M5

Question 1

are measures of the
average distance of each observation from the center of the
distribution.

Answer 1

Measures of Variability or Dispersion

Question 2

tell us how spread out

the scores are

Answer 2

Measures of Variability or Dispersion

Question 3

summarize and describe the extent to which scores in

a distribution differ from each other.

Answer 3

Measures of Variability or Dispersion

Question 4

two general classifications of Measures of

Variability or Dispersion:

Answer 4

1) Measures of absolute dispersion

2) Measures of relative dispersion

Question 5

cannot be used to compare variations of two data sets when
the averages of these sets differ a lot in value or when the
observations differ in units of measurements.

Answer 5

measures of absolute dispersion

Question 6

are expressed in the units of the original observations

Answer 6

measures of absolute dispersion

Question 7

This is the simplest but most unreliable measure of

dispersion since it only uses two values in the distribution

Answer 7

range

Question 8

is the difference between the highest and the lowest values.

Answer 8

range

Question 9

is the average of the squared deviation of each score from the
mean

Answer 9

variance

Question 10

is the square root of the average of the squared deviation of each score from the
mean, or simply, the square root of the variance

Answer 10

standard devation

Question 11

are unitless measures and are used when one wishes to
compare the scatter of one distribution with another
distribution.

Answer 11

measures of relative dispersion

Question 12

is the ratio of the standard deviation to the mean and is

usually expressed in percentage.

Answer 12

coefficient variation

Question 13

is used to compare
variability of two or more sets of data even when they are
expressed in different units of measurements.

Answer 13

coefficient variation

Question 14

At least the fraction of 1 − 1/𝑘^2
of measurements of any set of
data must lie within 𝑘 standard deviations of the mean.

Answer 14

chebyshev’s theorem

Question 15

are values
below which a specific fraction or percentage of the observations
in a given set must fall.

Answer 15

fractile or quartile

Question 16

measures how many standard deviation an observation is

above or below the mean.

Answer 16

z-score

Question 17

are values that divide a set of observations into

100 equal parts.

Answer 17

percentile

Question 18

are values that divide a set of observations into 10

equal parts.

Answer 18

decile

Question 19

are values that divide a set of observations into 4

equal parts

Answer 19

quartile

Question 20

describe the shape of a certain

distribution

Answer 20

measures of shapes

Question 21

refers to the degree of symmetry and asymmetry of a distribution.

Answer 21

Skewness

Question 22

is bell-shaped and symmetric through the mean

Answer 22

normal distribution,

Question 23

A distribution is skewed to the X if the mean is less than the median.
The bulk of the distribution is on the right.

Answer 23

left

negatively skewed

Question 24

A distribution is skewed to the X if the mean is greater than the median.
The bulk of the distribution is on the left.

Answer 24

right

positively skewed

Question 25

refers to the peakedness or flatness of a distribution.

Answer 25

Kurtosis

Question 26

is a normal distribution (kurtosis)

Answer 26

Mesokurtic

Question 27

is more peaked than the normal distribution (kurtosis)

Answer 27

Leptokurtic

Question 28

is flatter than the normal distribution (kurtosis)

Answer 28

Platykurtic