AP Stats Quiz 1

quantitative discrete

specific, countable numeric values

quantitative continuous

variables that can take any value within a given range.

What are some examples of quantitative continuous data?

Examples include height, weight, temperature, and time.

categorical binary

A type of variable that has only two possible categories or outcomes, such as yes/no or true/false.

categorical non-binary

A type of variable that can have more than two categories or outcomes, such as colors, types of animals, or survey responses.

response variable

dependent variable

explanatory variable

independent variable that explains changes in another variable.

observational/experimental units

The individual entities upon which observations or experiments are conducted, such as people, animals, or objects.

variable

A characteristic or attribute that can take on different values among individuals or units.

approximately normal

symmetrical graph, similar to a bell curve

positive skew

distribution where most values are concentrated on the left, with a tail extending to the right.

negative skew

distribution where most values are concentrated on the right, with a tail extending to the left.

uniform distribution

a type of distribution where all outcomes are equally likely, resulting in a flat, even graph.

bimodal or multimodal

distribution with two or more peaks, indicating the presence of multiple modes.

outliers and unusual features

values that lie significantly outside the overall pattern of data, which can affect statistical analyses.

center

mean, median, mode

range

max-min

confounding variable

variable that is related to group membership and the response variable of interest

selection bias

sample selected to systematically exclude some part of the population of interest

response bias

Bias that results from problems in the measurement process

measurement bias

tools used to gather data result in systematic and consistent errors

nonresponse bias

responses are not obtained from all individuals selected

simple random sample

sample is chosen ensuring each different possible sample of the desired size has an equal chance of being chosen (random number generator)

cluster sampling

dividing population of interest into heterogeneous subgroups (clusters) and then picking a few of these clusters for the study

stratified sampling

dividing population of interest into homogeneous subgroups and samples are independently selected from each subgroup

systematic sampling

treating the population of interest as a list or sequential arrangement. picking every 1 in kth person or object for the sample.

convenience sampling (NO!)

using a convenient group.