Decision-Based Learning - Questions of relationship

1. Is the problem you are working on focus on
Questions of Relationship?

2. Is the problem you are working on focus on
Questions of Relationship?

3. Questions of relationship focus on how two or more
variables co-vary or co-relate with each other.

4. Or how increases or decreases in one variable are
accompanied by increases or decreases in another
variable.

5. Here is an equation to use as a guide

6. Here is an equation to use as a guide
An Increase
or decrease in

7. Here is an equation to use as a guide
Variable 1
An Increase
or decrease in

8. Here is an equation to use as a guide
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in

9. Here is an equation to use as a guide
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

10. Variable 1
An Increase
or decrease in
By variable we mean
something that varies or
changes, like temperature,
speed, weight, test scores,
is accompanied
by an increase
or decrease in
Variable 2
etc.

11. Let’s see an example:

12. Researchers hypothesize that as the
temperature increases burglaries increase.

13. Researchers hypothesize that as the
temperature increases burglaries increase.

14. Researchers hypothesize that as the
temperature increases burglaries increase.
as

15. Researchers hypothesize that as the
temperature increases burglaries increase.
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

16. Researchers hypothesize that as the
temperature increases burglaries increase.
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

17. Researchers hypothesize that as the
temperature increases burglaries increase.
Temperature
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

18. Researchers hypothesize that as the
temperature increases burglaries increase.
Temperature
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

19. Researchers hypothesize that as the
temperature increases burglaries increase.
Temperature
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Burglaries

20. Researchers hypothesize that as the
temperature increases burglaries increase. Test
this hypothesis with the data set provided.
Therefore, this is a question of
Temperature
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Burglaries
Relationship

21. Let’s see what the data might look like for
this word problem:

22. Let’s see what the data might look like for
this word problem:
Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o 100

23. Let’s see what the data might look like for
this word problem:
Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o 100

24. Let’s see what the data might look like for
this word problem:
Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o 100

25. Let’s see what the data might look like for
this word problem:
Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o 100

26. What do we mean when we say that a
relationship exists between two variables – in
this case – temperature and burglaries?
Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o 100

27. What we mean is that the two variables vary
(increase or decrease) in either the same or
opposite directions.
Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o 100

28. A simple way to illustrate this idea of covary-ing is
to see the relative rank of the values of one
variable and see if those ranks are similar to the
relative rank of the values of the other variable
Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o 100

29. Let’s begin by rank ordering the average
temperature values.
Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o 100

30. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul 90o This is the 1h0ig0h est value so we’ll give it a #1 Rank

31. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul #1 90o 100

32. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun 80o 80
Jul #1 90o 100
This is the 2nd highest value so we’ll give it a #2 Rank

33. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun #2
80o 80
Jul #1 90o 100

34. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun #2
80o 80
Jul #1 90o 100
This is the 3rd highest value so we’ll give it a #3 Rank

35. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100

36. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr 60o 40
May 70o 60
Jun #2
80o 80
Jul #1 90o 100
This is the 4th highest value so we’ll give it a #4 Rank
#3

37. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100

38. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100
This is the 7th highest value so we’ll give it a #7 Rank

39. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100

40. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb 40o 25
Mar 20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100
This is the 5th highest value so we’ll give it a #5 Rank
#7

41. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100

42. Month Average
Temperature
Number of
Burglaries
Jan 30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100
This is the 6th highest value so we’ll give it a #6 Rank

43. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100

44. Now, let’s do the same for the number of
burglaries:
Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100

45. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o 100
This is the highest
value so we’ll give it a
#1 Rank

46. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o #1
100

47. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o 80
Jul #1 90o #1
100
This is the 2nd highest
value so we’ll give it a
#2 Rank

48. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o #2
80
Jul #1 90o #1
100

49. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o #2
80
Jul #1 90o #1
100
This is the 3rd highest
value so we’ll give it a
#3 Rank

50. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

51. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o 40
May #3
70o 60
Jun #2
80o #2
80
Jul #1 90o #1
100
This is the 4th highest
value so we’ll give it a
#4 Rank #3

52. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

53. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o 5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100
This is the 7th highest
value so we’ll give it a
#7 Rank

54. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

55. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o 25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100
This is the 5th highest
value so we’ll give it a
#5 Rank

56. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

57. Month Average
Temperature
Number of
Burglaries
Jan #6
30o 10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100
This is the 6th highest
value so we’ll give it a
#6 Rank

58. Month Average
Temperature
Number of
Burglaries
Jan #6
30o #6
10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

59. Notice that the relative rank order for
temperature and burglaries across each month
Month Average
Temperature
is the SAME.
Number of
Burglaries
Jan #6
30o #6
10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

60. The highest rank on one is the highest rank
Month Average
order on the other.
Temperature
Number of
Burglaries
Jan #6
30o #6
10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

61. The highest rank on one is the highest rank
Month Average
order on the other.
Temperature
Number of
Burglaries
Jan #6
30o #6
10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

62. The 2nd highest rank on one is the 2nd highest
rank order on the other.
Month Average
Temperature
Number of
Burglaries
Jan #6
30o #6
10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

63. Month Average
Temperature
Ect. Ect. Ect.
Number of
Burglaries
Jan #6
30o #6
10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

64. This is a way of visualizing how an increase in
one is accompanied by an increase in another.
Month Average
Temperature
Number of
Burglaries
Jan #6
30o #6
10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

65. What would an increase in one variable and an
decrease in another variable look like?

66. What would an increase in one variable and an
decrease in another variable look like?
Month Average
Temperature
Number of
Burglaries
Jan #6
30o #6
10
Feb #5
40o #5
25
Mar #7
20o #7
5
Apr #4
60o #4
40
May #3
70o #3
60
Jun #2
80o #2
80
Jul #1 90o #1
100

67. What would an increase in one variable and an
decrease in another variable look like?
#6 #1
#5
#7
#4
#3
#2
#1
#2
#3
#4
#7
#5
#6
Month Average
Temperature
Number of
Burglaries
Jan 30o 100
Feb 40o 80
Mar 20o 60
Apr 60o 40
May 70o 5
Jun 80o 25
Jul 90o 10

68. What would an increase in one variable and an
decrease in another variable look like?
Month Average
Temperature
Number of
Burglaries
Jan #6 30o #1
100
Feb #5
40o #2
80
Mar #7
20o #3
60
Apr #4
60o #4
40
May #3
70o #7
5
Jun #2
80o #5
25
Jul #1 90o #6
10

69. Notice that in this case, as temperature increases
burglaries decrease.
Month Average
Temperature
Number of
Burglaries
Jan #6 30o #1
100
Feb #5
40o #2
80
Mar #7
20o #3
60
Apr #4
60o #4
40
May #3
70o #7
5
Jun #2
80o #5
25
Jul #1 90o #6
10

70. Let’s consider other word problems

71. An ice cream parlor owner wishes to know the
degree to which ice cream sales are related to
average monthly temperature.

72. An ice cream parlor owner wishes to know the
degree to which ice cream sales are related to
average monthly temperature.

73. An ice cream parlor owner wishes to know the
degree to which ice cream sales are related to
average monthly temperature.
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

74. An ice cream parlor owner wishes to know the
degree to which ice cream sales are related to
average monthly temperature.
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

75. An ice cream parlor owner wishes to know the
degree to which ice cream sales are related to
average monthly temperature.
Ice cream
sales
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

76. An ice cream parlor owner wishes to know the
degree to which ice cream sales are related to
average monthly temperature.
Ice cream
sales
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

77. An ice cream parlor owner wishes to know the
degree to which ice cream sales are related to
average monthly temperature.
Ice cream
sales
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

78. An ice cream parlor owner wishes to know the
degree to which ice cream sales are related to
average monthly temperature.
Ice cream
sales
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Temperature

79. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight

80. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight

81. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight

82. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight
E.g., a jet can fly as slow as 0 mph and as fast as 700
mph. It’s speed can take on any number of values
in between 0 and 700 (e.g., 2.8 mph or 345.6 mph )

83. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight
E.g., A person can be as young as
zero or as old as 100+
(e.g., 6.32 years or 98.9 years)

84. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight
with variables that can take on limited values
like gender, year in school or whether a person
has experienced something or not.

85. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight
with variables that can take on limited values
like gender, year in school or whether a person
has experienced something or not.
E.g., with gender, male can take on a value of 1
and female a value of 2.

86. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight
with variables that can take on limited values
like gender, year in school or whether a person
has experienced something or not.
or

87. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight
with variables that can take on limited values
like gender, year in school or whether a person
has experienced something or not.
female can take on a value of 1 and
male a value of 2.

88. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight
with variables that can take on limited values
like gender, year in school or whether a person
has experienced something or not.
Year in school can take on a value of
1 for freshmen, 2 for sophomore, 3 for junior
and 4 for senior.

89. Some word problems will look for a relationship
between variables that can take on unlimited
values like speed, age, height or weight
with variables that can take on limited values
like gender, year in school or whether a person
has experienced something or not.
Experience can mean I experienced it = 1 or I did
not experience it = 2 (e.g., exposed to gamma
rays or not exposed to gamma rays)

90. Let’s see an example of this,

91. Researchers wish to know if there is a
relationship between the average freeway
driving speed and gender.

92. In this case the wording of our relationship
equation will change from

93. In this case the wording of our relationship
equation will change from
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

94. In this case the wording of our relationship
equation will change from
to
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

95. In this case the wording of our relationship
equation will change from
to
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2
Variable 1
Higher and
lower scores
in
tend to be
related to
certain groups in
Variable 2

96. In this case the wording of our relationship
equation will change from
to
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Because variables like
Gender can neither
increase nor decrease
Variable 2
Variable 1
Higher and
lower scores
in
tend to be
related to
certain groups in
Variable 2

97. Let’s see how this works in our word problem
about gender and freeway speed.

98. Researchers wish to know if there is a
relationship between the average freeway
driving speed and gender.

99. Researchers wish to know if there is a
relationship between the average freeway
driving speed and gender.
Variable 1
Higher and
lower scores
in
tend to be
related to
certain groups in
Variable 2

100. Researchers wish to know if there is a
relationship between the average freeway
driving speed and gender.
Variable 1
Higher and
lower scores
in
tend to be
related to
certain groups in
Variable 2

101. Researchers wish to know if there is a
relationship between the average freeway
driving speed and gender.
Freeway
Driving
Speed
Higher and
lower scores
in
tend to be
related to
certain groups in
Variable 2

102. Researchers wish to know if there is a
relationship between the average freeway
driving speed and gender.
Freeway
Driving
Speed
Higher and
lower scores
in
tend to be
related to
certain groups in
Variable 2

103. Researchers wish to know if there is a
relationship between the average freeway
driving speed and gender.
Freeway
Driving
Speed
Higher and
lower scores
in
tend to be
related to
certain groups in
Gender

104. Here is what the data set would look like:

105. Here is what the data set would look like:
Driver
Mary
Bill
Sarah
Mike
Sally
Charles
Fred

106. Here is what the data set would look like:
Driver Average Freeway
Speed (mph)
Mary 66
Bill 73
Sarah 56
Mike 82
Sally 62
Charles 78
Fred 91

107. Here is what the data set would look like:
Driver Average Freeway
Speed (mph)
Gender
1= male
2 = female
Mary 66 2
Bill 73 1
Sarah 56 2
Mike 82 1
Sally 62 2
Charles 78 1
Fred 91 1

108. Driver Average Freeway
Speed (mph)
Gender
1= male
2 = female
Mary 66 2
Bill 73 1
Sarah 56 2
Mike 82 1
Sally 62 2
Charles 78 1
Fred 91 1
So, are higher
speeds associated
with one gender
and are lower
speeds associated
with the other
gender?

109. Driver Average Freeway
Speed (mph)
Gender
1= male
2 = female
Mary 66 2
Bill 73 1
Sarah 56 2
Mike 82 1
Sally 62 2
Charles 78 1
Fred 91 1
It appears that the
number 2s (female)
have lower average
driving speeds than

110. Driver Average Freeway
Speed (mph)
Gender
1= male
2 = female
Mary 66 2
Bill 73 1
Sarah 56 2
Mike 82 1
Sally 62 2
Charles 78 1
Fred 91 1
. . . the number 1s
(male)

111. Driver Average Freeway
Speed (mph)
Gender
1= male
2 = female
Mary 66 2
Bill 73 1
Sarah 56 2
Mike 82 1
Sally 62 2
Charles 78 1
Fred 91 1
Notice that
this could
sound like a
difference
question.

112. Let’s see an example of this:

113. Difference question:

114. Difference question: Are women faster freeway
drivers than men?

115. Difference question: Are women faster freeway
drivers than men?
Same question expressed as a relationship:

116. Difference question: Are women faster freeway
drivers than men?
Same question expressed as a relationship:
Does a relationship exist between freeway
speed and gender?

117. Difference question: Are women faster freeway
drivers than men?
Same question expressed as a relationship:
Does a relationship exist between freeway
speed and gender?
Depending on how the question is asked it will
either be a difference or a relationship question.

118. Some relationship questions focus on how well
one or two variables predict another variable.

119. For example,

120. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.

121. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

122. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

123. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.
ACT Scores
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

124. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.
ACT Scores
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

125. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.
ACT Scores
An Increase
or decrease in
predict Variable 2

126. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.
ACT Scores
An Increase
or decrease in
predict Variable 2

127. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.
ACT Scores
An Increase
or decrease in
predict
Writing
Course
Grades

128. To what degree do ACT scores predict college
freshmen grades in a introduction to writing
course.
ACT Scores
An Increase
or decrease in
predict
Writing
Course
Grades
Prediction Questions are classified as
Questions of Relationship

129. In Summary

130. Relationship questions ask about the degree to
which a change (increase/decrease) in one
variable is accompanied by a change
(increase/decrease) in another variable.

131. Relationship questions ask about the degree to
which a change (increase/decrease) in one
variable is accompanied by a change
(increase/decrease) in another variable.
Variable 1
An Increase
or decrease in
is accompanied
by an increase
or decrease in
Variable 2

132. Relationship questions can be between variables
that take on unlimited values (e.g, age and
weight, or age and weight),

133. Relationship questions can be between variables
that take on unlimited values (e.g, age and
weight, or age and weight),
Or between variables with limited values (e.g.,
gender and year in school)

134. Relationship questions can be between variables
that take on unlimited values (e.g, age and
weight, or age and weight),
Or between variables with limited values (e.g.,
gender and year in school)
Variable 1
Higher and
lower scores
in
tend to be
related to
certain groups in
Variable 2

135. Finally, relationship questions can focus on the
degree to which one variable predicts another
variable.

136. Finally, relationship questions can focus on the
degree to which one variable predicts another
variable.
Variable 1
An Increase
or decrease in
Predicts Variable 2

137. Some of the words to look for in your problem to
determine if it is a question of relationship are:

138. Some of the words to look for in your problem to
determine if it is a question of relationship are:
• Increase
• Decrease
• Association
• Are associated with
• Relationship
• Relate to
• Predict
• Predictive Power

139. Some of the words to look for in your problem to
determine if it is a question of relationship are:
• Increase
• Decrease
• Association
• Are associated with
• Relationship
• Relate to
• Predict
• Predictive Power

140. Examine the question or problem you are
working on.

141. Is it a question of relationship?

142. If so, select RELATIONSHIP