AP Statistics Vocabulary

The distribution of many samples.

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

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

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

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

A variable of description rather than value.

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

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

A model that describes the overall pattern of a distribution.

The set of all possible outcomes of a chance process.

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

Making conclusions about a larger population based on sample data.

The most common number.

The exact counts of a variable.

The probability that an event does NOT happen.

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

Decisions based through a process of chance.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The range from Q1 to Q3.

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

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

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

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

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

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

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

The occurrence of two events at the same time.

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

A sample selected by taking individuals that select themselves.

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

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

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

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

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

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

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

A non-symmetric distribution that has a distinct tail.

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

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

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

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

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

The middle number (resistant to outliers).

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

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

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

A variable that takes on an infinite number of values.

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

The standard deviation of a significance test or confidence interval.

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

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

The distribution of just one sample.

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

The maximum minus the minimum.

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

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

A variable of value rather than description.

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

An individual that falls well outside the pattern of data.

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

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

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

An event that rarely would have happened just by chance.

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

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

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

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

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

A study where researchers deliberately impose treatment on the individuals.

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

A number that describes some characteristic of a population.

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

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

The variable that may predict the changes in another variable.

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

A graph of quantitative data with two clear peaks.

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

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

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

The science of data.

A graph of the five-number summary.

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

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

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