Intro Descriptive Stats/Data Sum Flashcards

1
Q

Measures of center and location

A

mean median mode weighted mean

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2
Q

measures of variation

A

range IQR variance standard deviation

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3
Q

negative of mean

A

affected by extreme outliers

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4
Q

pth percentile in data array means

A

p% are less than or equal to this value

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5
Q

quartiles do what to the data

A

split ranked data into 4 equal groups

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6
Q

formula to find path percentile in ordered array

A

p/100 (n+1) = position

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7
Q

disadvantages of range

A

ignores way in which data distributed

sensitive to outliers

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8
Q

advantage of IQR over range

A

not sensitive to outliers, provides sense of typicality (range of middle 50% of values)

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9
Q

variance

A

average of squared deviations of values form the mean

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10
Q

sample variance:

A

sum of diffs between each observation and mean squared and divided by samples - 1

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11
Q

difference in formula b/w sample variance and pop variance

A

population divide by N

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12
Q

standard deviation shows

A

variation about the mean

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13
Q

whiskers of box and whisker plots extend to

A

1.5 IQRs from 1st and 3rd queartile

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14
Q

scaled data types

A

values assigned by measurement (potassium) or contain (number of kids)

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15
Q

categorical data type

A

values assigned buy classification (blood type)

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16
Q

nominal measurement

A

categorical; cannot be ordered

occupation, gender, eye color

17
Q

ordinal measurement

A

categorical; categories convey info about direction but intervals between categories don’t reflect same quantitative difference (small/med/large)

18
Q

interval

A

scaled; data on measurement scale with arbitrary zero point in which numerically equal intervals at diff locations on scale reflect quantitative differences
dont have natural zero point
can destroy zero when doing calculations
temp F

19
Q

ratio

A

scaled and continuous
data on measurement scale with true and absolute zero
numerically equal intervals at diff locations on scale reflect same quantitative difference (height, weight)