Bus Stat Chap 3

Business Statistic Vocab for chap 3

represents the population mean. Greek lowercase letter “mu”

N

number of values in a population

x

represents any particular value

Σ

Greek capital letter “sigma” and indicates the operation of adding

Σx

sum of x values in the population

=Σx/N

Population Mean

Parameter

a characteristic of a population

x̄

represents the sample mean. It is read “x bar”

n

number of values in the sample

x̄=Σx/n

Sample mean

Statistic

A characteristic of a sample

Median

The midpoint of the value after they have been ordered from the minimum to the maximum values

Mode

The value of the observation that appears most frequently

x̄_w= Σ(wx)/Σw

Weighted Mean

GM = nth sqrt [(x₁)(x₂)…(x_n)]

Geometric Mean (average percent of increase usually)

GM = nth sqrt [(value at end of period)/(Value at start of period)] - 1

Rate of increase over time

Range = Maximum value - Minimum value

Range

Σ(x-μ)² /N

Variance, The arithmetic mean of the squared deviations from the mean

σ²

population variance. it is read as “sigma squared”

σ² = Σ(x-μ)²/N

Population Variance

σ = sqrt [Σ(x-μ)²/N]

Population Standard Deviation

s² = Σ(x-x̄)²/(n-1)

Sample Variance (s²)

s = sqrt [Σ(x-x̄)²/(n-1)]

Sample Standard Deviation

ChebyShev’s Theorem

For any set of observations (sample or population), the proportion of the values that lie within k standard deviations of the mean is at least 1 - 1/k² where k is any value greater than 1

Empirical rule/ normal rule

For a symmetrical, bell-shaped frequency distribution, approximately 68% of the observations will lie within plus and minus 1 standard deviation of the mean, about 95% of the observations will lie within plus and minus 2 standard deviations of the mean, and practically all will lie within plus and minus 3 standard deviations of the mean

σ

Population standard deviation