Measures of Dispersion in Business Flashcards

1
Q

measures of variability

A

which are statistical procedures to describe how spread out the data
Range
Standard Deviation
Variance

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2
Q

Range

A

defined as a single number representing the spread of the data

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3
Q

Standard deviation

A

defined as a number representing how far from the average each score is
the measure of how closely all of the data in the data set surrounds the mean
helps to identify a normal distribution of data by comparing the distance of the average of each data point’s variance to the mean.

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4
Q

Variance

A

defined as a number indicating how spread out the data is
seeks to find the parameter
direct measure of data variability
calculated as the average of the squared differences of all individual data points from the datasets mean value

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5
Q

population

A

defined as the complete collection to be studied, like all the police officers in your city
the larger group that the sample

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6
Q

sample

A

defined as a section of the population and would be a selection of police officers you are studying
a group to study

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7
Q

VAR.P

A

Variance in a Population

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8
Q

VAR.S

A

Variance in a Sample

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9
Q

normal distribution of data

A

represented when the majority of the data is found close to the average of the set.

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10
Q

continuous distribution

A

it is never a fixed value.

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11
Q

normally distributed

A

verified to represent the population that is being studied.

the data tends towards a middle value with equal amounts to the left and right.

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12
Q

outliers

A

extreme values

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13
Q

A bell curve plot

A

a visual representation that the data is normally distributed.

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14
Q

Chebyshev’s inequality

A

also known as Chebyshev’s theorem, is a statistical tool that measures dispersion in a data population

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15
Q

z-score

A

is a measure of distance from the mean in terms of how many standard deviations it is removed from the mean.
a measurement of how far away a point is from the mean in terms of standard deviations

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16
Q

To find the standard deviation

A
  1. take the mean of all the values in the set
  2. subtract the mean from each value
  3. square the difference
  4. find the mean of the sum of those differences
  5. take the square root of that number
17
Q

Z-Score calculation

A

It is calculated by subtracting the value of the mean from the value of the point in question, then dividing by the standard deviation of the set

18
Q

Empirical rule

A

majority of data will be contained within these three standard deviations, a z-score of 1 will always contain 68% of the individual data points within a set. Likewise, a z-score of 2 will always contain 95%, while a z-score of 3 will always contain 99.7%

19
Q

Six Sigma

A

a data-driven approach to process improvement