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A summary of useful formulas used in examining descriptive statistics

    Commonly used symbols

  • The symbol Σ means to add or to find the sum.
  • n = the number of data values in a sample
  • N = the number of people, things, etc. in the population
  • x ¯ size 12{ {overline {x}} } {} = the sample mean
  • s = the sample standard deviation
  • μ = the population mean
  • σ = the population standard deviation
  • f = frequency
  • x = numerical value

    Commonly used expressions

  • x * f = A value multiplied by its respective frequency
  • x size 12{ Sum {x} } {} = The sum of the values
  • (x * f) size 12{ Sum {(x} times f)} {} = The sum of values multiplied by their respective frequencies
  • ( x x ¯ ) or ( x μ ) = Deviations from the mean (how far a value is from the mean)
  • ( x x ¯ ) 2 or ( x μ ) 2 = Deviations squared
  • f ( x x ¯ ) 2 or f ( x μ ) 2 = The deviations squared and multiplied by their frequencies

    Box plot with outliers formulas

  • IQR=Q3 - Q1
  • LOWER FENCE=Q1 – 1.5(IQR)
  • UPPER FENCE=Q3 + 1.5(IQR)
  • OUTLIERS=greater than 1.5(IQR) but less than 3.0(IQR), this is indicated by: o
  • Far OUTLIERS=3.0(IQR) or greater, this is indicated by: *

Mean Formulas:

  • x ¯ = size 12{ {overline {x}} ={}} {} x n size 12{ { { Sum {x} } over {n} } } {} or x ¯ = size 12{ {overline {x}} ={}} {} (f · x) n size 12{ { { Sum {f times x} } over {n} } } {}
  • μ = size 12{μ={}} {} x N size 12{ { { Sum {x} } over {N} } } {} or μ size 12{μ} {} = (f · x) N size 12{ { { Sum {f times x} } over {N} } } {}

Standard Deviation Formulas:

  • s = size 12{s={}} {} Σ ( x x ¯ ) 2 n 1 or s = size 12{s={}} {} Σ f · ( x x ¯ ) 2 n 1
  • σ = size 12{σ={}} {} Σ ( x μ ¯ ) 2 N or σ = size 12{σ={}} {} Σ f · ( x μ ¯ ) 2 N

Formulas Relating a Value, the Mean, and the Standard Deviation:

  • value = mean + (#ofSTDEVs)(standard deviation), where #ofSTDEVs = the number of standard deviations
  • x size 12{x} {} = x + (#ofSTDEVs)( s )
  • x size 12{x} {} = μ size 12{μ} {} + (#ofSTDEVs)( σ )

Glossary

Frequency

The number of times a value of the data occurs.

Interquartile range (irq)

The distance between the third quartile (Q3) and the first quartile (Q1). IQR = Q3 - Q1.

Mean

A number that measures the central tendency. A common name for mean is 'average.' The term 'mean' is a shortened form of 'arithmetic mean.' By definition, the mean for a sample (denoted by x ¯ size 12{ {overline {x}} } {} ) is x ¯ size 12{ {overline {x}} } {} = Sum of all values in the sample Number of all values in the sample and the mean for a population (denoted byμ) is μ = Sum of all values in the population Number of all values in the population .

Median

A number that separates ordered data into halves. Half the values are the same number or smaller than the median and half the values are the same number or larger than the median. The median may or may not be part of the data.

Mode

The value that appears most frequently in a set of data.

Outlier

An observation that does not fit the rest of the data.

Percentile

A number that divides ordered data into hundredths.Example .  Let a data set contain 200 ordered observations starting with{2.3,2.7,2.8,2.9,2.9,3.0...}. Then the first percentile is (2.7 +2.8) 2 = 2.75, because 1% of the data is to the left of this point on the number line and 99% of the data is on its right. The second percentile is (2.9 +2.9) 2 = 2.9. Percentiles may or may not be part of the data. In this example, the first percentile is not in the data, but the second percentile is. The median of the data is the second quartile and the 50th percentile. The first and third quartiles are the 25th and the 75th percentiles, respectively.

Quartiles

The numbers that separate the data into quarters. Quartiles may or may not be part of the data. The second quartile is the median of the data..

Relative frequency

The ratio of the number of times a value of the data occurs in the set of all outcomes to the number of all outcomes.

Standard deviation

A number that is equal to the square root of the variance and measures how far data values are from their mean. Notation: s for sample standard deviation and σ for population standard deviation.

Variance

Mean of the squared deviations from the mean. Square of the standard deviation. For a set of data, a deviation can be represented as where x is a value of the data x ¯ size 12{ {overline {x}} } {} and x is the sample mean. The sample variance is equal to the sum of the squares of the deviations divided by the difference of the sample size and 1.

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Source:  OpenStax, Collaborative statistics using spreadsheets. OpenStax CNX. Jan 05, 2016 Download for free at http://legacy.cnx.org/content/col11521/1.23
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