Math cafe
Please recall that we have a mathcafe where you can get help with your unsolved exercises. Next session is:
 Aalborg: Not scheduled yet.
 Esbjerg: Not scheduled yet.
 Copenhagen: Not scheduled yet.
Literature
 [Geil] Olav Geil, "Elementary Linear Algebra". Pearson, 2015. ISBN: 9781784483722.
Supplementary literature
MATLAB
The use of Matlab is an integral part of the four sessions without lectures (miniprojects) and, up to some extent, in other sessions as well. Students can freely download Matlab via the ICT link at http://www.tnb.aau.dk/. One can find more information in the MATLAB center (including a video showing how to install it).
Exam
The course is evaluated through a four hour written exam without the use of any electronic device. One may bring any kind of notes and books.
Plan
Manual for the exercises:
 Exercises are structured according to content.
 First, do the exercises that are bold. Then do the rest.
 In general, each student is responsible for doing enough
exercises to aquire basic skills and routine. Some students need
many exercises to get this, others fewer.
 Skills from one session will often be a prerequisite for the next
sessions. Hence, it is very important to keep up and master the
skills. Otherwise, one may have to spend a lot of time during
a later session practising skills which should have been routine
by then.
 Not only aquiring basic skills, but also understanding the text is
important. hence, the exercises testing understanding should be
taken seriously. At the exam, there are multiple choice exercises
along the lines of the True/False exercises in the textbook.
These exercises count for 30$\%$
of the points.

1. session:
 Topic: Introduction to vectors and matrices.
 Section 1.1 Matrices and vectors
 Addition og multiplication by a scalar. 1,3,7.
 Transposition. 5,11,9.
 Is it possible to add two matrices: 19, 21,
 Test your understanding of matrices and vectors:
3739, 41,42, 4456.
 Section 6.1. Scalarproduct and Orthogonality.
 Calculate norm of and distance between vectors 1, 7.
 Are two vectors orthogonal: 9, 15
 Section 1.2
 Matrixvector product: 1,3,5,7 9,11,15. Hint:
Pencast.
 Express a vector as a linear combination of a set of
vectors.: 29, 33, 31, 35, 39
 Test your understanding of linear combinations.
4551.
 Section 1.1
 Determine rows and columns in a matrix 29, 31
 Symmetric matrices 71, 72, 75.
 Skew matrices 79, 80, 81

2.session:
 Topic: Matrixvector product and systems of linear equations
 Section 1.2.
 Write $2\times 2$
rotation matrices. 17, 19
 Test your understanding of matrixvector products.
5164
 Section 1.3.
 Write the coeﬃcient matrix and the augmented
matrix of a linear system: 1,3,5.
 Rowoperations: 7,9,11
 Decide if a vector is a solution to a system of linear
equations. 23, 25.
 Decide from the reduced echelon form, if a system of
linear equations is consistent. If so, ﬁnd the general
solution. 39, 43, 41.
 As above, but furthermore write the genral solution
in vector form. 47, 49.
 Test your understanding of Systems of linear
equations and their matrices. 5776

3.session:
 Topic: Gausselimination. Span.
 Section 1.4:
 Decide, if a linear system is consisten. If so, ﬁnd the
general solution. 1,5,9,3,7,11
 Determine rank and nullity of a matrix. 37, 35.
 Test your understanding of Gausselimination: 5372.
 Section 1.6.
 Is $v$
in Span( $S$)?.
1,3,7
 Is $v$
in Span($S$)?
A coordinate in $v$
is unknown. 17, 19
 Is $Ax=b$
consistent for all $b$?
31,33.
 Test your understanding of span. 4564.
 About the connection between Span($S$)
and the span of a linearcombination of $S$.
71, 72. Consequences for rowoperations: 77, 78.
 Section 1.4:
 Systems of equations where a coeﬃcient $r$
is unknown. For which values of $r$
is the system inconsistent. 17, 19,21

4.session:
 Topic: Linear independence.
 Section 1.7.
 Determine, if a set of vectors is linearly dependent.
1,5,7,9,11
 Find a small subset of $S$,
with the same span as $S$.13,
15.
 Determine, if a set of vectors is linearly independent.
23,25,27
 Test your understanding of linear (in)dependence 1.7
6382.
 Given a set of vectors, one of which has an unknown
coordinate $r$.
For which values of $r$,
if any, is the set linearly dependent. 41.

5.session:
 Miniproject 1. Solve systems of linear equations using
MatLab

6.session:
 Topic: Linear transformations and matrices.
 Section 2.7.
 $T:X\to Y$
is induced by a matirx. Find $X$
and $Y$.
1, 3
 Find the image of a vector under a linear
transformation induced by a matrix. 7, 11
 From the rule for $T$,
ﬁnd $n$
and $m$,
such that $T:{\mathbb{R}}^{n}\to {\mathbb{R}}^{m}$.
21 23
 Find the standard matrix of a linear transformation.
25, 27, 29,31, 33
 Test your understanding of linear transformations
and their matrix representations. 3554.
 Section 2.8.
 Find a generating set for the range. 1,3
 Are the following maps surjective (onto), injective
(onetoone), bijective?
 $f:\mathbb{R}\to \mathbb{R}$,
$f\left(x\right)={x}^{2}+1$
 $g:\mathbb{R}\to \mathbb{R}$,
$g\left(x\right)={x}^{3}+1$
 $h:\text{ThesetofDanishcitizens}\phantom{\rule{3.26288pt}{0ex}}\to \mathbb{R}$
$h\left(x\right)$
is the CPRnumber for $x$.
 61, 65.
 Determine by ﬁnding a spanning set of the null
space, wheter a transformation is injective. 13,
15, 17
 Determine by ﬁnding the standard matrix, whether a
linear transformation is injective. 25, 29, surjective. 33,
35.
 Test your understanding of section 2.8 (till p. 185).
4155.
 Section 2.7.
 If $T$
er linear and $T\left(v\right)$
is known, what is $T\left(cv\right)$.
57
 Determine, if $T:{\mathbb{R}}^{n}\to {\mathbb{R}}^{m}$
is linear. 77, 73, 79

7.session:
 Topic: Matrix multiplication, composition of linear transformations.
 Section 2.1.
 If the product of two matrices is deﬁned, ﬁnd the size,
$m\times n$,
of the product. 1,3
 Calculate matrix products. 5,9,11,7. Calculate a
given entrance in a product matrix. 25
 Test your understanding of the matrix product.
3350.
 Section 2.8.
 Find a rule for $U\circ T$
from rules for $U$
og $T$.
69. Find standard matrices for $T$,
$U$
og $U\circ T$.
70, 71,72.
 Test your understanding of section 2.8  composition
of linear transformations and their matrices. 5658.
 MatLab: Section 2.1 opg. 53

8.session:
 Topic: Invertible matrices and invertible linear transformations.
 Section 2.3.
 determine whether $B={A}^{1}$.
1,3
 Given ${A}^{1}$
and ${B}^{1}$.
Find the inverse of combinations of $A$
and $B$.
9, 11.
 Elementary matrices. Find inverses. 17, 19. Givet
$A$,
$B$,
ﬁnd elementary matrices $E$,
such that $EA=B$.
25, 29.
 Section 2.4. Is a given matrix invertible? If so, ﬁnd the inverse.
1, 3, 5, 9, 13
 Section 2.8 The connection between invertible matrices and
invertible linear transformations. 59,60.
 Section 2.4.
 Rowreduction to calculate ${A}^{1}B$.
19
 Test your understanding of Section 2.4. 3554.
 Solve a system of linear equations by inverting the
coeﬃcient matrix. 57.
 Rowreduction to determine reduced row echelon form
$R$
of $A$
and a $P$
s.t. $PR=A$.
27
 Section 2.3
 The column correspondence property. 67.
 Write a column as a linear combination of the pivot
columns. 75.
 MatLab. Section 2.8. Find the standard matrix for a
linear transformations calculate the invers (MatLab)
Use this to ﬁnd a rule for the inverse transformation.
100

9.session:
 Topic: Determinants.
 Section 3.1
 Determinant of a $2\times 2$
matrix. 1, 3, 7. Do the calculation using the formula
on p. 200.
 Determinant of a $3\times 3$
matrix using cofactors. 13, 15
 Calculate determinants  choose your preferred
method. 21, 23.
 Determinant of $2\times 2$
matrices and area. 29
 Determinant and invertibility. 37.
 Test your understanding of determinants and
cofactors. 4564
 Section 3.2
 Calculate determinants develop after a given column
1, 5
 Calculate determinants using rowoperations . 13, 15,
21, 23
 Test your understanding of the properties of
determinants. 3958.
 Section 3.1 Prove that $det\left(AB\right)=det\left(A\right)det\left(B\right)$
for $2\times 2$
matrices. 71
 Section 3.2 Prove that $det\left({B}^{1}AB\right)=det\left(A\right)$
for $n\times n$
matrices $A$
and $B$,
where $B$
is invertible. 71

10.session:
 Miniproject 2: (01) matrices, Kirchoﬀ’s laws

11.session:
 Topic: Subspaces, basis for subspaces.
 Section 4.1
 Find a generating set for a subspace. 1, 5, 9.
 Is a vector in the null space of a given matrix. 11, 15
 Is a vector in the column space of a given matrix.
19,21
 Find a generating set for the null space of a matrix.
27, 29
 Test your understanding of subspace, nullspace,
column space. 4362.
 Prove that a set is not a subspace. 81,
 Prove that a set is a subspace. 89
 The null space of a linear transformation is a
subspace. 96.
 Section 4.2.
 Find a basis for the null space and column space of
a matrix. 1, 3, 5.
 Find a basis for the null space and range of a linear
transformation. 9,
 Section 4.1 Find a generating set for the column space of a
matrix. With a prescribed number of elements. 67,69
.

12.session:
 Topic: Dimension, Rank and nullity.
 Section 4.2
 Find a basis for the range and null space of a linear
transformation. 9, 11, 13 15
 Find a basis for a subspace 17, 19, 23
 Test your understanding of Basis and dimension.
3352.
 Section 4.3.
 Find the dimension of the column space,
null space and row space of a matrix
$A$
and the null space of
${A}^{T}$
 When $A$
is on reduced echelon form. 1, 3.
 In general. 7.
 Find the dimension of a subspace. 15
 Find en basis for rækkerum. 17, 19.
 Test your understanding of dimension of subspaces
connected to matrices. 4160.
 Prove that a given set is a basis for a given subspace. 61,
63.
 Section 4.2
 Explain why a set is not generating. 55
 Explain why a set is not linearly independent. 57.

13.session:
 Topic: Coordinatesystems.
 Section 4.4.
 Find $v$
given ${\left[v\right]}_{\mathcal{\mathcal{B}}}$
and $\mathcal{\mathcal{B}}$.
1, 7
 Given $v$
as a linear combination of $\mathcal{\mathcal{B}}$,
what is ${\left[v\right]}_{\mathcal{\mathcal{B}}}$?
13
 Find ${\left[v\right]}_{\mathcal{\mathcal{B}}}$
given $\mathcal{\mathcal{B}}$
and $v$.
15, 17, 19
 Write a vector as a linear combination of a set of
vectors. 25, 27
 Test your understanding of coordinate systems. 3150
 What is the connection between the matrix $\left[{\left[{e}_{1}\right]}_{\mathcal{\mathcal{B}}}{\left[{e}_{2}\right]}_{\mathcal{\mathcal{B}}}\right]$
and the matrix whose columns are the vectors in
$\mathcal{\mathcal{B}}$.
51, 53
 A basis $\mathcal{\mathcal{B}}$
for the plane is constructed by rotating the standard
basis. What is the connection between $v$
and ${\left[v\right]}_{\mathcal{\mathcal{B}}}$.
55, 67, 75
 Equations for cone sections before and after change
of basis. 79
 What does it imply, that there is a vector $v$,
s.t. ${\left[v\right]}_{A}={\left[v\right]}_{B}$?
99.

14.session:
 Topic: Linear transformations and coordinate systems.
 Section 4.5
 Find the matrix for $T$
wrt. $\mathcal{\mathcal{B}}$.
1,3,7
 Find the standard matrix for $T$
given ${\left[T\right]}_{\mathcal{\mathcal{B}}}$
and $\mathcal{\mathcal{B}}$.
11, 15
 Test your understanding of matrixrepresentations of
linear transformations 2023, 2538
 Find ${\left[T\right]}_{\mathcal{\mathcal{B}}}$,
the standardmatrix for $T$
and a rule for $T$
given $T\left({b}_{i}\right)$
for all $b\in \mathcal{\mathcal{B}}$.
47, 49, 51
 Find ${\left[T\right]}_{\mathcal{\mathcal{B}}}$
udfra $T\left({b}_{i}\right)$
as a linearcombination of $\mathcal{\mathcal{B}}$.
Then ﬁnd $T\left(w\right)$,
where $w$
is a linearcombination of $\mathcal{\mathcal{B}}$.
39, 55 43,59

15.session:
 Topic: Eigenvectors og og eigenvalues. 5.1 and 5.2 till p.
307
 Section 5.1
 Show that a vector is an eigenvector. 3, 7
 Show that a scalar is an eigenvalue. 13, 21
 Test your understanding of eigenvalues and
eigenvectors. 4156, 5760
 Section 5.2
 Find eigenvalues and a basis for the associated
eigenspaces
 For a matrix  given the characteristic
polynomial 1, 11
 For a matrix. 15, 19
 For a linear transformation  given the
characteristic polynomial. 31
 For a linear transformation. 37
 Does a $2\times 2$
matrix have any (reat) eigenvalues? 41
 Test your understanding of characteristic polynomial,
multiplicity of eigenvalues. 5359, 61,6365, 6972.
 Connection between eigenspaces for
$B$ og
$cB$
81.
 Connection between eigenvalues (and egenvectors?) for
$B$ og
${B}^{T}$
83.

16.session:
 Topic: Diagonalization. 5.3
 Section 5.3
 Given a matrix $A$
and the characteristic polynomial. Find $P$
and a diagonalmatrix $D$,
s.t. $A=PD{P}^{1}$
or explain why $A$
is not diagonalizable. 1, 3, 5,7,9
 As above, but the characteristic polynomial is not
given. 13, 15 17
 Test your understanding of diagonalization of
matrices. 2937, 3943, 45,46
 Determine from the eigenvalues and their multiplicity
whether $A$
is diagonalizable. 49, 51
 Given eigenvalues and a basis for the eigenspaces,
ﬁnd ${A}^{k}$.
57, 59
 Given a matrix and the characteristic polynomial.
One entrance is an unkonown. For which values is
the matrix not diagonalizable. 63
 Section 5.5. These exercises are connected to miniproject
3.
 Find the general solution to a system of diﬀerential
equations.. 45

17.session:
 Miniproject 3: Systems of diﬀ. eq.’s, 5.5

18.session:
 Topic: Ortogonality, Gram Schmidt, QRfaktorization.
 Section 5.5. These exercises are related to miniproject 3.
 Test your understanding of systems of linear
diﬀerential equations. 811
 In exercise 45, ﬁnd the solution satisfying ${y}_{1}\left(0\right)=1$
og ${y}_{2}\left(0\right)=4$.(Solution:
${y}_{1}\left(t\right)={e}^{3t}+2{e}^{4t}$.
${y}_{2}\left(t\right)=3{e}^{3t}+{e}^{4t}$)
 Section 6.1 (refresh your memory)
 Test your understanding of the inner product and
orthogonality. 6170, 7380
 Section 6.2
 Determine whether a set of vectors is orthogonal. 1,
3, 7
 Apply GramSchmidt. 9,11, 13,15
 $QR$faktorization.
25,27,29, 31
 Solve systems of equations using $QR$faktorization.
33, 35, 37,39 OBS: Show that the solutions you found
to $Rx={Q}^{T}b$
are solutions to $Ax=b$.
(An extra challenge: Why is this necessary.)
 Test your understanding of GramSchmidt and $QR$faktorization.
4152

19.session:
 Topic: Ortogonale projektioner. 6.3
 Section 6.1 (refresh your memory) Projection on a line. 43,
45
 Section 6.3
 Find a basis for the orthogonal complement. 1, 3, 5
 write a vector $u$
as a sum $u=w+z$,
where $w\in W$
and $z\in {W}^{\perp}$.
9,11
 As above. Moreover, ﬁnd the matrix ${P}_{W}$
for orthogonal projection on $W$,
ﬁnd the distance to $W$.
17,19,21 Hint to 21: Warning  the columns of $A$
are not linearly independent.
 Test your understanding of orthogonal projection og
orthogonal complement. 3356.
 What is the orthogonal complement to the
orthogonal complement? 63
 What is ${\left({P}_{W}\right)}^{2}$
and ${\left({P}_{W}\right)}^{T}$.
67
 Find ${P}_{W}$
given an orthonormal basis for $W$.
75

20.session:
 Topic: Orthogonal matrices. Orthogonal transformations in the
plane. 6.5 till p. 419

21.session:
 Miniproject 4: Least squares, 6.4

22.session:
 Topic: Rigid motion. 6.5 p.419421.
Overview of the course.
Suggestion: Use the problems from one of the exams as a point of
departure and explain in broad terms what to do in each of the
problems.
 Section 6.5
 Determine the matrix and vector of a rigid motion. 61, 62, 63, 64
 Old exams.
Old exams
Note: new structure in the organisation of the exam. Relevant from
spring 2016 and onwards.
 2017 spring
 2016 autumn
 2016 spring
 Test set
Previous exams
 Test set (2015 autumn)
 Test sets
 2010
 2011
 2012
 2013
 2014
 2015 autumn
Curriculum
Literature:
 [Geil] Olav Geil, "Elementary Linear Algebra". Pearson, 2015. ISBN: 9781784483722:
Curriculum ([Geil])::
 Section 1.1, 1.2, 1.3, 1.4, 1.6, 1.7
 Section 2.1, 2.3, 2.4, 2.7, 2.8
 Section 3.1, 3.2 to page 217 l.9
 Section 4.1, 4.2, 4.3, 4.4, 4.5
 Section 5.1, 5.2 to page 307 bottom, 5.3
 Orthogonality: Section 6.1 to page 366, 6.2, 6.3, 6.5.
 Appendix D
 Miniprojects 14
Math cafe
Do you have a hard time understanding linear algebra and/or calculus at the first study year, and are you determined to do something about it?
Then Math cafe is just the right thing for you.
It is held throughout the semester at all three campuses (specific times and places are listed below).
It is an extra possibility for getting help with maths. A teaching assistant is available to help you with exercises from the last few lectures.
The teaching assistants are preparing to help with the material from the last few lectures, and they might not be able to help with all your math questions, but feel free to ask.
This is a new initiative and its success is partly measured by the amount of students coming to the math cafe. If there is a great interest in this initiative we will schedule more than the ones planed now. On the other hand if attendance is very low cancellation may occur.
Note: This is an extra curricular activity, so it is NOT a valid excuse for not participating in other course activities or project work.
Aalborg
Here the math cafe in general runs either Tuesday or Thursday afternoon every week.
Current scheduled dates (will be updated throughout the semester):
 Tuesday 14/317 16:1517:45 in auditorium 1.
 Thursday 23/317 16:1517:45 in auditorium 1.
 Tuesday 28/317 16:1517:45 in auditorium 1.
 Thursday 6/417 16:1517:45 in auditorium 1.
 Thursday 20/417 16:1517:45 in auditorium 1.
 Tuesday 25/417 16:1517:45 in auditorium 1.
 Thursday 4/517 16:1517:45 in auditorium 1.
 Tuesday 9/517 16:1517:45 in auditorium 1.
 Thursday 18/517 16:1517:45 in auditorium 1.
 Tuesday 30/517 16:1517:45 in auditorium 1.
Esbjerg
Here the math cafe in general runs Tuesday afternoon approximately every other week.
Scheduled dates so far (will be updated throughout the semester):
 Tuesday 21/317 16:1517:45 in room C1.119.
 Tuesday 4/417 16:1517:45 in room C1.119.
 Tuesday 25/417 16:1517:45 in room C1.119.
 Tuesday 9/517 16:1517:45 in room C1.119.
 Tuesday 23/517 16:1517:45 in room C1.119.
Copenhagen
Here the math cafe in general runs Friday afternoon approximately every other week.
Scheduled dates so far (will be updated throughout the semester):
 Friday 17/317 16:1517:45 in room 0.108, FKJ 10A.
 Friday 7/417 16:1517:45 in room 0.108, FKJ 10A.
 Friday 28/417 16:1517:45 in room 0.108, FKJ 10A.
 Friday 19/517 16:1517:45 in room 0.108, FKJ 10A.
 Friday 2/617 16:1517:45 in room 0.108, FKJ 10A.
Mathematics during the weekend
Do you both want to improve your math skills before the exam and also see how the math at the first study year can be applied?
Then Math Saturday the 22nd of April 2017 at 9:3015:00 is just what you need. The main part of this event is held as a workshop in Aud. 1, Badehusvej, Aalborg.
The day will consist of two miniprojects where the teacher will give a short presentation of each subject (one before lunch and one after), and afterwards the teacher will assist you as needed during the project.
The two projects will make use of e.g. matrix multiplication, rotation matrices, scaling and translation, and you will use a large part of the material you have learnt in the semester so far.
Through both "pen and paper" exercises and MATLAB exercises the projects will stregthen your math skills.
Hence, this is a great occacion to practice Calculus and prepare for the exam.
It is possible to participate as nonDanish speaker since the course material and exercises will be in English, but the short intro by the teacher will be held in Danish.
The two subjects are Image representations and Computer graphics and planetary orbits, and a more detailed description of each is available on the Danish version of this page (you may try your luck with Google Translate or ask a fellow student that understands Danish).
A free sandwich is served for lunch and therefore you need to sign up by filling out the form below no later than Wednesday the 19th of April 2017.
It is no longer possible to sign up for the event.
Preparation for exam
You are offered help to prepare for the coming exam in both calculus and linear algebra at all three campuses.
The idea is much like the exercise session during a normal lecture, where you on your own solve exercises and can get help from a teaching assistant present to help you.
The point of departure for this exam preparation is the old exam sets available at this website, and you are encouraged to solve as much as possible on your own before showing up, so you know which parts you find difficult.
Please note that the teaching assistants are not coming to the group rooms; rather everybody sits in the same room where the teaching assistants are present as indicated below.
Note: In Aalborg the sessions Thursday and Friday are split up since there are fewer teaching assistants these days, so please take note of when you are supposed to come.
Aalborg  Calculus (and CALI for GBE)
Thursday 8 June 16:15  18:45 in Auditorium 6 Badehusvej 513.
(Only for the classes taught by Horia Cornean, Nikolaj HessNielsen and Athanasios Georgiadis.)
Friday 9 June 16:15  18:45 in Auditorium 6 Badehusvej 513.
(Only for the classes taught by Diego Ruano and Jon Johnsen.)
Saturday 10 June 10:00  15:00 in Auditorium 6 Badehusvej 513.
(For everyone.)
Sunday 11 June 10:00  15:00 in Auditorium 6 Badehusvej 513.
(For everyone.)
Aalborg  Linear algebra
Thursday 8 June 16:15  18:45 in Auditorium 7 Badehusvej 513.
(Only for the class taught by Jacob Broe.)
Friday 9 June 16:15  18:45 in Auditorium 7 Badehusvej 513.
(Only for the class taught by Nikolaj HessNielsen.)
Saturday 10 June 10:00  15:00 in Auditorium 7 Badehusvej 513.
(For everyone.)
Sunday 11 June 10:00  15:00 in Auditorium 7 Badehusvej 513.
(For everyone.)
Esbjerg  Linear algebra
Wednesday 7 June 8:15  10:15 in own group rooms.
Copenhagen  Calculus
Wednesday 31. maj 9:00  13:00 in room 3.161 FKJ 10A.