Question

The key advantage of bivariate regression over correlation is that regression can be used for prediction. Explain this period how is it that regression can be used to predict values not in the data set, but correlation cannot?

Answer #1

Explain the differences and similarities of
correlation analysis and bivariate regression analysis

Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
48
41.8
39.2
67.4
34.7
68.4
42.9
50.2
49
50.6
45.6
57
58.7
29.7
40.5
68.4
47.4
34.7
45.7
50.9
38.9
47.7
40.9
53.6
Find the correlation coefficient and report it accurate to three
decimal places.
r =
What proportion of the variation in y can be explained by
the variation in the values of x? Report answer as a
percentage...

Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
81.1
86
77.5
60.4
92.7
126.5
104
132.5
85
53.1
64.3
95.5
64.6
31.7
39.7
5.7
82.3
121.3
82.4
98.2
29.2
-50.2
34.2
-1
Find the correlation coefficient and report it accurate to three
decimal places.
r =
What proportion of the variation in y can be explained by
the variation in the values of x? Report answer as a
percentage...

Match the statistics term with its BEST
definition.
Question 2 options:
A key requirement for using correlation and regression models is
to collect this type of data.
With bivariate data, the result of MINIMIZING the sum of squared
distances between the observed and predicted values (residuals) for
a linear model.
This quantity is computed by subtracting the observed response
variable from the predicted response variable.
With bivariate data, when one variable increases a second
variable decrease implies this relationship.
A...

Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
16.1
47.3
10.6
42.8
22.4
50.6
33.3
67.6
47.8
61.1
41.4
62.1
30.2
57.9
30.6
53.6
33
57.4
9.7
41.2
19.3
49.6
Verify that the correlation is significant at an α=0.05. If the
correlation is indeed significant, predict what value (on average)
for the explanatory variable will give you a value of 54 on the
response variable.
What is the predicted...

Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
28.8
90.1
30.6
139.6
12.6
42.2
18.1
94.8
13.9
28.5
31.9
102.4
-3.9
-13.4
16.7
57.1
11
55.8
16.8
76.3
31.7
80.1
43.5
123.8
Find the correlation coefficient and report it accurate to three
decimal places.
r =
What proportion of the variation in y can be explained by
the variation in the values of x? Report answer as a
percentage...

One of your last homework problems related to a bivariate linear
regression analysis on a sample of 107 nations. It used the percent
of the adult population that was literate in a nation to predict
life expectancy for people born now in that nation. In other words,
the study investigated whether nations with higher rates of
literacy have longer (or perhaps shorter) life expectancy. The
value of R2 for the regression analysis was 0.749.
Data on the same 107 nations...

Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
31
131.5
32.7
88.1
45.9
52.1
51.8
47
65.8
30.1
58.4
36.4
84.5
-92.1
25.3
103.4
49.8
37.5
4.6
127.3
46.6
32.1
75.2
-12.4
Find the correlation coefficient and report it accurate to three
decimal places.
r =
What proportion of the variation in y can be explained by
the variation in the values of x? Report answer as a
percentage...

I need to conduct a regression and correlation analysis. Where
can I find yearly data for any economic or business variable, for a
period of at least 20 years? Suggestions?

5. A sales manager used linear regression to find the positive
linear relationship between advertising expenditures and sales. the
equation was calculated from the following data from 7 randomly
selected advertising campaigns:
Advertising Expenditures - $8,000 / $22,000 / $15,000 / $39,000
/ $32,000 / $12,000 / $45,000
Sales - $95,000 / $190,000 / $125,000 / $ 225,000 / $285,000 /
$150,000 / $350,000
If the sales manager used regression equation to predict the
amount of sales that he can...

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