Question

The equation for a straight line between two variables, xx and yy, is y=mx+by=mx+b. In this equation, mm is the slope of the line and bb is the yy-intercept (the point at which the straight line crosses the yy-axis). When m<0m<0, the line has a negative slope. When m>0m>0, the line has a positive slope.

The correlation coefficient, rr, can be used to calculate the values of mm and bb in a linear regression.

First, use the values you have already calculated to calculate mm in this equation: m=rsysxm=rsysx. Enter your answer to the nearest whole number. (sysy and sxsx are the standard deviations of variables xx and yy.)

Answer #1

**Solution:**

The strength of the relationship between two quantitative
variables can be measured by
the y-intercept of the simple linear regression
equation.
the slope of a simple linear regression equation.
both the coefficient of correlation and the coefficient of
determination.
the coefficient of determination.
the coefficient of correlation.

Consider the line with non-zero slope m and y-intercept b,
that is the line described by the equation y = mx + b where m is
not equal to 0. Use dot products of vectors to show that any line
perpendicular to this one must have a slope of -1/m. Also show that
in the case where m=0, any perpendicular line must be vertical (and
hence have undefined slope).

Find the equation of the tangent line y=mx+b
y=e2x+2x at x=0
m=???
n=???

Number of customers in millions
Energy Consumption in GWh
1.363138
22416
1.389033
23138
1.417664
24042
1.448548
24795
1.480294
25845
Using the linear regression equation make a prediction what the
Gigawatt hours will be equal to when the number of customers reach
ten (10) million.
Linear regression equation:
Where,
x and y are the variables
b = The slope of the regression line
a = The intercept point of the regression line and the y
axis.
N = Number of values...

1) In the regression equation, y = 2.164 + 1.3657x, n = 6, the
mean of x is 8.667, SSxx = 89.333 and Se =
3.44. A 95% confidence interval for the average of y when x = 8 is
_________.
2)If the correlation coefficient between variables X
and Y is roughly zero, then ______.
3) Determine the Pearson product-moment correlation coefficient
for the following data.
x
1
11
9
6
5
3
2
y
10
4
4
5
7...

The regression line can never be used for prediction. True
False
The slope is the amount Y changes for every increase in X. True
False
"When you calculate a regression equation, you want the line
with the most error. " True False
"Correlation measures the linear relationship between two
variables, while a regression analysis precisely defines this line.
" True False
The predicted value based on a regression equation is a perfect
prediction. True False
What represents the intercept (the...

Linear Regression and Correlation.
x
y
3
-3.26
4
2.72
5
1.2
6
1.88
7
0.16
8
-5.66
9
3.02
10
-6.7
11
-3.92
12
-5.34
Compute the equation of the linear regression line in the form y =
mx + b, where m is the slope and b is the intercept.
Use at least 3 decimal places.
y = x +
Compute the correlation coeficient for this data set. Use at least
3 decimal places.
r=
Compute the P-value...

Linear Regression and Correlation.
x
y
3
-10.52
4
1.94
5
-2.7
6
-3.14
7
-9.18
8
-4.82
9
-12.26
10
-11.1
11
-6.44
Compute the equation of the linear regression line in the form y =
mx + b, where m is the slope and b is the intercept.
Use at least 3 decimal places. (Round if necessary)
y = x +
Compute the correlation coeficient for this data set. Use at least
3 decimal places. (Round if necessary)...

Given are five observations for two variables, x and
y.
xi
1
2
3
4
5
yi
4
6
6
11
15
Which of the following scatter diagrams accurately represents
the data?
1.
2.
3.
What does the scatter diagram indicate about the relationship
between the two variables?
Develop the estimated regression equation by computing the the
slope and the y intercept of the estimated regression line
(to 1 decimal).
ŷ = + x
Use the estimated regression equation to...

Find the equation of the regression line for the given data.
Then construct a scatter plot of the data and draw the regression
line. (The pair of variables have a significant correlation.)
Then use the regression equation to predict the value of y for each
of the given x-values, if meaningful. The table below shows the
heights (in feet) and the number of stories of six notable
buildings in a city.
Height comma xHeight, x
774774
625625
521521
508508
497497...

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