## Revision for Linear Algebra

Posted: November 14, 2013 in Linear Algebra Fall 2013

Some FAQs (updated now and then).

I’ve excluded the Chapters 17 to 20 from David Lerner’s notes. Does that mean that orthogonal projections, inner product and trace will not be tested?

No. I excluded them because in the notes, more “advanced” concepts are discussed in the chapters. For example, the chapter on inner product introduce the concept of positive definite and bilinear, which may be confusing. However, you will still need to know that how to compute the inner product between two vectors and what it means for two vectors to be orthogonal.

Similarly, orthogonal projection and trace are classic examples of linear transformations. Hence, you should be able to determine the kernel and range of these transformations. For example, Tut 10 Q2 asks you to determine the range of a trace map, which is within your ability. However, we will not ask you to show that trace map is invariant with respect to a change of basis.

I do not understand the concept of determining a matrix associated with a linear transformation.

Please take a look at this video from khan academy. I hope this is more illuminative.

Tut 11, Q4 is wrong.

My apologies. I’ve updated the worksheet.

When am I going to provide the feedback for the Final Sample?

Now. Here are the solutions with some feedback. Do not be too bothered by question 5.
If you want to find out more about projections as linear transformation, you can look at this video.

Am I going to provide the answers for the tutorial fill-in the blanks?

Ok…

Here are some general guidance to studying linear algebra:

David Lerner’s notes are useful for self-study. They contain small exercises that help understanding and sometimes give hints to the tutorial questions.

Chapters to take note are: Ch 1- 8, Ch 10-13, Ch 15.

Khan Academy also has a comprehensive course for linear algebra too.

Relevant videos/lessons are:

• Vector and spaces – Vectors, Linear combinations and spans, Linear dependence and independence, Subspaces and the basis for a subspace, Vector dot (without cross) product, Matrices for solving systems by elimination, Null space and column space.
• Matrix transformations – Functions and linear transformations, Linear transformation examples, Transformations and matrix multiplication (matrix products are more relevant), Finding inverses and determinants.
• It looks a lot, but the videos are typically very short. You can also select the topics to revise.

For those who prefer the “abstract” flavour, you can search for the text Linear Algebra Done Right by Sheldon Axler. (The link is the link to the official website. The book is easily found online, but I would not place it here.) This text is probably more useful for Linear Algebra 2.

My consultation hours are: Mon – Wed, 10am to 5pm. Please drop an email to arrange for consultation.

## Linear Algebra 1 – Midterm sample

Posted: October 4, 2013 in Linear Algebra Fall 2013

Here is some feedback for those who submitted the midterm samples.

There are some who attempted Q5 to Q7 (in Tutorial 6). I have also provided the solutions and feedback for these questions too.

Question 1 and 5

Solution: (Q1) Since the equation contains the term ${x^2}$, there are no values of ${k}$ that make the equation linear. (Q5) Since the equation contains the term ${xy}$, there are no values of ${\lambda}$ that makes the equation.

Feedback: Unless otherwise specified, unknowns in an equation are given by ${x}$, ${y}$ and ${z}$. For an equation to be linear, any term containing an unknown must be of the form (constant)${\cdot}$(unknown). Terms like ${xy}$ and ${x^2}$ are not of the required form and hence, the equation is not linear.

Some mistakes:

1. Writing “${k=0}$” and “${k=\emptyset}$” to mean “there are no values of ${k}$”. This is not the case. “${k=0}$” means ${k}$ can be ${0}$. “${k=\emptyset}$” means ${k}$ is a set which contains no element.

2. There is a solution that states ${k=0}$, because ${x^2-1=0}$ is in fact two straight lines. This is not correct. Prof Putinar mentioned that ${y^2=x^2}$ is in some sense “linear”. Do not interpret this as saying that the equation ${y^2=x^2}$ is linear. By definition, both ${x^2-1=0}$ and ${y^2=x^2}$ are not linear equations.

## SPMS Freshmen Survey

Posted: October 2, 2013 in General

Reposted from SPMS Student Welfare:

Hi Year 1s! We would like to have your feedback and suggestions on SPMS Freshmen Orientation 2013. Please click here to access the survey! Appreciate the time taken! Thank you!

SPMS Freshmen Survey

## Linear Algebra – Tutorials

Posted: August 20, 2013 in Linear Algebra Fall 2013

Fill-in-the-blanks Tutorial Solutions
Tutorial 8
Tutorial 9
Tutorial 10
Tutorial 11

Mini Revision Quiz 2
Slides

Mini Revision Quiz
Slides
Quiz 2 was well done. Everyone got full credit for this quiz.

Tutorial 3
Worksheet with blanks.
Worksheet with solutions.
Quiz 1 was generally well done. Almost everyone got full credit for this quiz.

## Real Analysis – Consultation

Posted: April 19, 2013 in General

Do note that I would be overseas from 26 Apr (Fri). Hence, I would not be available for consultation nor be able to answer an queries (including emails).

Good Luck for the Examinations!

## Real Analysis – Student Feedback

Posted: April 15, 2013 in Real Analysis Spring 2013

For students taking MH3100/MTH311, I sincerely like to seek your feedback on the the conduct of the tutorials.

Please access this link to provide your feedback. Feel free to make ANY comments and your feedback will be taken seriously and taken into consideration (if I ever get to teach again).

Note that the link is only available until 21 Apr (Sun).

Regards,
HanMao

## Real Analysis – Tutorial 9

Posted: March 27, 2013 in Real Analysis Spring 2013

As mentioned by Prof Chan and Prof Zhao, the definitions of limits can be interpreted as a challenge-and-respond’ process and Prof Zhao further elaborated ${\epsilon}$ as a standard of proximity’. In the tutorial, I gave another (similar) interpretation of the definition.

In general, most’ theorems and definitions in mathematics can be interpreted as a machine’ that produces some output given every input of certain type. For example, the definition of functional limits can be interpreted as the following machine.

Here, the input is a positive ${\epsilon}$ and the output (highlighted in blue) is a ${\delta}$. We notice the output has to fulfill certain conditions that are dependent on the input. This is highlighted in yellow.

In other words, the machine is a `${\lim_{x\rightarrow c} f(x)=L}$‘ machine if given input ${\epsilon>0}$, the machine outputs a ${\delta>0}$ such that ${|f(x)-L|<\epsilon}$ whenever ${0< |x-c|<\delta}$.