Chapter 1 Looking at Data—Distributions

These flashcards cover key vocabulary and concepts from Chapter 1 regarding distributions and data analysis.

Data

Observations collected for analysis, consisting of cases, variables, values, and labels.

Variable

A special characteristic or attribute of a case.

Categorical Variable

A variable that places each case into one of several groups or categories.

Quantitative Variable

A variable that takes numerical values for which arithmetic operations make sense.

Outlier

An observation that lies outside the overall pattern of a distribution.

Histogram

A graphical display of the distribution of a quantitative variable using bars.

Boxplot

A graphical representation that showcases the median and quartiles of a data set.

Mean

The arithmetic average of a set of observations.

Median

The midpoint of a distribution, where half of the observations fall above and half below.

Standard Deviation

A measure of how spread out the observations are around the mean.

Normal Distribution

A symmetric, single-peaked, bell-shaped curve described by its mean and standard deviation.

Density Curve

A curve that shows the overall pattern of a distribution, with an area of exactly 1 beneath it.

1.5 IQR Rule

A rule to identify outliers where an observation is considered an outlier if it is more than 1.5 times the interquartile range above Q3 or below Q1.

Exploratory Data Analysis

An approach to analyzing data sets to summarize their main characteristics, often with visual methods.

Quartiles

Values that divide a data set into four equal parts.