AP Statistics Vocab Master

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

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

A group of experimental units that are similar and so are grouped together and then randomly assigned treatments.

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

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

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

The probability that an event does NOT happen.

The variable that may predict the changes in another variable.

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

The range from Q1 to Q3.

Making conclusions about a larger population based on sample data.

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

The distribution of many samples.

A non-symmetric distribution that has a distinct tail.

A process where each individual was randomly assigned to a treatment.

A number that describes some characteristic of a population.

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

The set of all possible outcomes of a chance process.

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

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

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

The proportion of observations that are less than or equal to a particular observation.

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

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

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

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

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

The exact counts of a value of a variable.

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

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

The claim that we assume is true until we find evidence against it.

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

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

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

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

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

A sample selected by taking individuals that select themselves.

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

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

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

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

A variable of value rather than description.

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

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

The maximum minus the minimum.

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

A sample selected by putting individuals into representative groups (heterogenous) & randomly choosing groups to sample.

A graph of the five-number summary.

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.

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

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

The science of data.

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

A variable of description rather than value.

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

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

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

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

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

A variable that takes on an infinite number of values.

A model that describes the approximate pattern of a histogram.

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

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

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

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

The distribution of just one sample.

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

The typical distance observations are away from the mean.

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

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

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

The standard deviation of a significance test or confidence interval.

A graph of quantitative data with two clear peaks.

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 middle number in a sorted list (resistant to outliers).

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

Measures the strength of the linear relationship between two quantitative variables, from -1 to 1.

A study where researchers deliberately impose treatment on the individuals.

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

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

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

The most common number in a list.

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

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

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

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

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

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

A sample selected by putting individuals into like-groups (homogenous) & randomly choosing individuals from each group.

A graph with bars that show the counts of the values of a quantitative variable.

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

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

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

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