Question

find an ** econometrical** solution of this
problem using the linear regression model

There are data on average output per worker y (thousand dollars) and turnover x (thousand dollars) in 10 stores for the quarter. Based on the above data, it is required:

1) determine the dependence (correlation coefficient) of average output per worker on turnover,

2) make a direct regression equation for this dependence.

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |

x | 10 | 14 | 21 | 23 | 32 | 39 | 45 | 55 | 61 | 68 |

y | 3,8 | 4,8 | 5,9 | 6,1 | 6,3 | 6,6 | 7,4 | 8,5 | 9,7 | 12,4 |

Answer #1

Using a calculator or statistical software, find the linear
regression line for the data in the table below.
Enter your answer in the form y=mx+b, with m and b both rounded
to two decimal places.
x
y
3
6.17
4
5.77
5
4.97
6
7.21
7
5.89
8
9.74
9
9.3
10
8
11
8.88
Provide your answer below:

61. The following data
is to be used to construct a regression model:
x
5
7
4
15
12
9
y
8
9
10
22
16
12
The value of SSR is
____________.
124.986
121.116
118.182
112.157
110.136

Find the linear regression line for the following table of
values, where x represents the number of work site accidents and y
represents the average percentage of employee turnover. You will
need to use a calculator, spreadsheet, or statistical software.
Round your final answers to two decimal places.
x
1
2
3
4
5
6
y
7.97
7.85
11.3
10
12.58
15.41

Find regression line for the data
X 0 1 2 3
4 5 6 7
8
Y 11 21 31 41 51 61 71 81 91
X 0 2 4 6 8
10
Y 12 15 17 18 20 22

Let us instead fit a linear regression model to the data on
employee sales. in particular, we fit the model: sales = b0 +
b1*employee group + e, where employee group is a categorical
variable with values a, b, and c. we set group a to be the
reference category. from this model we get the following
output. from this output,
1. what can we conclude is the mean sales for group a (in
dollars/day)?
2.what can you conclude is the...

Find the required linear model using least-squares
regression.
The table below gives the total sales (in billions of dollars)
for the aerospace industry.
Year
2006
2007
2008
2009
2010
2011
Total Sales
184.4184.4
186.7186.7
188.3188.3
189.5189.5
190.5190.5
191.3191.3
(a) Find a linear model for the data with x=6
corresponding to the year 2006.
(b) Assuming the trend continues, estimate
the total sales for the year 2015.
(a) The linear model for the data is
yequals=nothing xplus+nothing .

Run a regression analysis on the following data set, where yis
the final grade in a math class and xis the average number of hours
the student spent working on math each week.
hours/week
x
Grade
y
5
53
5
50
8
60.2
9
60.6
9
68.6
10
68
11
64.4
11
71.4
20
100
20
100
State the regression equation y=m⋅x+b, with constants accurate to
two decimal places.
What is the predicted value for the final grade when a...

An analyst is running a regression model using the following
data:
Y
x1
x2
x3
x4
x5
x6
4
1
5
0
-95
17
12
10
5
8
1
-27
7
10
32
1
7
0
-82
0
9
2
2
7
0
17
5
10
9
3
9
1
-46
5
11
Excel performs the regression analysis, but the output looks all
messed up: For example the F statistic cannot be computed, standard
errors are all zero, etc etc....

The following table shows data for the cost of natural gas in
Maryland (in dollars per thousand cubic feet) for each month of the
year 2018.
Month Price in $ per Million Btu
1 8.38
2 7.99
3 7.73
4 8.20
5 8.73
6 8.99
7 9.25
8 9.30
9 10.65
10 8.19
11 8.69
12 9.69
Define the explanatory and response variables for this
problem.
Use the calculator to obtain the linear regression line
of best fit line; round...

22. We fit a simple linear regression model using price (in
dollars) to predict the number of packets of dog biscuits sold per
day. The regression equation is y = 98.1 - 9.8x, and R2 =
0.5275.
Explain how to interpret the R2 in the context of this problem.:
*
(A) 52.75% of the variation in the price is explained by the number
of packets of dog biscuits sold per day.
(B) 52.75% of the variation in the number of...

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