AP Statistics Vocabulary (Semester 1 only)

The middle number (resistant to outliers).

When randomly selected individuals cannot be contacted or refuse to participate.

A family of distributions that always take on positive values and are skewed right.

The variable that may predict the changes in another variable.

The occurrence of two events at the same time.

Explains how well the regression line fits the data, from 0 (weak) to 1 (strong).

A diagram used to display the sample space of a chance process involving a sequence of outcomes

The exact counts of a variable.

When the design of a study would consistently give an over or underestimate of the true value.

An imitation of a chance behavior that uses a model that accurately represents the situation.

A number between 0 and 1 that describes the proportion of an outcome in a chance process.

When it is not possible for two event to occur simultaneously.

The maximum minus the minimum.

When a distribution is even across the full range of values of the variable.

A study where researchers deliberately impose treatment on the individuals.

When a group of the population does not get accurate representation in a sample.

An inactive (fake) treatment for which some subjects may actually respond.

The most common number.

The probability that an event does NOT happen.

The sum of the values of the observations divided by the number of observations.

A number that describes some characteristic of a population.

Minumum, Q1, Median, Q3, and Maximum values of a data set.

When the right and left sides of a distribution are mirror images of each other.

The occurrence of one event or the other, or both.

The distribution of many samples.

A sample where each individual was randomly chosen from the population.

A graph of quantitative data with two clear peaks.

When neither the researchers nor the subjects know which treatments were assigned to groups.

A non-symmetric distribution that has a distinct tail.

A graph that shows bars that have ranges for counts of a continuous variable.

The response value a Least Squares Regression Line would expect for a given explanatory value.

The distribution of total values for categorical variables on a one-way or two-way table.

The smallest collection of individuals to which a treatment is to be applied.

A sample by putting individuals into population-like groups and randomly choosing one group.

Decisions based through a process of chance.

An outcome of a chance process is more likely to occur if it has not occurred for a long time.

The distribution of a random variable of continuing trials until a certain number of successes.

A study that attempts to survey every individual of the population.

A variable that takes on an infinite number of values.

The fraction of the variation that can be explained by the least-squares regression line (r²).

In experiments, when all variables except for the explanatory variable must be kept the same.

The science of data.

A smaller group of individuals whose information is used to infer about a larger group.

Explains the linear relationship between two quantitative variables, from -1 to 1.

The distribution of just one sample.

A sample where each individual was randomly chosen and randomly assigned to a treatment.

A model that describes the overall pattern of a distribution.

Making conclusions about a larger population based on sample data.

The proportion of observations that are lower than a particular observation.

When the effects of two different variables on a response variable cannot be told apart.

A group of experimental units that are similar and so are treated as one experimental unit.

Individuals are monitored for measures of variables of interest but not influenced in response.

When knowing the value of one variable helps to predict the value of another.

An individual that falls well outside the pattern of data.

The range from Q1 to Q3.

The set of all possible outcomes of a chance process.

The four evenly sized sections of a set of ordered data.

A number from a sample used to estimate some characteristic of a population.

The total value to be added/subtracted from the test statistic to find the interval max/min.

A graph that shows the relationship between two quantitative variables using dots.

A class of density curves that are symmetric, single-peaked, and bell-shaped.

An accurate statistic used to approximate the parameter of a population.

The probability that an event will occur given that another event has already occurred.

The difference between an observed value and its predicted/expected value.

A Normal distribution with mean 0 and standard deviation of 1.

The proportion of a chance process will approach a single value as you do more trials.

When randomly selected individuals in a sample do not provide accurate information.

A common form of blocking in comparing two different treatments, often on the same sample.

A sample obtained by putting individuals into like-groups and randomly choosing some from each.

When only either the researchers or the subjects know which treatments were assigned to groups.

The typical or common distance observations are away from the mean.

A sampling distribution of at least 30 will be approx normal even if the population is not.

A variable that takes on a finite number of values (usually no decimals).

The distribution of a random variable with the number of trials set in advance.

A sample selected by taking individuals that were easy to reach.

Occurs when we fail to reject the Null hypothesis when it was actually false.

The # of standard deviations an observation falls from the center of a Normal distribution.

A variable of description rather than value.

A graph of the five-number summary.

The entire group of individuals which we are interested in knowing something about.

A sample selected by taking individuals that select themselves.

A family of distributions like the Normal curve except with more variability in the samples.

A variable of value rather than description.

An event that rarely would have happened just by chance.

The amount of counts of a variable out of all counts, often expressed as a percent.

The (inaccurate) use of a regression line to estimate outside the range of the given data.