This document discusses when to use parametric vs non-parametric methods for analyzing relationships between variables. Parametric methods are appropriate when data is scaled, meaning points are equally spaced along the scale, and the distribution is normal. An example is provided of researchers examining the relationship between death anxiety and religiosity, where subjects completed scaled questionnaires and the data had a normal distribution. Therefore, a parametric method would be suitable for analysis.

1. Parametric or Nonparametric
Methods

2. This presentation is designed to help you
determine if using parametric or non-parametric
methods would be most appropriate with the
relationship question you are working on.

3. This presentation is designed to help you
determine if using parametric or non-parametric
methods would be most appropriate with the
relationship question you are working on.
Parametric Method
Non-Parametric Method

4. What are parametric methods?

5. Parametric methods are used when we examine
sample statistics

6. Parametric methods are used when we examine
sample statistics as a representation of
population parameters

7. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.

8. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Normal
Distribution

9. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Normal
Distribution
A normal distribution tends to
have the same number of data
points on one side of the
distribution as it does on the
other side. These data points
decrease evenly to the far left and
far right.

10. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Normal
Distribution
A normal distribution tends to
have the same number of data
points on one side of the
distribution as it does on the
other side. These data points
decrease evenly to the far left and
far right.
50%

11. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Normal
Distribution
A normal distribution tends to
have the same number of data
points on one side of the
distribution as it does on the
other side. These data points
decrease evenly to the far left and
far right.
50% 50%

12. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Normal
Distribution
A normal distribution tends to
have the same number of data
points on one side of the
distribution as it does on the
other side. These data points
decrease evenly to the far left and
far right.

13. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Normal
Distribution
A normal distribution tends to
have the same number of data
points on one side of the
distribution as it does on the
other side. These data points
decrease evenly to the far left and
far right.

14. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Normal
Distribution
A normal distribution tends to
have the same number of data
points on one side of the
distribution as it does on the
other side. These data points
decrease evenly to the far left and
far right.

15. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.

16. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Speed

17. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Temperature

18. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Weight

19. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Scaled Data

20. Parametric methods are used when we examine
sample statistics as a representation of
population parameters when the distribution is
normal and the data are scaled.
Data which is scaled have equal points along the scale
(e.g., 1 pound is the same unit of measurement across
the weight scale)

21. A parametric question that deals with
relationships might look like this:

22. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:

23. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
&

24. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:

25. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
Death Anxiety
Scale

26. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:

27. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.)
A data sample is provided to the right:

28. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.)
A data sample is provided to the right:

29. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity).
A data sample is provided to the right:
Measure of
Religiosity

30. Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:

31. Death Anxiety Religiosity
38 4
42 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:

32. Death Anxiety Religiosity
38 4
42 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
This data has enough
spread to be
considered scaled

33. Death Anxiety Religiosity
38 4
39 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
Same with this data.

34. Death Anxiety Religiosity
38 4
39 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
The skew for this data set is
0.26 (a skewed distribution will
have a skew value greater
than +2.0 or less than -2.0).
While slightly skewed to the
right, the distribution would be
considered normal

35. Death Anxiety Religiosity
38 4
39 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
The skew for this data set is
0.26 (a skewed distribution will
have a skew value greater
than +2.0 or less than -2.0).
While slightly skewed to the
right, the distribution would be
considered normal

36. Death Anxiety Religiosity
38 4
39 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
The skew for this data set is
0.26 (a skewed distribution will
have a skew value greater
than +2.0 or less than -2.0).
While slightly skewed to the
right, the distribution would be
considered normal

37. Death Anxiety Religiosity
38 4
39 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
At the end of this
module, please go to the
presentation entitled
“Assessing Skew” to
learn how to assess the
level of skew in your
data set in SPSS.
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
You can access it
through the link on the
webpage you just left.

38. Death Anxiety Religiosity
38 4
39 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
The skew for this data set is 0.03
and therefore the distribution
would be considered normal

39. Death Anxiety Religiosity
38 4
39 3
29 11
31 5
28 9
15 6
24 14
17 9
19 10
11 15
8 19
19 17
3 10
14 14
6 18
Researchers interested in determining if
there is a relationship between death
anxiety and religiosity conducted the
following study. Subjects completed a
death anxiety scale (high score = high
anxiety) and also completed a checklist
designed to measure an individuals degree
of religiosity (belief in a particular religion,
regular attendance at religious services,
number of times per week they regularly
pray, etc.) (high score = greater religiosity.
A data sample is provided to the right:
Because the data are scaled
and the distributions are both
normal, this analysis would be
handled with a parametric
method.

40. In summary,

41. In summary, if and only if the data are BOTH
scaled and the distribution is normal, then you
will use a parametric method.

42. In summary, if and only if the data are BOTH
scaled and the distribution is normal, then you
will use a parametric method.
Data: Scaled
Distribution: Normal

43. In summary, if and only if the data are BOTH
scaled and the distribution is normal, then you
will use a parametric method.
Data: Scaled
Distribution: Normal
Use a
PARAMETRIC
Test

44. What are nonparametric methods?

45. Non-Parametric methods are used when we
examine sample statistics

46. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters

47. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.

48. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
Skewed
Distributions

49. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
Skewed
Distributions

50. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.

51. `
Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
Or ranked data like
percentiles %

52. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.

53. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
1 = American
2 = Canadian

54. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
1 = American
2 = Canadian
Nominal data are
used as a way of
differentiating
groups.

55. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
1 = American
2 = Canadian
Nominal data are
used as a way of
differentiating
groups.

56. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
1 = American
2 = Canadian
Nominal data are
used as a way of
differentiating
groups.

57. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
Or

58. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
1 = Those who eat
colorful vegetables
Or

59. Non-Parametric methods are used when we
examine sample statistics as a representation of
population parameters when the distribution is
skewed or the data are ordinal / nominal.
1 = Those who eat
colorful vegetables
2 = Those who don’t
eat colorful vegetables
Or

60. A nonparametric question that deals with
relationships might look like this:

61. Determine whether the following Beatle’s album top 40
rankings is related to the albums’ sales-rankings from
1965 to 1970.

62. Determine whether the following Beatle’s album top 40
rankings is related to the albums’ sales-rankings from
1965 to 1970.
Album Top 40 & Sales Rank
Album Year Top 40
Rank
Sales
Rank
Beatles for Sale 1965 1 1
Rubber Soul 1965 2 1
Revolver 1966 3 3
Sgt. Pepper 1967 1 2
Magical Mystery Tour 1967 3 4
The Beatles (white album) 1968 6 2
Abbey Road 1969 7 3
Let it Be 1970 4 5

63. Determine whether the following Beatle’s album top 40
rankings is related to the albums’ sales-rankings from
1965 to 1970.
Album Top 40 & Sales Rank
Album Year Top 40
Rank
Sales
Rank
Beatles for Sale 1965 1 1
Rubber Soul 1965 2 1
Revolver 1966 3 3
Sgt. Pepper 1967 1 2
Magical Mystery Tour 1967 3 4
The Beatles (white album) 1968 6 2
Abbey Road 1969 7 3
Let it Be 1970 4 5
Both sets of data
are ordinal or rank
ordered

64. Determine whether the following Beatle’s album top 40
rankings is related to the albums’ sales-rankings from
1965 to 1970.
Album Top 40 & Sales Rank
Album Year Top 40
Rank
Sales
Rank
Beatles for Sale 1965 1 1
Rubber Soul 1965 2 1
Revolver 1966 3 3
Sgt. Pepper 1967 1 2
Magical Mystery Tour 1967 3 4
The Beatles (white album) 1968 6 2
Abbey Road 1969 7 3
Let it Be 1970 4 5
Both sets of data
are ordinal or rank
ordered

65. Determine whether the following Beatle’s album top 40
rankings is related to the albums’ sales-rankings from
1965 to 1970.
Because the data are ordinal
this analysis would be handled
with a nonparametric method.

66. Very Important Note –
When the data are ordinal in at least
ONE data set we will automatically use
a nonparametric test, regardless of
whether the distribution is normal or
not.regardless of whether the
distribution is normal or not.

67. Very Important Note –
When the data are ordinal in at least
ONE data set we will automatically use
a nonparametric test, regardless of
whether the distribution is normal or
not.regardless of whether the
distribution is normal or not.

68. Very Important Note –
When the data are ordinal in at least
ONE data set we will automatically use
a nonparametric test, regardless of
whether the distribution is normal or
not.

69. Here is another nonparametric-relationship
problem:

70. Do those from rural areas tend to drink more
than 8 ounces of an alcoholic beverage in one
sitting than those from urban areas?

71. Do those from rural areas tend to drink more
than 8 ounces of an alcoholic beverage in one
sitting than those from urban areas?
Where the subject
is from?
Amount of
alcohol drunken
Subject
Rural = 1
City = 2
Less than 8oz = 1
More than 8oz = 2
a 1 1
b 1 1
c 1 2
d 1 1
e 2 2
f 2 1
g 2 1
h 2 1

72. Do those from rural areas tend to drink more
than 8 ounces of an alcoholic beverage in one
sitting than those from urban areas?
Where the subject
is from?
Amount of
alcohol drunken
Subject
Rural = 1
City = 2
Less than 8oz = 1
More than 8oz = 2
a 1 1
b 1 1
c 1 2
d 1 1
e 2 2
f 2 1
g 2 1
h 2 1
Both sets of
data are
nominal
(either/or)

73. Do those from rural areas tend to drink more
than 8 ounces of an alcoholic beverage in one
sitting than those from urban areas?
Where the subject
is from?
Amount of
alcohol drunken
Subject
Rural = 1
City = 2
Less than 8oz = 1
More than 8oz = 2
a 1 1
b 1 1
c 1 2
d 1 1
e 2 2
f 2 1
g 2 1
h 2 1
Both sets of
data are
nominal
(either/or)
Because the data are nominal
this analysis would be handled
with a nonparametric method.

74. The Same Very Important Note –
When the data are nominal in at least
ONE data set we will automatically use
a nonparametric test, regardless of
whether the distribution is normal or
not.regardless of whether the
distribution is normal or not.

75. The Same Very Important Note –
When the data are nominal in at least
ONE data set we will automatically use
a nonparametric test, regardless of
whether the distribution is normal or
not.regardless of whether the
distribution is normal or not.

76. The Same Very Important Note –
When the data are nominal in at least
ONE data set we will automatically use
a nonparametric test, regardless of
whether the distribution is normal or
not.

77. In summary,

78. In summary, if and only if the data are BOTH
scaled and the distribution is normal, then you
will use a parametric method.

79. In summary, if and only if the data are BOTH
scaled and the distribution is normal, then you
will use a parametric method.
Data: Scaled
Distribution: Normal

80. In summary, if and only if the data are BOTH
scaled and the distribution is normal, then you
will use a parametric method.
Data: Scaled
Distribution: Normal
Use a
PARAMETRIC
Test

81. However, if the data are EITHER
Ordinal/Nominal or the distribution is skewed,
then you will use a NONparametric method.

82. However, if the data are EITHER
Ordinal/Nominal or the distribution is skewed,
then you will use a NONparametric method
Data: Scaled
Distribution: Normal
Data: Ordinal/Nominal
Distribution: Normal

83. However, if the data are EITHER
Ordinal/Nominal or the distribution is skewed,
then you will use a NONparametric method
Data: Scaled
Distribution: Normal
Data: Ordinal/Nominal
Distribution: Normal
Use a
NONPARAMETRIC
Test

84. However, if the data are EITHER
Ordinal/Nominal or the distribution is skewed,
then you will use a NONparametric method.
Data: Scaled
Distribution: Normal
Data: Ordinal/Nominal
Distribution: Normal
Data: Scaled
Distribution: Skewed

85. However, if the data are EITHER
Ordinal/Nominal or the distribution is skewed,
then you will use a NONparametric method.
Data: Scaled
Distribution: Normal
Data: Ordinal/Nominal
Distribution: Normal
Data: Scaled
Distribution: Skewed
Use a
NONPARAMETRIC
Test

86. However, if the data are EITHER
Ordinal/Nominal or the distribution is skewed,
then you will use a NONparametric method
Data: Scaled
Distribution: Normal
Data: Ordinal/Nominal
Distribution: Normal
Data: Scaled
Distribution: Skewed
Data: Ordinal/Nominal
Distribution: Skewed

87. However, if the data are EITHER
Ordinal/Nominal or the distribution is skewed,
then you will use a NONparametric method
Data: Scaled
Distribution: Normal
Use a
NONPARAMETRIC
Test
Data: Ordinal/Nominal
Distribution: Normal
Data: Scaled
Distribution: Skewed
Data: Ordinal/Nominal
Distribution: Skewed

88. What type of method would be most
appropriate for the data set you are
working with?

89. What type of method would be most
appropriate for the data set you are
working with?
Parametric Method
Non-Parametric Method