Duplicate of AP Statistics Vocabulary

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

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

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

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

The science of data.

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

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

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

The maximum minus the minimum.

A sample selected by taking individuals that select themselves.

The middle number (resistant to outliers).

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

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

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

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

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

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

A variable that takes on an infinite number of values.

The standard deviation of a significance test or confidence interval.

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

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

Decisions based through a process of chance.

The occurrence of two events at the same time.

An event that rarely would have happened just by chance.

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

The distribution of many samples.

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

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

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

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

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

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

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

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

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

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

The distribution of just one sample.

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

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

An individual that falls well outside the pattern of data.

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

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

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

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

The set of all possible outcomes of a chance process.

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

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

A non-symmetric distribution that has a distinct tail.

A graph of the five-number summary.

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

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

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

A graph of quantitative data with two clear peaks.

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

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

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

A variable of value rather than description.

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

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

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

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

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

A study where researchers deliberately impose treatment on the individuals.

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

A model that describes the overall pattern of a distribution.

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

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

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

The probability that an event does NOT happen.

A number that describes some characteristic of a population.

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

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

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

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

The variable that may predict the changes in another variable.

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

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

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

Making conclusions about a larger population based on sample data.

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 exact counts of a variable.

The most common number.

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

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

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

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

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

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

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.

The range from Q1 to Q3.

A variable of description rather than value.

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

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

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

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

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