(c) Which of the comments corresponds to the code in the lines denoted with (1), (2), (3) and (5)? (1) design matrix for a linear model design matrix for a quadratic model matrix for polynomial interpolation matrix for spline interpolation (2) solve non-linear equation solve normal equation solve quadratic equation project X onto Y (3) draw model as a solid curve draw model as single dots (5) оо draw measurements as linear spline draw measurements as single dots draw model as a solid curve draw model as single dots draw measurements as linear spline dras measurements as single dots % read in data data = xm ут csvread('measurements.csv'); data(:,1); % 50 measurements for x data (:,2); % 50 measurements for y M = [ones (size (xm)), xm, xm.^2]; % b = (MM) (-1) *M'*y; % (1) (2) & display results. figure (1), clf, hold on prepare figure plot (xm, ym, ' . '); 응 (3) linspace (min (xm), max (xm),200); % define values for x & determine predicted model values y = plot (x, y,'-') & (4) (5) Please answer the following multiple choice questions in part a.), b.) and c.): (a) Which numerical method has been used in the above given example? polynomial interpolation numerical differentiation least-squares regression numerical integration (b) Choose the correct code that needs to be put into the line denoted with the number (4): (4) O О y y = 1+b(2) + b(3) ; 1 + x + x.^2 ; y = b (1) = b (1) y = b (2) *x + b (3) *x. ^2 ; + b (2) *x ;
(c) Which of the comments corresponds to the code in the lines denoted with (1), (2), (3) and (5)? (1) design matrix for a linear model design matrix for a quadratic model matrix for polynomial interpolation matrix for spline interpolation (2) solve non-linear equation solve normal equation solve quadratic equation project X onto Y (3) draw model as a solid curve draw model as single dots (5) оо draw measurements as linear spline draw measurements as single dots draw model as a solid curve draw model as single dots draw measurements as linear spline dras measurements as single dots % read in data data = xm ут csvread('measurements.csv'); data(:,1); % 50 measurements for x data (:,2); % 50 measurements for y M = [ones (size (xm)), xm, xm.^2]; % b = (MM) (-1) *M'*y; % (1) (2) & display results. figure (1), clf, hold on prepare figure plot (xm, ym, ' . '); 응 (3) linspace (min (xm), max (xm),200); % define values for x & determine predicted model values y = plot (x, y,'-') & (4) (5) Please answer the following multiple choice questions in part a.), b.) and c.): (a) Which numerical method has been used in the above given example? polynomial interpolation numerical differentiation least-squares regression numerical integration (b) Choose the correct code that needs to be put into the line denoted with the number (4): (4) O О y y = 1+b(2) + b(3) ; 1 + x + x.^2 ; y = b (1) = b (1) y = b (2) *x + b (3) *x. ^2 ; + b (2) *x ;
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
Related questions
Question
Transcribed Image Text:(c) Which of the comments corresponds to the code in the lines denoted with (1), (2), (3) and (5)?
(1)
design matrix for a linear model
design matrix for a quadratic model
matrix for polynomial interpolation
matrix for spline interpolation
(2)
solve non-linear equation
solve normal equation
solve quadratic equation
project X onto Y
(3)
draw model as a solid curve
draw model as single dots
(5)
оо
draw measurements as linear spline
draw measurements as single dots
draw model as a solid curve
draw model as single dots
draw measurements as linear spline
dras measurements as single dots
![% read in data
data =
xm
ут
csvread('measurements.csv');
data(:,1); % 50 measurements for x
data (:,2); % 50 measurements for y
M = [ones (size (xm)), xm, xm.^2]; %
b =
(MM) (-1) *M'*y; %
(1)
(2)
& display results.
figure (1), clf, hold on prepare figure
plot (xm, ym, ' . ');
응
(3)
linspace (min (xm), max (xm),200); % define values for x
& determine predicted model values
y =
plot (x, y,'-') &
(4)
(5)
Please answer the following multiple choice questions in part a.), b.) and c.):
(a) Which numerical method has been used in the above given example?
polynomial interpolation
numerical differentiation
least-squares regression
numerical integration
(b) Choose the correct code that needs to be put into the line denoted with the number (4):
(4) O
О
y
y
=
1+b(2) + b(3) ;
1 + x + x.^2 ;
y
=
b (1)
= b (1)
y
=
b (2) *x + b (3) *x. ^2 ;
+ b (2) *x ;](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4810b3f8-7174-4e11-ad5b-d1003066dd42%2F51327c89-77ec-4281-8893-99753daad6cd%2F0l7wmt4_processed.png&w=3840&q=75)
Transcribed Image Text:% read in data
data =
xm
ут
csvread('measurements.csv');
data(:,1); % 50 measurements for x
data (:,2); % 50 measurements for y
M = [ones (size (xm)), xm, xm.^2]; %
b =
(MM) (-1) *M'*y; %
(1)
(2)
& display results.
figure (1), clf, hold on prepare figure
plot (xm, ym, ' . ');
응
(3)
linspace (min (xm), max (xm),200); % define values for x
& determine predicted model values
y =
plot (x, y,'-') &
(4)
(5)
Please answer the following multiple choice questions in part a.), b.) and c.):
(a) Which numerical method has been used in the above given example?
polynomial interpolation
numerical differentiation
least-squares regression
numerical integration
(b) Choose the correct code that needs to be put into the line denoted with the number (4):
(4) O
О
y
y
=
1+b(2) + b(3) ;
1 + x + x.^2 ;
y
=
b (1)
= b (1)
y
=
b (2) *x + b (3) *x. ^2 ;
+ b (2) *x ;
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