Getting ready for JC

Getting ready for JC

JC Mathematics, Mathematics

Its been awhile since we last posted. And it is good to know that JC1s have all been well inducted or settled into their schools. Of course, I do hear that many schools are severely overcrowded recently. Anyway, I thought of sharing how students can get ready for JC. I contemplated sharing how to cope with JC Mathematics, but decided to be more general this time round.

Firstly, JC life can be quite rigorous. With CCA and different subject commitments piling, students must try their best to stay healthy (get enough sleep) and juggle time (skip some dramas) efficiently. For science subjects (not just H2 Mathematics), students should avoid procrastinating. The schools do not go back to teaching the subjects again, maybe just refresh using questions or tests. Thus, seek help if you need and do not just sweep it off. For J1, your A’levels is pretty much in 22 months while for J2, it is 10 months. So the clock started ticking.

Secondly, last year’s papers were intuitive and some questions were driven to see if students do understand their content and can think on their feet. And we have a name for such questions, it is application questions. For H2 Mathematics, they have made an effort to allocate about 25% of the total marks to application questions. Thus, students need to shift their focus from doing to learning. It is important for them to appreciate the concepts in each topic.

Thirdly, I understand some students enter JC and realise that there are really some (or a lot of) smarter peers around. Do not feel pressured and just stay focus. Some of them might have found help, or developed better intuition for certain things. Comparing with your neighbour will only make yourself more stressed. This is unnecessary stress.

Lastly, JC is the last “school” you have. So do enjoy yourself. Pick a CCA that you really want to try. 🙂

Since Mr Teng teaches H2 Mathematics, here are some little tips for H2 Mathematics as I told my J1s this year.

  1. Some topics from High School are still very relevant, which is why I gave a proper review test. These topics are considered under assumed knowledge for H2 Mathematics, and you can find them here. A good understanding of these topics will allow you to follow classes better. You will learn that schools are constantly rushing to clear topics.

  2. Learn the topics. You do not need to master them, but learn and find out what is going on. Because you can memorise the entire Ten Years Series and realise that it will not save you.

  3. You will learn that time is very precious during exams. In general, 1 mark is 1.5 mins. And you should not go beyond it for questions. Rather learn the hard way to time manage well during exams, start with your normal practices at home. Thats why I encourage my students in class to do fast. Your papers will be two 3-hour papers, so during that 3-hour, you must exhibit sufficient tenacity.

P.S. I’ve spent the last few months getting a lot of application questions up. Aside from sharing them with students in my classes, I’ll also put them here. So do check in. 🙂

Happy CNY!

JC Talk 2018

JC General Paper, JC Mathematics

Over the weekends, we had the privilege of conducting a mini JC talk which saw Mr. Teng and Ms. Christine share their knowledge with parents and students of O’levels 2017.

The lessons for J1 2018 started on the first week of January and the schedules can be found here.

The following are the grade profiles of local universities, NUS and NTU.

NTU IGP

NUS IGP

We are very thankful for your attendance and do hope that the information was beneficial. If you do have more questions, you can contact Mr. Teng at +65 9815 6827

2017 A-level H2 Mathematics (9740) Paper 2 Suggested Solutions

2017 A-level H2 Mathematics (9740) Paper 2 Suggested Solutions

JC Mathematics, Mathematics

All solutions here are SUGGESTED. Mr. Teng will hold no liability for any errors. Comments are entirely personal opinions.

This is answers for H2 Mathematics (9740). H2 Mathematics (9758), click here.

Numerical Answers (click the questions for workings/explanation)

Question 1: 2 \sqrt{15}; xy=6
Question 2: d = 1.5;~ r \approx 1.21 \text{~or~} r \approx -1.45;~n=42
Question 3: (\frac{1}{2}a, 0), (0,b);~ (a+1, 0,);~ (\frac{a+1}{2}, 0);~ (0, a), (b, 0);~ a = 1;~ gg(x) = x, x \in \mathbb{R}, x \neq 1  , ~ g^{-1}(x) = 1 - \frac{1}{1-x}, x \in \mathbb{R}, x \neq 1;~b= 2 \text{~or~}0
Question 4: 15.1875;~ \frac{\pi}{2a(a-1)};~ b = \frac{1}{2} + \frac{1}{2}\sqrt{1-a+a^2}
Question 5: 0.647;~ 0.349;~k=2.56
Question 6: 955514880;~ 1567641600;~ \frac{1001}{3876}
Question 7: 31.8075, 0.245;~ p = 0.0139; Do not reject h_0, Not necessary.
Question 8: Model (D); a \approx 4.18, b \approx 74.0;~ r \approx 0.981
Question 9: 0.632;~ 1.04 \times 10^{-4};~ 0.472;~ 0.421;~ 0.9408
Question 10: 0.345;~ 0.612;~ \mu = 12.3, \sigma = 0.475;~ k \approx 55.7

Relevant materials

MF26

KS Comments

Making Use of this September Holidays

Making Use of this September Holidays

JC Mathematics, Mathematics

This is a little reminder and advice to students that are cheong-ing for their Prelims or A’levels…

For students who have not taken any H2 Math Paper 1 or 2, I strongly advise you start waking at up 730am and try some papers at 8am. I gave my own students similar advices and even hand them 4 sets of 3 hours practice papers. Students need to grind themselves to be able to handle the paper at 8am. It is really different. Not to mention, this September Holidays is probably your last chance to be able to give yourself timed practices.

For students who took H2 Math Paper 1, you might be stunned with the application questions that came out. For NJC, its Economics. For YJC, its LASER. For CJC, a wild dolphin appeared. And more. These application questions are possible, due to the inclusion of the problems in real world context in your syllabus. You can see the syllabus for yourself. I’ve attached the picture below. So for Paper 2, expect these application questions to be from statistics mainly, as suggested in your scheme of work below.

Scheme of Examination Source: SEAB

For students that have took H2 Math paper 1 & 2, and this is probably ACJC. The paper was slightly stressful, given the mark distributions, but most of the things tested are still technically “within syllabus”. For one, the directional cosine question, is a good reminder to students that they should not leave any pages un-highlighted. AC students should be able to properly identify their weaknesses and strengths this time round. If its time management, then start honing that skill this holidays – by having timed practice. A quick reminder that the TYS papers are not 3 hours, since some of the questions are out of H2 Mathematics 9758 syllabus. Students can consider the ratio of 1 mark to 1.5 min to gauge how much time they have for each paper.

R-Formulae seems to be popular about the prelims exams this time round, making waves in various schools. Perhaps it was because it appeared in the specimen paper, and if you’re keen on how it can be integrated or need a refresher. I did it recently here.

Lastly, for the students that are very concerned on application questions. Check the picture below. It contains some examples that SEAB has given. Students should also be clear about the difference between a contextual question and an application question.

Integration & Applications Source: SEAB

With that, all the best to your revision! 🙂

Trigonometry Formulae & Applications (Part 2)

Trigonometry Formulae & Applications (Part 2)

JC Mathematics, Secondary Math

I meant to share more on factor Formulae today. However, a few students are not so sure how to get the R-formulae correctly during their preliminary exams recently. So I thought that I’ll share how they can derive the R-Formulae from the MF26.

The following is the R-Formulae which students should have memorised. It is under assumed knowledge, just saying…

a \text{cos} \theta \pm b \text{sin} \theta = R \text{cos} (\theta \mp \alpha)

a \text{sin} \theta \pm b \text{cos} \theta = R \text{sin} (\theta \pm \alpha)

where R = \sqrt{a^2 + b^2} and \text{tan} \alpha = \frac{b}{a} for a > 0, b > 0 and \alpha is acute.

So here, I’ll write the addition formulae that’s found in MF26.

\text{sin}(A \pm B) \equiv \text{sin}A \text{cos} B \pm \text{cos} A \text{sin} B

\text{cos}(A \pm B) \equiv \text{cos}A \text{cos} B \mp \text{sin} A \text{sin} B

I’ll use an example I discussed previously.

f(x) = 3 \text{cos}t - 2 \text{sin}t

Write f(x) as a single trigonometric function exactly.

Lets consider the formulae from MF26.

\text{cos}(A \pm B) \equiv \text{cos}A \text{cos} B \mp \text{sin} A \text{sin} B

R\text{cos}(A \pm B) \equiv R \text{cos}A \text{cos} B \mp R \text{sin} A \text{sin} B

We can let

3 = R \text{cos} B ---(1)

2 = R \text{sin} B ---(2)

\Rightarrow \sqrt{ 3^2 + 2^2 } = \sqrt{ R^2 \text{cos}^2 B + R^2 \text{sin}^2 B}

\Rightarrow \sqrt{13} = R

\Rightarrow \frac{R \text{sin} B}{R \text{cos} B} = \frac{2}{3}

\Rightarrow \text{tan} B = \frac{2}{3}

Putting things together, we have that

 f(x) = \sqrt{13} \text{cos} ( t + \text{tan}^{\text{-1}} (\frac{2}{3}))

Students, test your Vectors!

Students, test your Vectors!

JC Mathematics

As the prelims examinations draw really close, many students were asking me to give questions to test their concepts for several topics. In class, I had the opportunity to explore several applications questions too. We saw several physics concepts mixed. We also have some conceptual questions that need students to be able to use the entire topic to solve it.

So I’ll share one here. This involves several concepts put together. I’ll put the solution up once I find the time. Concepts that will be involved, will be

  1. Vector Product
  2. Equations of Plane
  3. Finding foot of perpendicular of point

The question in one a reflection of a plane in another plane. I think such questions will come out in a few guided steps in exams. But should a student be able to solve it independently, it shows that he has good understanding.

The plane p has equation x + y + z = 9 and the plane p_1 contains the lines passing through (0, 2, 3) and are parallel to (1, -1, 0) and (0, 1, 1) respectively. Find, in scalar product form, the equation of the plane which is the reflection of p_1 in p.

Quick Summary (Probability)

Quick Summary (Probability)

JC Mathematics, Mathematics, University Mathematics

University is starting for some students who took A’levels in 2016. And, one of my ex-students told me to share/ summarise the things to know for probability at University level. Hopefully this helps. H2 Further Mathematics Students will find some of these helpful.


Random Variables

Suppose X is a random variable which can takes values x \in \chi.

X is a discrete r.v. is \chi is countable.
\Rightarrow p(x) is the probability of a value of x and is called the probability mass function.

X is a continuous r.v. is \chi is uncountable.
\Rightarrow f(x) is the probability density function and can be thought of as the probability of a value x.

Probability Mass Function

For a discrete r.v. the probability mass function (PMF) is

p(a) = P(X=a), where a \in \mathbb{R}.

Probability Density Function

If B = (a, b)

P(X \in B) = P(a \le X \le b) = \int_a^b f(x) ~dx.

And strictly speaking,

P(X = a) = \int_a^a f(x) ~dx = 0.

Intuitively,

f(a) = P(X = a).

Properties of Distributions

For discrete r.v.
p(x) \ge 0 ~ \forall x \in \chi.
\sum_{x \in \chi} p(x) = 1.

For continuous r.v.
f(x) \ge 0 ~ \forall x \in \chi.
\int_{x \in \chi} f(x) ~dx = 1.

Cumulative Distribution Function

For discrete r.v., the Cumulative Distribution Function (CDF) is
F(a) = P(X \le a) = \sum_{x \le a} p(x).

For continuous r.v., the CDF is
F(a) = P(X \le a ) = \int_{- \infty}^a f(x) ~dx.

Expected Value

For a discrete r.v. X, the expected value is
\mathbb{E} (X) = \sum_{x \in \chi} x p(x).

For a continuous r.v. X, the expected value is
\mathbb{E} (X) = \int_{x \in \chi} x f(x) ~dx.

If Y = g(X), then

For a discrete r.v. X,
\mathbb{E} (Y) = \mathbb{E} [g(X)] = \sum_{x \in \chi} g(x) p(x).

For a continuous r.v. X,
\mathbb{E} (Y) = \mathbb{E} [g(X)] = \int_{x \in \chi} g(x) f(x) ~dx.

Properties of Expectation

For random variables X and Y and constants a, b, \in \mathbb{R}, the expected value has the following properties (applicable to both discrete and continuous r.v.s)

\mathbb{E}(aX + b) = a \mathbb{E}(X) + b

\mathbb{E}(X + Y) = \mathbb{E}(X) + \mathbb{E}(Y)

Realisations of X, denoted by x, may be larger or smaller than \mathbb{E}(X),

If you observed many realisations of X, \mathbb{E}(X) is roughly an average of the values you would observe.

\mathbb{E} (aX + b)
= \int_{- \infty}^{\infty} (ax+b)f(x) ~dx
= \int_{- \infty}^{\infty} axf(x) ~dx + \int_{- \infty}^{\infty} bf(x) ~dx
= a \int_{- \infty}^{\infty} xf(x) ~dx + b \int_{- \infty}^{\infty} f(x) ~dx
= a \mathbb{E} (X) + b

Variance

Generally speaking, variance is defined as

Var(X) = \mathbb{E}[(X- \mathbb{E}(X)^2] = \mathbb{E}[X^2] - \mathbb{E}[X]^2

If X is discrete:

Var(X) = \sum_{x \in \chi} ( x - \mathbb{E}[X])^2 p(x)

If X is continuous:

Var(X) = \int_{x \in \chi} ( x - \mathbb{E}[X])^2 f(x) ~dx

Using the properties of expectations, we can show Var(X) = \mathbb{E}(X^2) - \mathbb{E}(X)^2.

Var(X)
= \mathbb{E} [(X - \mathbb{E}[X])^2]
= \mathbb{E} [(X^2 - 2X \mathbb{E}[X]) + \mathbb{E}[X]^2]
= \mathbb{E}[X^2] - 2\mathbb{E}[X]\mathbb{E}[X] + \mathbb{E}[X]^2
= \mathbb{E}[X^2] - \mathbb{E}[X]^2

Standard Deviation

The standard deviation is defined as

std(X) = \sqrt{Var(X)}

Covariance

For two random variables X and Y, the covariance is generally defined as

Cov(X, Y) = \mathbb{E}[(X - \mathbb{E}[X])(Y - \mathbb{E}[Y])]

Note that Cov(X, X) = Var(X)

Cov(X, Y) = \mathbb{E}[XY] - \mathbb{E}[X] \mathbb{E}[Y]

Properties of Variance

Given random variables X and Y, and constants a, b, c \in \mathbb{R},

Var(aX \pm bY \pm b ) = a^2 Var(X) + b^2 Var(Y) + 2ab Cov(X, Y)

This proof for the above can be done using definitions of expectations and variance.

Properties of Covariance

Given random variables W, X, Y and Z and constants a, b, \in \mathbb{R}

Cov(X, a) = 0

Cov(aX, bY) = ab Cov(X, Y)

Cov(W+X, Y+Z) = Cov(W, Y) + Cov(W, Z) + Cov(X, Y) + Cov(X, Z)

Correlation

Correlation is defined as

Corr(X, Y) = \dfrac{Cov(X, Y)}{Std(X) Std(Y)}

It is clear the -1 \le Corr(X, Y) \le 1.

The properties of correlations of sums of random variables follow from those of covariance and standard deviations above.

Thinking Math@TheCulture #2

Thinking [email protected] #2

JC Mathematics, Mathematics

[email protected] is a series of questions that we, as tutors feel that are useful in helping students think and improve their understanding.

Thinking [email protected] is curated by KS. More of him can be found here.


(i) Find the two possible values of z such that z^2 = 1 + \sqrt{3}i, leaving your answer in exact form a + bi, where a and b are real numbers.

(ii) Hence or otherwise, find the exact roots of the equation

2w^2 + 2 \sqrt{6}w + 1 - 2 \sqrt{3} i = 0