3VL Measures of dispersion: Flashcards

1
Q

1 quartile

A

viertel 1/4 quarter

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2
Q

1 quintile

A

1/5 one fifth

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3
Q

1 decentile

A

1/10 one ten

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4
Q

1 percentile

A

1/100 one over one hundred

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5
Q

Name Measures of Dispersion

A
  1. Range
  2. Interquartile range (IQR)
  3. Standard Deviation and variance
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6
Q

What does Range show?

A

The Range is simplest way of showing the variability

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7
Q

Formula of Range

A

Max-min

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8
Q

What are disadvantages of Range?

A

The range does not take into account
the data structure

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9
Q

Formula of IQR

A

Q3-Q1

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10
Q

What is IQR compering with range?

A

Range only distance between min and max but IQR is distance of the middle 50% of your observations

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11
Q

What does IQR represents?

A

IQR is representative of the central grouping of the data set

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12
Q

Advantage of IQR

A

Not affected by extreme values

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13
Q

How to find IQR?

A
  1. Find median (Q2)
  2. Exclude the mean
  3. Find mean with remaining values on
    both sides from first mean (find Q1 and Q3)
  4. Q3-Q1=IQR
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14
Q

What is Standard Deviation?

A

mean of all squared deviations in the dataset

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15
Q

What is deviation?

A

amount by which a value differs from the mean

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16
Q

Describe steps for calculating Standard Deviation

A
  1. Find the mean
  2. Find the distance of each value from the mean
  3. Square the deviations
  4. Sum up all squared deviations
  5. Divide by N
  6. Take the square root of the result
17
Q

Formula of Standard Deviation

A

Check notes

18
Q

How to interpretate Standard Deviation?

A

On average a value deviates by (SD) from the mean.
Change SD by calculated number

19
Q

Symbol of Standard deviation

20
Q

When to write higher and lower SD?

A

lower SD stands for less variability

21
Q

formula of variance

A

Squared standard Deviation or all steps of Standard deviation without last one

22
Q

When is it possible to compare standard deviations from different datasets?

A

2 constraints when it is possible:
1. If the datasets have the same unit of measurement (both = Euros)
AND
2. If there are the same number of observations (N/n) in the two datasets

23
Q

How to understand if variation is high in different datasets?

A

To understand whether variation is high in different datasets, one can compare it to the mean use Coefficient of variation (CV)

24
Q

Formula of CV (Coefficient of variation)

A

Check notes

25
With what level data can CV be used?
CV can only be used for ratio level data and should not be used for interval level data
26
What rule of thumb does CV have?
CV>1 rather high variability CV<1 rather low variability
27