CHAPTER 4

Question 1

 The difference between the actual value and the average value.

Answer 1

Dispersion

Question 2

What are the MEASURES OF DISPERSION

Answer 2

range
average deviation
variance
standard deviation

Question 3

What are the MEASURES OF LOCATION

Answer 3

Quartiles
Deciles
Percentiles
Midhinge
Interquartile range
Quartile Deviation

Question 4

 The difference of the highest value and the lowest value in the data set.

Answer 4

Range

Question 5

 It is the absolute difference between the element and a given point.

Answer 5

Average Deviation

Question 6

 It is a statistical term that provides a good indication of volatility.
 It measures how widely values are dispersed from the average.
 It is calculatedas the square root of variance.

Answer 6

Standard Deviation

Question 7

It is the measure of risk

Answer 7

Volatility

Question 8

 It is used to approximate or to give a rough estimate of the standard deviation

Answer 8

Range Rule of Thumb

Question 9

 It is a mathematical expectation of the average squared deviations from the mean.

Answer 9

Variance

Question 10

It is the mean of the first (Q1) and third (Q3) quartiles in the data set. It is used to overcome potential problems introduced by extreme values (or outliers) in the data set.

Answer 10

Midhinge

Question 11

A is a measure of statistical dispersion, being equal to the difference between the third and first quartiles.

Answer 11

Interquartile Range (IQR)

Question 12

Interquartile Range is also called

Answer 12

midspread
middle fifty

Question 13

It is slightly better measure of absolute dispersion than the range.

It ignores the observation on the tails.

Answer 13

Quartile Deviation (QD)

Question 14

The difference samples from a population & calculate their quartile deviations, their values are quite likely to be sufficiently different called

Answer 14

sampling fluctuation

Question 15

It is calculated from the sample data does not help us to draw any conclusion about the quartile deviation in the population.

Answer 15

inference

Question 16

It is used when one is interested to compare standard deviations of two different units, coefficient of variations can be applied.

Answer 16

Coefficient of Variation (CV)

Question 17

is a statistical tool that measures dispersion in a data population that states that no more than 1 / k2 of the distribution’s values will be more than k standard deviations away from the mean.

Answer 17

Chebychev’s Theorem

Question 18

Statistical measure used to describe the distribution of observed data around the mean. It measures the relative peakedness or flatness of a distribution (as compared to the normal distribution, which shows a kurtosis of zero)

Answer 18

Kurtosis

Question 19

Three Types of Kurtosis

Answer 19

Leptokurtic
Mesokurtic
Platykurtic

Question 20

are distributions where values clustered heavily or pile up in the center. (k  0)

Answer 20

Leptokurtic

Question 21

are intermediate distribution w/c are neither too peaked nor too flat. (k = 0).

Answer 21

Mesokurtic

Question 22

are flat distributions with values more evenly distributed about the center with broad humps and shot tails. (k  0)

Answer 22

Platykurtic

Question 23

Measures the general shape of the distribution or the lack of symmetry of a distribution.

Ranges from –3 to +3.

It relates the difference between the mean and the median to the standard deviation.

The direction of the long tail of the distribution points the direction of the skewness.

Answer 23

Coefficient of Skewness

Question 24

Data values are evenly distributed.

The distribution is unimodal.

The mean, median, and mode are similar & are at the center of the distribution.

Answer 24

Symmetrical

Question 25

Most of the values in the data fall to the left of the mean and group at the lower end of the distribution.

The tail is to the right.

The mean is to the right of the median, and the mode is to the left of the median

Answer 25

Positively Skewed (or Right-Skewed).

Question 26

The mass of the data values fall to the right of the mean and group at the upper end of the distribution.

The tail to the left.

The mean is to the left of the median, and the mode is to the right of the median.

Answer 26

Negatively Skewed (or Left-Skewed).

Question 27

A data set should be checked for extremely high or extremely low values. These values are called outliers. Outliers can strongly affect the mean and standard deviation of a variable. One method in determining the outliers is when a data value in a data set is less Q1 – 1.5(IQR) or greater than Q3 + 1.5(IQR)

Answer 27

Outliers

Question 28

Outliers can strongly affect the mean and standard deviation of a variable.
true or false

Answer 28

true

Question 29

Introduced by John Tukey in 1970’s..
It gives the following information:
 If the median is near the center of the box, the distribution is approximately symmetric.
 If the lines are about the same length, the distribution is approximately symmetric.
 If the median falls to the right of the center of the box, the distribution is negatively skewed.
 If the median falls to the right of the center of the box, the distribution is negatively skewed.

Answer 29

Boxplot (Box-and-Whisker plot)

Question 30

 If the left line is larger than the right line, the distribution

Answer 30

negatively skewed

Question 31

If the right line is larger than the left line, the distribution is

Answer 31

positively skewed.