Statistics For Business And Economics Chapter 3 Vocabularly

Front 1

Sample Statistic

Back 1

A numerical value used as a summary measure for a sample ex. the sample mean, the sample variance, the sample standard deviation, s, s², and x-bar

Front 2

Population Parameter

Back 2

A numerical value used as a summary measure for a population ex. the population mean, the population standard deviation, µ, the population variance, δ², and δ

Front 3

Point Estimator

Back 3

A sample statistic, such as x-bar, s and s², used to estimate the corresponding population parameter.

Front 4

Mean

Back 4

A measure of central location computed by summing the data values and dividing by the number of observations.

Front 5

Weighted Mean

Back 5

The mean obtained by assigning each observation a weight that reflects its importance.

Front 6

Median

Back 6

A measure of central location provided by the value in the middle when the data are arranged in ascending order.

Front 7

Geometric Mean

Back 7

A measure of location that is calculated by finding the nth root of the product of n values.

Front 8

Mode

Back 8

A measure of location, defined as the value that occurs with greatest frequency.

Front 9

Percentile

Back 9

A value such that at least p percent of the observations are less than or equal to this value and at least (100-p) percent of the observations are greater than or equal to this value. The 50th percentile is the median.

Front 10

Quartiles

Back 10

The 25th, 50th and 75th percentiles, referred to as the first quartile, second quartile and third quartiles respectively.

Front 11

Range

Back 11

A measure of variability, defined to be the largest value minus the smallest value.

Front 12

Interquartile Range (IQR)

Back 12

A measure of variability, defined to be the difference between the third and first quartiles.

Front 13

Variance

Back 13

A measure of variability based on the squared deviations of the data values above the mean.

Front 14

Standard Deviation

Back 14

A measure of variability computed by taking the positive square root of the variance.

Front 15

Coefficient of Variation

Back 15

A measure of relative variability computed by dividing the standard deviation by the mean and multiplying by 100.

Front 16

Skewness

Back 16

A measure of the shape of a data distribution. Data skewed to the left result in negative skewness; a symmetric data distribution results in zero skewness; and data skewed to the right result in positive skewness.

Front 17

z-score

Back 17

A value computed by dividing the deviation about the mean (x₁-xbar) by the standard deviation s. A z-score is referred to as a standardized value and denotes the number of standard deviations x₁ is from the mean.

Front 18

Chebyshev's Theorem

Back 18

A theorem that can be used to make statements about the proportion of data values that must be within a specified number of standard deviations of the mean.

Front 19

Empirical Rule

Back 19

A rule that can be used to compute the percentage of data values that must be within one, two and three standard deviations of the mean for data that exhibit a bell shaped distribution.

Front 20

Outlier

Back 20

An unusually small or large data value.

Front 21

Five-Number Summary

Back 21

A technique that uses five numbers to summarize the data: smallest value, first quartile, median, third quartile and largest value.

Front 22

Box Plot

Back 22

A graphical summary of data based on a five-number summary.

Front 23

Covariance

Back 23

A measure of linear association between two variables. Positive values indicate a positive relationship; negative values indicate a negative relationship.

Front 24

Correlation Coefficient

Back 24

A measure of linear association between two variables that takes on values between -1 and +1. Values near +1 indicate a strong positive linear relationship; values near -1 indicate a strong negative linear relationship; and values near zero indicate the lack of a linear relationship.