AP Statistics Vocabulary

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

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

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

The probability that an event does NOT happen.

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

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

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

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

The standard deviation of a significance test or confidence interval.

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

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

An event that rarely would have happened just by chance.

A model that describes the overall pattern of a distribution.

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

The maximum minus the minimum.

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

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

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

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

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

A variable of description rather than value.

A sample selected by taking individuals that select themselves.

The middle number (resistant to outliers).

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

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

The occurrence of two events at the same time.

The range from Q1 to Q3.

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

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

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

The set of all possible outcomes of a chance process.

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

The science of data.

A variable that takes on an infinite number of values.

A number that describes some characteristic of a population.

The most common number.

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

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

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

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

A variable of value rather than description.

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

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

Decisions based through a process of chance.

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

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

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

The initial claim that we test.

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

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

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

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

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

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

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

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

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

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

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

The distribution of a random variable with two unique, specific outcomes.

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

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

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

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

Making conclusions about a larger population based on sample data.

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

An individual that falls well outside the pattern of data.

The distribution of many samples.

The secondary claim that we are trying to find evidence for.

The variable that may predict the changes in another variable.

A graph of the five-number summary.

A study where researchers deliberately impose treatment on the individuals.

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

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

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

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

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

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

A family of distributions used when the sample size is small or the population standard deviation is unknown.

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

A non-symmetric distribution that has a distinct tail.

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

The exact counts of a variable.

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

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

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

A graph of quantitative data with two clear peaks.

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

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

The distribution of just one sample.

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

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

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