Question

5) |
If two variables (x and y) have a very strong linear relationship, it can be inferred that |
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Answer #1

**(e) None of the
above**

This question is related to one of the disadvantages of correlational statistical tests. One of the important consequence of correlation is that it does not imply causation. According to the question, there is a strong linear relationship between the variables and this implies that there is a strong correlation. However, this does not imply that there is going to be a causal relationship between the variables.

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A) Two variables have a high covariance. This means the two
variables have a strong relationship. T/F
B) For a variable x, the sample mean is 8 and the sample
standard deviation is 2. One of the observations is 15. Is this
observation an outlier?
Group of answer choices
Yes, the z-score is greater than 3
No, the z-score is between -3 and 3
Yes, the z-score is between -3 and 3
No, the z-score is less than -3
C)...

Correlation and regression are concerned with:
a. the relationship between two
qualitative variables
b. the relationship between two
quantitative variables
c. the relationship between a
qualitative and quantitative variable
d. none of the above
e. all of the above

One of the major misconceptions about correlation is that a
relationship between two variables means causation; that is, one
variable causes changes in the other variable. There is a
particular tendency to make this causal error, when the two
variables seem to be related to each other.
What is one instance where you have seen correlation
misinterpreted as causation? Please describe
Can you help me understand how to answer this question

prior to run a regression a least squares line for variables x
and y indicates the slope is 4 units at this point we can
conclude
variable x causes variable y to change
there is a positive relaationship between variables x and y
there may be a relationship between variables x and y
there is no relationship between variables x and y
x-n(100.3. P9x> 96) =
90.9 %
9.1%
80.2%
19.8%

Using the data given below, calculate the linear correlation
between the two variables x and y.
X
0
3
3
1
4
y
1
7
2
5
5
(a)
.794
(b)
.878
(c)
.497
(d) .543
Refer to question 4. Assume you are using a 0.05 level of
significance; is there a
significant
relationship between the two variables x and y?
Yes
(b) no
The heights (in inches) and pulse rates (in beats per minutes)
for a sample of 40...

Consider the following sample data for two variables. x = 16,
6,4,2 and Y= 5,11,6,8 a. Calculate the sample covariance
Sxy= b. Calculate the sample correlation coefficient
rxy= c. Describe the relationship between x and y. Choose the
correct answer below. A. There is a positive linear relationship
between x and y. B. There is no linear relationship between x and
y. C. There is a perfect negative linear relationship between x and
y. D. There is a perfect positive linear...

One of the major misconceptions about correlation is that a
relationship between two variables means causation; that is, one
variable causes changes in the other variable. There is a
particular tendency to make this causal error, when the two
variables seem to be related to each other.
What is one instance where you have seen correlation
misinterpreted as causation? Please describe.
an orginal post please

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...

Suppose the correlation coefficient between two variables is
found to be 0.83. Which of the following statements are true?
small values of one variable are associated with large values of
the other variable
the relationship between the variables is weak
a scatter plot of the points would show an upward trend
low values of one variable tend to be paired with low values of
the other variable
there is a strong positive curvilinear relationship between the
variables
there is a...

True or False: Assuming a linear relationship between X and Y,
if the coefficient of correlation (r) equals 0.50, this means that
50% of the variation in the dependent variable (Y) is due to
changes in the independent variable (X).

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