AP Statistics Vocabulary (Complete)

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

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

The claim that we do not believe to be true that we are trying to find evidence against.

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

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

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

The set of all possible outcomes of a chance process.

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

The range from Q1 to Q3.

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

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

A graph of the five-number summary.

A non-symmetric distribution that has a distinct tail.

The most common number.

An individual that falls well outside the pattern 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.

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

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

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

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

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

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

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

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

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

The probability that a test will reject the Null when the Alternative is true.

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

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

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

A variable that takes on an infinite number of values.

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

The variable that may predict the changes in another variable.

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

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

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

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

A model that describes the overall pattern of a distribution.

The middle number (resistant to outliers).

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

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

A procedure using a sample statistic to make a decision about the validity of a claim.

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

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

The probability that the statistic would have taken on a value given the Null hypothesis true.

Making conclusions about a larger population based on sample data.

The distribution of many samples.

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

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

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

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

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

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

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

The individual terms that are added together to form the test statistic for categorical data.

The standard deviation of a significance test or confidence interval.

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

Occurs when we reject the Null hypothesis when it was actually true.

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

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

The exact counts of a variable.

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

A variable of value rather than description.

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

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

A fixed value used as a cutoff on what probability is or is not statistically significant.

__% of all such samples would produce a range of values that would capture the true value.

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

The occurrence of two events at the same time.

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

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

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

The number of standard deviations to be added/subtracted from the test statistic (z* or t*)

The number of individuals that would be found in each category if the Null hypothesis is true.

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

The probability that an event does NOT happen.

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

Decisions based through a process of chance.

A variable of description rather than value.

The number of individuals of a sample found in each category in response to a survey.

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

The science of data.

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

A number that describes some characteristic of a population.

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

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

The maximum minus the minimum.

A study where researchers deliberately impose treatment on the individuals.

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

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

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

A range of plausible values for a parameter, based on a statistic.

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

A sample selected by taking individuals that select themselves.

The distribution of just one sample.

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

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

The claim that we actually believe to be true that we are trying to find evidence for.

An event that rarely would have happened just by chance.

A graph of quantitative data with two clear peaks.