determine the probability of an event occurring by subtracting the probability of an event not occurring from 1.
Conditional probability The probability of a particular event occurring, given that another event occurred.
Contingency table A table used to classify sample observations according to two or more identifiable characteristics.
Event A collection of one or more outcomes of an experiment.
Experiment A process that leads to the occurrence of one and only one of several possible observations.
Independence The occurrence of one event has no affect on the probability of the occurrence of another event.
Joint probability A probability that measures the likelihood two or more events will happen concurrently.
Law of large numbers Over a large number of trials the empirical probability of an event will approach its true probability.
Multiplication formula If there are m ways of doing one thing, and n ways of doing another thing, there are m × n ways of doing both.
Mutually exclusive The occurrence of one event means that none of the other events can occur at the same time.
Outcome A particular result of an experiment.
Permutation Any arrangements of r objects selected from a single group of n possible objects.
Posterior probability A revised probability based on additional information.
Prior probability The initial probability based on the present level of information.
Probability A value between zero and one, inclusive, describing the relative possibility (chance or likelihood) an event will occur.
Subjective concept of probability The likelihood (probability) of a particular event happening that is assigned by an individual based on whatever information is available.
Binomial probability distribution Describes the number of successes, x, in n independent trials of a statistical experiment. The probability of a success on a single trial, π, is the same for each trial.
Continuous random variable A variable that can assume one of an infinitely large number of values within certain limitations.
Discrete random variable A random variable that can assume only certain clearly separated values.
Finite population A population consisting of a small number of individuals, objects, or measurements.
Hypergeometric probability distribution. Describes the number of successes, x, in n trials of a statistical experiment. Each trial is conducted by selecting an item without replacement from a finite population of size N.
Poisson probability distribution Describes the number of times some event occurs during a specified interval. Also used to approximate a binomial probability distribution when the probability of success, π, is small, and n, the number of trials, is relatively large.
Probability distribution A listing of all the outcomes of an experiment and the probability associated with each outcome.
Random Variable A random variable whose value is determined by the outcome of a random experiment.
Continuity correction factor The value 0.5 subtracted or added, depending on the question, to a selected value when a discrete probability distribution is approximated by a continuous probability distribution.
Normal approximation to the binomial A binomial probability can be estimated using the normal probability distribution.
Normal probability distribution A continuous probability distribution uniquely determined by μ and σ.
Standard normal probability distribution A normal probability distribution with a mean of 0 and a standard deviation of 1.
Uniform probability distribution A continuous probability distribution with its values spread evenly over a range of values that are rectangular in shape and are defined by minimum and maximum values.
z value The distance between a selected value and the population mean in units of the standard deviation.
