STAT-225: Lecture 5 - Empirical Rule, Measures of Position, Outliers, and Boxplots

These flashcards cover key concepts related to statistical analysis, including the empirical rule, z-scores, quartiles, outliers, and boxplots, which were discussed in the lecture.

Empirical Rule

A guideline stating that for a bell-shaped distribution: approximately 68% of data is within one standard deviation of the mean, 95% within two, and almost all within three.

Bell-Shaped Histogram

A histogram that is symmetric and has a single mode near its center, resembling a bell.

Z-score

A metric that indicates how many standard deviations a data point is from the mean of a data set.

Quartiles

Values that divide a dataset into four equal parts; specifically the first quartile (Q1), second quartile (Q2, median), and third quartile (Q3).

Five-Number Summary

A summary that includes the minimum, first quartile, median, third quartile, and maximum of a dataset.

Outlier

A value that is significantly higher or lower than most of the data in a dataset.

Boxplot

A graphical representation of the five-number summary, which shows the distribution of a dataset.

Percentiles

Values that divide a dataset into 100 equal parts, indicating the percentage of data points below a certain value.

Interquartile Range (IQR)

A measure of statistical dispersion that is the difference between the third quartile (Q3) and the first quartile (Q1).

Skewness

A measure of the asymmetry of the distribution of values in a dataset.