Duplicate of AP Statistics Vocabulary

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

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

The occurrence of two events at the same time.

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

A study where researchers deliberately impose treatment on the individuals.

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

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

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

The distribution of just one sample.

The science of data.

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

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

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

The maximum minus the minimum.

A number that describes some characteristic of a population.

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

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

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

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

An individual that falls well outside the pattern of data.

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

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

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

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

A sample selected by taking individuals that select themselves.

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

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

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 set of all possible outcomes of a chance process.

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

A non-symmetric distribution that has a distinct tail.

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

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

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

The standard deviation of a significance test or confidence interval.

A graph of quantitative data with two clear peaks.

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

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

The range from Q1 to Q3.

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

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

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

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

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

A graph of the five-number summary.

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

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

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

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

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

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

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

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

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

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

A variable that takes on an infinite number of values.

The most common number.

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

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

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

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

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

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

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

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

The distribution of many samples.

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

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

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

The middle number (resistant to outliers).

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

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

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

A variable of value rather than description.

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

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

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

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

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

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

A model that describes the overall pattern of a distribution.

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

Making conclusions about a larger population based on sample data.

A variable of description rather than value.

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

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

The variable that may predict the changes in another variable.

The exact counts of a variable.

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

An event that rarely would have happened just by chance.

Decisions based through a process of chance.

The probability that an event does NOT happen.

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

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

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

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

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

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

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