Correlation (a) Positive linear relationship (b) Negative linear relationship 2oin (c) Curvilinear relationship (d) No relationship

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FIGURE 10-1
Tpes of Relationships
Section 10-1 Correlation
541
(a) Positive linear relationship
(b) Negative linear relationship
betio inomeo t
•• ech
(c) Curvilinear relationship
(d) No relationship
pressure, the researcher can generally assume that age affects blood pressure. Hence, the
variable age can be called the independent variable, and the variable blood pressure can be
called the dependent variable. On the other hand, if a researcher is studying the attitudes of
husbands on a certain issue and the attitudes of their wives on the same issue, it is difficult
to say which variable is the independent variable and which is the dependent variable. In this
study, the researcher can arbitrarily designate the variables as independent and dependent.
The independent and dependent variables can be plotted on a graph called a scatter
plot. The independent variable x is plotted on the horizontal axis, and the dependent vari-
abie pletted on the vertical axis.
da dgng sdt no nioq dono sol9
A scatter plot is a graph of the ordered pairs (x, y) of numbers consisting of the
independent variable x and the dependent variable y.
The scatter plot is a visual way to describe the nature of the relationship between the
independent and dependent variables. The scales of the variables can be different, and
the coordinates of the axes are determined by the smallest and largest data values of the
variables.
Researchers look for various types of patterns in scatter plots. For example, in Fig-
ure 10–1(a), the pattern in the points of the scatter plot shows a positive linear relation-
ship, Here, as the values of the independent variable (x variable) increase, the values of
the dependent variable (y variable) increase. Also, the points form somewhat of a straight
line going in an upward direction from left to right.
The pattern of the points of the scatter plot shown in Figure 10–1(b) shows a negative
linear relationship. In this case, as the values of the independent variable increase, the
values of the dependent variable decrease. Also, the points show a somewhat straight line
going in a downward direction from left to right.
The pattern of the points of the scatter plot shown in Figure 10–1(c) shows some type
of a nonlinear relationship or a curvilinear relationship.
Finally, the scatter plot shown in Figure 10-1(d) shows basically no relationshin
between the independent variable and the dependent variable since no pattern (line or
curve) can be seen.
10-3
Transcribed Image Text:FIGURE 10-1 Tpes of Relationships Section 10-1 Correlation 541 (a) Positive linear relationship (b) Negative linear relationship betio inomeo t •• ech (c) Curvilinear relationship (d) No relationship pressure, the researcher can generally assume that age affects blood pressure. Hence, the variable age can be called the independent variable, and the variable blood pressure can be called the dependent variable. On the other hand, if a researcher is studying the attitudes of husbands on a certain issue and the attitudes of their wives on the same issue, it is difficult to say which variable is the independent variable and which is the dependent variable. In this study, the researcher can arbitrarily designate the variables as independent and dependent. The independent and dependent variables can be plotted on a graph called a scatter plot. The independent variable x is plotted on the horizontal axis, and the dependent vari- abie pletted on the vertical axis. da dgng sdt no nioq dono sol9 A scatter plot is a graph of the ordered pairs (x, y) of numbers consisting of the independent variable x and the dependent variable y. The scatter plot is a visual way to describe the nature of the relationship between the independent and dependent variables. The scales of the variables can be different, and the coordinates of the axes are determined by the smallest and largest data values of the variables. Researchers look for various types of patterns in scatter plots. For example, in Fig- ure 10–1(a), the pattern in the points of the scatter plot shows a positive linear relation- ship, Here, as the values of the independent variable (x variable) increase, the values of the dependent variable (y variable) increase. Also, the points form somewhat of a straight line going in an upward direction from left to right. The pattern of the points of the scatter plot shown in Figure 10–1(b) shows a negative linear relationship. In this case, as the values of the independent variable increase, the values of the dependent variable decrease. Also, the points show a somewhat straight line going in a downward direction from left to right. The pattern of the points of the scatter plot shown in Figure 10–1(c) shows some type of a nonlinear relationship or a curvilinear relationship. Finally, the scatter plot shown in Figure 10-1(d) shows basically no relationshin between the independent variable and the dependent variable since no pattern (line or curve) can be seen. 10-3
What seems to be true about the figures at the top of the
page ?
Page 541
а.
When there is no relationship, the points are
widely scattered
b.
The pattern of the points can slope from left to
right and from right to left
Neither statement is true
C.
d.
Both are true
Transcribed Image Text:What seems to be true about the figures at the top of the page ? Page 541 а. When there is no relationship, the points are widely scattered b. The pattern of the points can slope from left to right and from right to left Neither statement is true C. d. Both are true
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