ap stats summer vocab

Population

The entire collection of individuals or measurements about which information is desired.

Sample

A subset of the population selected for study.

Descriptive Statistics

Numerical, graphical, and tabular methods for organizing and summarizing data.

Inferential Statistics

Methods for generalizing a sample to a population

Statistic

A characteristic or variable of a sample; used to estimate the value of a population parameter.

Categorical data

Individual responses are categorical responses (nonnumerical).

Numerical data

Individual responses are numerical (quantitative) in nature.

Discrete numerical data

Possible values are isolated points along the number line.

Continuous numerical data

Possible values form an entire interval along the number line.

Bar chart

A graph of a frequency distribution for a categorical data set. Each category is represented by a bar for the corresponding frequency or relative frequency.

Dotplot

A graph of numerical frequency data among groups where each observation is represented by a dot on a horizontal measurement scale.

Parameter

characteristic or variable of a population, describes the properties of entire populations.

Observational Study

A study that observes characteristics of an existing population or a sample of it.

Controlled Experiment

The way to investigate the effect of experimental conditions on a response variable to understand cause-and-effect relationships. Researcher controls how subjects are assigned to groups and which treatments each group receives.

Extraneous variable

A variable that is not an explanatory variable in the study but is thought to affect the response variable.

Explanatory variable (factor)

The variable that's manipulated to find the effect on the response variable.

Response variable

Thought to be related to the explanatory variable in an experiment, with a change in the explanatory variable causing an effect on it. Not controlled by experimenter.

Confounding variable

Variable relating to the explanatory variable/ experimental groups or how they were formed and the response variable

Selection bias

The way you select the sample excludes some part of the population

Response Bias

The way you observe produces values that differ from the true value in some way.

Placebo

A treatment that is identical to other treatments in an experiment but doesn't have active ingredients.

Blinding

If subjects do not know which treatment was received and those measuring the response do not know which treatment was given to which subject, the experiment is described as double-blind. If only one of the two types of blinding is present, the experiment is single-blind. often to make sure that subjects dont know if they got a placebo.

Blocking

Using extraneous variables to create groups (blocks) that are similar, so that response variable values will be similar within the block. All experimental conditions (treatments) are then tried in each block.

Census

Obtaining information from an entire population

Treatment

The experimental conditions made for the study. combinations of independent variable levels.

Random assignment

(of subjects to experimental groups and treatments or of treatments to trials) ensures that the experiment does not favor one experimental condition over another.

Simple random sample

Selected in a way where a sample has size n, each sample of size n has a chance of being selected from the population

Stratified Sampling

Population gets divided into strata, or subgroups, and a random sample is taken from each stratum.

Sampling without replacement:

Once an individual from the population is selected for inclusion in the sample, it may not be selected again in the sampling process. A sample selected without replacement includes n distinct individuals from the population.

Sampling with replacement

After an individual from the population is selected for inclusion in the sample and the corresponding data are recorded, the individual is placed back in the population and can be selected again in the sampling process.

Probability

Likelihood that an event occurs

Sample mean

The average of data values from a sample taken from the population

Population mean

The sum of the values in the population divided by the population size

Sample space

All possible outcomes of an experiment

Inference

Making conclusions about a population based on data from a sample

Two Way table

Table showing frequency and relationship between two categorical variables

measure of center

Describing a data set based on the center of the data set, through things like mean, median, and mode

Measure of spread

How much data is spread out/dispersed with relation to the center, through things like range, IQR, variance, and std dev

histogram

columns plotted on a graph to show frequency distribution of numerical data

boxplot

Data is split into quartiles. Q2 is the median, and a line is drawn there. The front and end of the box are Q1 and Q3 lines. Then whiskers are drawn to the smallest and largest extremes, excluding outliers.

Stemplot

Quantitative data separated into a stems (left) and leaves (right), which each having some unit

measure of position

where a data point is relative to other data values in a data set. can be measured using things like percentiles, quartiles, z scores and deciles.

Components of experimental design

Control of potential extraneous and confounding variables, Random assignment of treatments to trials and subjects to treatments, replication of experimental units in each treatment group, blocking to create experimental groups with similar extraneous variables & blinding.