AP Statistics Vocabulary

The most common number.

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

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

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

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

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

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

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

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

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

The range from Q1 to Q3.

A sample selected by taking individuals that select themselves.

The variable that may predict the changes in another variable.

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

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

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

The science of data.

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

Making conclusions about a larger population based on sample data.

The set of all possible outcomes of a chance process.

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

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

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

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

The probability that an event does NOT happen.

An individual that falls well outside the pattern of data.

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

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

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

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

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

The distribution of many samples.

The middle number (resistant to outliers).

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

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

The standard deviation of a significance test or confidence interval.

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

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

A number that describes some characteristic of a population.

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

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

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

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

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

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

A graph of quantitative data with two clear peaks.

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

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

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

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

The distribution of just one sample.

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

A variable that takes on an infinite number of values.

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

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

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

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

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

A non-symmetric distribution that has a distinct tail.

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

A model that describes the overall pattern of a distribution.

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

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

A graph of the five-number summary.

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

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

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

The exact counts of a variable.

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

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

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

The occurrence of two events at the same time.

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

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

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

The maximum minus the minimum.

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

Decisions based through a process of chance.

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.

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

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

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

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

A variable of description rather than value.

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

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

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

A study where researchers deliberately impose treatment on the individuals.

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

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

An event that rarely would have happened just by chance.

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

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

A variable of value rather than description.

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

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

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

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

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