Descriptive Statistics Flashcards

1
Q

mean

A

average of a set of measurements

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2
Q

what is the most common metric to describe LOCATIONN of a frequency distribution

A

mean

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3
Q

sample mean

A

average of the measurements in the sample

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4
Q

how to calculate the sample mean

A

sum of all the observations divided by the number of observations

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5
Q

standard deviation (s)

A

measures how far from the mean the observations typically are

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6
Q

most used measurement of distribution spread

A

standard deviation

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7
Q

what does a large vs small standard deviation indicate about the data

A

large = most of the observations are far from the mean

small = most observations are close to the mean

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8
Q

how to calculate the standard deviation

A

the square root of the variance

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9
Q

can the standard deviation be negative

A

NO

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10
Q

variance (s2) formula

A
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11
Q

what is the deviation

A

difference between a measurement and the mean

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12
Q

what will the average of the deviations be

A

zero

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13
Q

how to find the variance

A

square the deviations

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14
Q

how is the standard deviation often expressed

A

relative to the mean

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15
Q

coefficient of variation (CV)

A

calculates the standard deviation as a percentage of the mean

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16
Q

higher vs lower coefficient of variation

A

higher = more variability relative to the mean

lower = individuals are more consistently the same relative to the mean

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17
Q

when does the coefficient of variation only make sense

A

when all measurements are greater than or equal to zero

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18
Q

formula for coefficient of variation

A

divided the standard deviation by the sample mean

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19
Q

what is the sample size in a frequency table

A

the frequency total NOT the number of rows (this total is 395)

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20
Q

median

A

middle observation in a set of data

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21
Q

how is the median often displayed

A

a box plot

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22
Q

how to calculate the median

A

sort the sample observations from smallest to largest

(odd number of observations = middle number)

(even number of observations = average of middle pair)

23
Q

quartiles

A

values that partition data into quarters

24
Q

what is the first, second and third quartiles

A

first: Middle value of the measurement below the median

second: the median

third: Middle value of the measurements LARGER than the median

25
Q

interquartile range (IQR)

A

Span of the middle half of the data from the first quartile to the third quartile

26
Q

how to calculate the IQR

A

Compute the first and third quartiles

Then subtract them

27
Q

Box plots display

A

the median and interquartile range

28
Q

what do the lower and upper edges of a box plot represent

A

first and third quartiles

29
Q

what is the interquartile range in a box plot

A

the span of the box

30
Q

what is the horizontal line dividing a box in box plot

A

the median

31
Q

how are extreme values shown in a box plot

A

by a dot or line

32
Q

what are examples of measures of spread

A

standard deviation
interquartile range

33
Q

what are examples of measures of location

A

mean and median

34
Q

when are the mean and standard deviation LESS informative than the median and interquartile range

A

data is strongly skewed or have extreme observations

35
Q

when data is strongly skewed or have extreme observations what measures are LESS informative

A

mean and standard deviation

36
Q

median vs mean

A

median is the middle measurement of a distribution BUT the mean is the center of gravity

37
Q

is the mean sensitive to extreme values

A

YES

38
Q

is the median sensitive to extreme values

A

Less so than the mean

39
Q

is the standard deviation sensitive to extreme values

A

YES

40
Q

is the interquartile range affected by extreme values

A

NO

41
Q

percentile vs quantiles

A

percentile - value below which the X percent of the individuals lie

(50th percentile = median = half the data OR 25th percentile = first quartile)

quantiles - proportion less than or equal to the given value (represented by decimal)

(10th percentile = 0.10 quartile
Median = 0.5 quartile)

42
Q

most used descriptive stats for a categorical variable

A

proportions

43
Q

what is the analogues statement for the mean, standard deviation, median and interquartile range

A

mean : Standard deviation :: median : interquartile range

44
Q

how is the Coefficient of variation beneficial in comparisons

A

allows us to compare variables with different units because the CV is unitless

45
Q

how are measures of mean and median similar

A

both describe location of frequency distribution

46
Q

what is the purpose of the median

A

to partition ordered measures into two halves

47
Q

are the mean, median, st.d and IQR similar or different when the distribution is symmetrical and unimodal

A

give similar information

48
Q

what parameter gives the bulk of information when data is skewed

A

the median because the mean is pulled towards the outliers and away from the bulk of data

49
Q

is standard deviation more or less sensitive to extreme values than the mean

A

MORE sensitive

50
Q

why is the st.d more sensitive to extreme values than the mean

A

because extreme values of large deviations which when squared amplify that effect

51
Q

when is IQR better for data and when is the STDEV

A

IQR - regarding the MAIN part of the data

STDEV - better for information of ALL data in the distribution (with the spread)

52
Q

how do you calculate a proportion

A

number of category divided by total number in all categories

53
Q

what does the proportion (P-hat) estimate

A

estimate of true population proportion (p)

54
Q

what must the proportion sum to

A

1