Question

correlation measures the degree to which two variables are related to one another.

Here are the definitions of the three possibilities:

**Positive correlations:**In this type of correlation, both variables increase or decrease at the same time. A correlation coefficient close to +1.00 indicates a strong positive correlation.**Negative correlations:**This type of correlation indicates that as the amount of one variable increases, the other decreases (and vice versa). A correlation coefficient close to -1.00 indicates a strong negative correlation.**No correlation:**This indicates no relationship between the two variables. A correlation coefficient of 0 indicates no correlation.

Values range from -1 to 1. The closer to -1 or 1 the stronger the correlation. The closer to 0 the weaker it is. Correlation is a term that refers to the strength of a relationship between two variables where a strong, or high, correlation means that two or more variables have a strong relationship with each other while a weak or low correlation means that the variables are hardly related. Correlation analysis is the process of studying the strength of that relationship with available statistical data.

Example: A recent study of marriage and education found a strong negative correlation between the level of education and the divorce rate. Data from the National Survey of Family Growth show that as education level increases among women, the divorce rate for first marriages decreases.

. **Decker (1987) found that a supervisor's perceived
sense of humor was positively correlated with people's job
satisfaction. So what does this show?**

Answer #1

Solution:

**Decker (1987) found that a supervisor's perceived sense
of humor was positively correlated with people's job
satisfaction. This shows that a supervisor's perceived sense of
humor and people's job satisfaction increases or decreases at the
same time. In other words if a supervisor's perceived sense of
humor increases then the people's job satisfaction will also
increase. If a supervisor's perceived sense of humor decreases then
the people's job satisfaction will also decrease.**

**Please rate the answer. Thank you.**

A Correlation Coefficient is a measurement of
the relationship between two variables. A positive correlation
means that as one variable increases, the second variable increases
too. A negative correlation means that as one variable increases,
the second variable decreases, or as one variable decreases, the
second variable increases. Positive and negative correlations
exists in nature, science, business, as well as a variety of other
fields. Please watch the following video for a graphical
explanation of the correlation coefficient:
For Discussion...

A coefficient of correlation of -0.9 indicates the relationship
between the two variables is
(a) weak and negative
(b) strong and positive
(c) strong and negative

1. Name two ways in which two variables could be related. Select
the two most correct answers. Choose the correct answer below.
A) Strong and moderate B) Moderate and negative C) Weak and
moderate D) strong and weak
2. Name a graph that can be used to quickly illustrate the
relationship between two variables? Choose the correct answer
below.
A) Histogram B) Regression line C) Scatter plot D) Time series
graph.
3. What do we mean by the strength of...

Which statement explains why correlation could be 0 even if a
strong relationship between two variables existed?
Group of answer choices
Since the correlation is 0, there is no strong relationship
between the two variables; and a scatterplot would be
misleading.
Correlation can be 0 even if there is a strong linear
relationship between the variables.
Correlation only measures the strength of the relationship
between two variables when the units of the two variables are the
same.
Correlation does not...

Pick any two variables that you feel may be related and estimate
what you think the strength of the correlation coefficient would be
for those two variables. In your response, estimate the value of r.
For example, specify a strong (.7 to .9), medium (.4 to .6), or low
(0 to .3) value for r. The value of the coefficient can be positive
or negative. For example, consider an increase in police patrols in
a neighborhood and the number of...

Pick any two variables that you feel may be related and estimate
what you think the strength of the correlation coefficient would be
for those two variables. In your response, estimate the value of r.
For example, specify a strong (.7 to .9), medium (.4 to .6), or low
(0 to .3) value for r. The value of the coefficient can be positive
or negative. For example, consider an increase in police patrols in
a neighborhood and the number of...

Pick any two variables that you feel may be related and estimate
what you think the strength of the correlation coefficient would be
for those two variables. In your response, estimate the value of r.
For example, specify a strong (.7 to .9), medium (.4 to .6), or low
(0 to .3) value for r. The value of the coefficient can be positive
or negative. For example, consider an increase in police patrols in
a neighborhood and the number of...

5) As the total amount of squared error of prediction increases,
the correlation between the two variables:
also increases.
decreases.
becomes equal.
equals one.
6) If the slope (b) of the regression line equals zero, this
indicates:
the correlation between the two variables is negative.
a perfect relationship between the two variables.
a correlation of +1.0.
the regression line is horizontal.

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