Question
In: Math
The accompanying data file contains 20 observations for t and yt. t y 1 10.32 2...
The accompanying data file contains 20 observations for t and yt.
| t | y |
| 1 | 10.32 |
| 2 | 12.25 |
| 3 | 12.31 |
| 4 | 13 |
| 5 | 13.15 |
| 6 | 13.84 |
| 7 | 14.39 |
| 8 | 14.4 |
| 9 | 15.05 |
| 10 | 14.99 |
| 11 | 16.95 |
| 12 | 16.18 |
| 13 | 17.22 |
| 14 | 16.71 |
| 15 | 16.64 |
| 16 | 16.26 |
| 17 | 16.77 |
| 18 | 17.1 |
| 19 | 16.91 |
| 20 | 16.79 |
b-1. Estimate a linear trend model and a quadratic trend model. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.)
b-2. Which trend model describes the data
well?
-
Linear trend based on the R2 measure.
-
Linear trend based on the adjusted R2 measure.
-
Quadratic trend based on the R2 measure.
-
Quadratic trend based on the adjusted R-squared and P-value for the quadratic term
Solutions
Expert Solution
From the given problem
The accompanying data file contains 20 observations for t and yt.
b-1. From the problem is estimate a linear trend model and a quadratic trend model. (Negitive values should be indicated by a minus sign. Round answer to 2 decimal places.)
b-2. Which trend model describes the data well. Linear trend based on the R2 measure. Linear trend based on the adjusted R2 measure. Quadratic trend based on the R2 measure. Quadratic based on the adjusted R-squared and P-value for the quadratic term.
milcah answered 2 months agoRelated Solutions
The accompanying data file contains 20 observations for t and yt.
The accompanying data file contains 20 observations for t and
yt.
t
1
2
3
4
5
6
7
8
9
10
yt
12.1
12.2
9.3
12.8
8.6
9.3
14.3
12.1
11.5
15.1
t
11
12
13
14
15
16
17
18
19
20
yt
13.5
9.8
9.6
14.5
14.9
12.4
11.2
8.8
11.8
10
a. Discuss the presence of random
variations.
The smoother appearance of the graph suggests the presence of
random variations.
The smoother appearance of the graph...
The accompanying data file contains 20 observations for t and yt. t 1 2 3 4...
The accompanying data file contains 20 observations for
t and yt.
t
1
2
3
4
5
6
7
8
9
10
yt
13.7
8.9
10.4
9.3
12.1
13.7
11.9
13.9
13.8
13.5
t
11
12
13
14
15
16
17
18
19
20
yt
10.8
10.6
12.3
9.3
11.2
10
10.5
13.7
10.3
10.7
The data are plotted below.
a. Discuss the presence of random variations.
A. The smoother appearance of the graph suggests the presence of
random variations....
The accompanying data file contains 20 observations for t and yt. The data are plotted below....
The accompanying data file contains 20 observations for
t and yt.
The data are plotted below.
t
1
2
3
4
5
6
7
8
9
10
yt
10.8
14.1
10.3
10.9
11.3
13.5
10.7
9.2
8.8
12
t
11
12
13
14
15
16
17
18
19
20
yt
9.8
11
15.1
12.5
12.9
12.3
9
14.9
10.1
11.9
b-1. Use the exponential smoothing method to make
forecasts with α = 0.2. (Round intermediate
calculations to at least 4...
The accompanying data file contains monthly observations for 5 years. a. Calculate the 12-month centered moving...
The accompanying data file contains monthly observations for 5
years.
a. Calculate the 12-month centered moving
average. (Do not round intermediate calculations. Round
your answers to 2 decimal places.)
b. Calculate the ratio-to-moving average.
(Do not round intermediate
calculations.Round your answers to 2 decimal
places.)
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sept
Oct
Nov
Dec
CMA:ybar
Rate- to moving Average:y/ybar
1
28
30
19
10
28
10
39
31
26
28
18
22
2
20
21
39...
y′ = t, y(0) = 1, solution: y(t) = 1+t2/2 y′ = 2(t + 1)y, y(0)...
y′ = t, y(0) = 1, solution: y(t) = 1+t2/2
y′ = 2(t + 1)y, y(0) = 1, solution: y(t) = et2+2t
y′ = 5t4y, y(0) = 1, solution: y(t) = et5
y′ = t3/y2, y(0) = 1, solution: y(t) = (3t4/4 + 1)1/3
For the IVPs above, make a log-log plot of the error of Backward
Euler and Implicit Trapezoidal Method, at t = 1 as a function of
hwithh=0.1×2−k for0≤k≤5.
y′ = t, y(0) = 1, solution: y(t) = 1+t2/2 y′ = 2(t + 1)y, y(0)...
y′ = t, y(0) = 1, solution: y(t) = 1+t2/2
y′ = 2(t + 1)y, y(0) = 1, solution: y(t) = et2+2t
y′ = 5t4y, y(0) = 1, solution: y(t) = et5
y′ = t3/y2, y(0) = 1, solution: y(t) = (3t4/4 + 1)1/3
For the IVPs above, make a log-log plot of the error of Explicit
Trapezoidal Rule at t = 1 as a function ofhwithh=0.1×2−k
for0≤k≤5.
The accompanying data file shows the square footage and associated property taxes for 20 homes in...
The accompanying data file shows the square footage and
associated property taxes for 20 homes in an affluent suburb 30
miles outside of New York City. Estimate a home’s property taxes as
a linear function of its square footage. At the 5% significance
level, is square footage significant in explaining property taxes?
Show the relevant steps of the test.
Please use Minitab and explain the various steps involved.
Property Taxes
Square Footage
21928
2449
17339
2479
18229
1890
15693
1000...
Solve equations 1.) y'-y=t/y 2.) y'-(1/t)y=y2sin(t) 3.) y'+y=y2cos(t) 4.) y'-2y=cos(t)/(y1/2)
Solve equations
1.) y'-y=t/y
2.) y'-(1/t)y=y2sin(t)
3.) y'+y=y2cos(t)
4.) y'-2y=cos(t)/(y1/2)
T F If y' = 3y^(2) + 5y − 2 and y(1) = 0, then lim t→∞ y(t) = −2.
T F If y' = 3y^(2) + 5y − 2 and y(1) = 0, then lim t→∞ y(t) = −2.
Consider the following time series data. t 1 2 3 4 5 6 7 yt 10...
Consider the following time series data. t 1 2 3 4 5 6 7 yt 10 9
7 8 6 4 4 a. Construct a time series plot. What type of pattern
exists in the data? b. Develop the linear trend equation for this
time series. c. What is the forecast for t=8?
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