Complete the following for the data set:
Scatter Plot
Calculate the regression line in Y-intercept form (do this
piece by piece in Excel, or by hand)
Interpret in Words your Beta coefficient
If X=5; then your Y-hat equals what? Is this a good estimate or
not (explain in words)
Plot the regression line
Use STATA to calculate and interpret the R2
Yi
Xi
2
11
4
9
4
14
6
9
8
9
10
8
10
13
11
5
13...
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 : 772, 628, 518, 508, 496, 483,
y:...
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 x 762 621 515 508 491 480...
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
766766
620620
520520
508508
494494...
Find the equation of the regression line for the given data.
Then construct a scatter plot of the data and draw the regression
line. (Each pair of variables has a significant correlation.)
Then use the regression equation to predict the value of y for each
of the given x-values, if meaningful. The caloric content and the
sodium content (in milligrams) for 6 beef hot dogs are shown in
the table below.
font size decreased by 1 font size increased by...
Find the equation of the regression line for the given data.
Then construct a scatter plot of the data and draw the regression
line. (Each pair of variables has a significant correlation.)
Then use the regression equation to predict the value of y for each
of the given x-values, if meaningful. The caloric content and the
sodium content (in milligrams) for 6 beef hot dogs are shown in
the table below. font size decreased by 1 font size increased by...
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 number of hours 6 students
spent for a test and their scores on that test are shown below.
font size decreased by 1 font size increased by 1...
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 x 775 619 519 508 491 474...
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 number of hours 6
students spent for a test and their scores on that test are shown
below.
Hours spent studying, x: 0, 1, 2, 4, 5, 6...
find the equation of the regression line for the given
data. then construct a scatter plot if the data and draw a
regression line. then use the regression equation to predict the
value of y for each of the given x values m, if meaningful.
x= 778, 621, 519, 510, 494, 473
y= 51, 47, 44, 43, 39, 37
y=____x + _______
predict the value y for x= 499
"
" x= 642
"
" x= 802
"
" x=...