AP Statistics Vocabulary

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

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

An event that rarely would have happened just by chance.

The probability that an event does NOT happen.

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

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

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

The set of all possible outcomes of a chance process.

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

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

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

A non-symmetric distribution that has a distinct tail.

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

A study where researchers deliberately impose treatment on the individuals.

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

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

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

The occurrence of two events at the same time.

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

The variable that may predict the changes in another variable.

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

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

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

Making conclusions about a larger population based on sample data.

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

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

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

The distribution of just one sample.

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

A number that describes some characteristic of a population.

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

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

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

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

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

Where each individual was randomly chosen and randomly assigned to a treatment.

Decisions based through a process of chance.

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

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.

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

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

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

The distribution of many samples.

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

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

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

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

The range from Q1 to Q3.

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

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

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

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

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

The most common number.

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

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

A variable of value rather than description.

An individual that falls well outside the pattern of data.

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

The science of data.

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

The middle number (resistant to outliers).

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

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

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

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

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

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

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

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

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

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

The standard deviation of a significance test or confidence interval.

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

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.

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

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

The exact counts of a variable.

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

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

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

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

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

A graph of quantitative data with two clear peaks.

A model that describes the overall pattern of a distribution.

A variable of description rather than value.

A sample selected by taking individuals that select themselves.

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

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

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

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

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

A variable that takes on an infinite number of values.

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

The maximum minus the minimum.

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

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

A graph of the five-number summary.