Module 7 Flashcards

1
Q

indicates the extent to which the individual items in a series are scattered about an average

A

Measures of Dispersion

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

a point at which certain percentage of the observations lie below the indicated point when all the observations are ranked in descending order

A

percentile of a distribution

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

what are the Measures of Absolute Dispersion

A

Range, Standard Deviation, Variance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

what are the Measures of Relative
Dispersion

A

Coefficient of Variation, Standard Score

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

expressed in the units of the original observations

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

A

Measures of Absolute Dispersion

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Distance covered by the scores in a distribution, from the smallest score to the largest score

Most obvious way to describe how spread out the scores are

A

Range

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

what is the formula for range

A

Highest – Lowest

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

state characteristics of range

A
  • uses only extreme values
    *outlier can greatly alter the value
    *cannot be approximated from open-ended frequency distributions
    *fails to communicate any information about the clustering or the lack of clustering of the values between the extremes
  • outlier can greatly alter the value
  • cannot be approximated from open-ended frequency distributions
  • unreliable when computed from frequency distribution table with gaps or zero frequencies
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

equals the mean of the squared deviations

A

variance

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

uses the mean of the distribution as a reference point and measures variability by considering the distance between each score and the mean

A

standard deviation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

give characteristics of standard deviations

A
  • Affected by the value of each observation
  • Cannot be computed from an open-ended
    distribution
  • If each observation of a set of data is transformed to a new set by addition/subtraction of a constant, the SD of a
    new set of data is the same as the SD of the
    original data set
  • If a set of data is transformed to a new set by multiplying/dividing each observation by a constant “c”, the SD of the new data set is equal to the SD of the original data set
    multiplied/divided by “c”
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

when do u use population standard deviation

A
  • You have the entire population
  • You have a sample of a larger population, but only interested in a sample and you do not wish to generalize your findings to the population
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

when do u use sample standard deviation

A

You have a sample, but wish to make a statement about the population SD, from which the sample is drawn

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

unitless; used when one wishes to compare the scatter of one distribution with another distribution

A

Measures of Relative Dispersion

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q
  • ratio of the SD to the mean
  • usually expressed in percentage
A

COEFFICIENT OF VARIATION

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

AKA Gaussian Distribution

A

normal distribution

17
Q
  • Most important distribution
  • Describes well the distribution of random variables arise in practice
A

Normal Distribution

18
Q

the different measures of Skewness

A

skewness, kurtosis, extreme values

19
Q

Horizontal stretching of a frequency distribution to one side or the other, so that the tail of the observations is longer and has more observations than the other tail

A

Skewness

20
Q

characterized by a vertical stretching or flattening of the frequency distribution

A

Kurtosis

21
Q

values considered to be abnormally far above or below the mean and one of the most perplexing problems for the analysis of data

A

Extreme Values (outliers):

22
Q

shows the degree of asymmetry, or departure from symmetry of a distribution

A

Measures of Skewness

23
Q
  • Distribution tapers more to the right than to the left
  • Longer tail to the right
  • More concentration of values below the mean
A

Positively Skewed

24
Q
  • Distribution tapers more to the left than to the right
  • Longer tail to the left
  • More concentration of values above the mean
A

Negatively Skewed

25
Q

graph that is very useful for displaying the following features of the data: location, spread, symmetry, extreme, outliers

A

box plot