Duplicate of AP Statistics Vocabulary

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

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

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 it is not possible for two event to occur simultaneously.

A sample selected by taking individuals that select themselves.

A study where researchers deliberately impose treatment on the individuals.

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

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

An individual that falls well outside the pattern of data.

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

Decisions based through a process of chance.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The range from Q1 to Q3.

A number that describes some characteristic of a population.

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

The exact counts of a variable.

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

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

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

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

A variable of description rather than value.

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

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

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

An event that rarely would have happened just by chance.

The middle number (resistant to outliers).

The distribution of just one sample.

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.

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

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

Making conclusions about a larger population based on sample data.

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

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

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

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

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

A model that describes the overall pattern of a distribution.

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

The variable that may predict the changes in another variable.

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

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

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

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

The set of all possible outcomes of a chance process.

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

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

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

The standard deviation of a significance test or confidence interval.

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

The maximum minus the minimum.

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

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

A graph of the five-number summary.

A variable that takes on an infinite number of values.

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

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

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

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

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

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

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

The distribution of many samples.

The probability that an event does NOT happen.

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

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

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

The occurrence of two events at the same time.

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

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

A non-symmetric distribution that has a distinct tail.

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

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

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

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