Browse papers
LevelMaster in Data Science (SMS, TU)
SubjectMathematics for Data Science
Year2078 BS
Exam sessionFirst Assessment · Set First Assessment 2078, p4 (Group A only fully shown; Group B Q6 begins, continues elsewhere)
Full marks45
Time allowed120 minutes
Questions6, all with step-by-step solutions
A

Group A

5 questions·3 marks each
1Short answer3 marks

Show that

(a) The line x2=ax1x_2 = ax_1 (in usual notations, y=axy = ax) is a subspace of R2\mathbb{R}^2.

(b) The line x2=ax1+bx_2 = ax_1 + b (perhaps more familiar as y=ax+by = ax + b) is not a subspace of R2\mathbb{R}^2 for b0b \neq 0.

subspacelinear-algebra
2Short answer3 marks

Show that any vector in R3\mathbb{R}^3 can be expressed as a linear combination of the three unit basis vectors in R3\mathbb{R}^3. Also, show that a linear combination of the three unit basis vectors in R3\mathbb{R}^3 equals to 0 if and only if all coefficients in the linear combination are zeros.

linear-combinationbasis
3Short answer3 marks

What is the parallel coordinates method? Explain with an example. What is the use of this method in data science?

parallel-coordinatesvisualization
4Short answer3 marks

Find a basis for the solution space of the equation x+yz=0x + y - z = 0.

basissolution-space
5Short answer3 marks

Let u1=(1,2,2,1)u_1 = (1, 2, 2, -1), u2=(1,1,1,1)u_2 = (1, 1, -1, 1), u3=(1,1,1,1)u_3 = (-1, 1, -1, -1) and B={u1,u2,u3}B = \{u_1, u_2, u_3\} an orthogonal basis for V=span(u1,u2,u3)V = \text{span}(u_1, u_2, u_3). Find the projection of w=(0,1,2,3)w = (0, 1, 2, 3) onto VV.

projectionorthogonal-basis
B

Group B

1 questions·6 marks each
6Long answer6 marks

(a) By showing that the LL_\infty-norm satisfies each of the conditions in the definition of a norm prove this is a vector norm for Rn\mathbb{R}^n.

(b) Let x=(x1,,xn)Rnx = (x_1, \ldots, x_n) \in \mathbb{R}^n be a vector with xi=i1x_i = i^{-1}. Compute the 1-norm, the 2-norm, and the \infty-norm of xx.

OR

Prove that if xx and yy are vectors in Rn\mathbb{R}^n, then

(a) xyx2y2|x \cdot y| \leq \|x\|_2 \|y\|_2.

vector-normcauchy-schwarz

Frequently asked questions

Where can I find the Master in Data Science (SMS, TU) Mathematics for Data Science question paper 2078?
The full Master in Data Science (SMS, TU) Mathematics for Data Science 2078 (First Assessment) question paper is available free on Kekkei. You can read every question online and attempt the paper under timed exam conditions.
Does the Mathematics for Data Science 2078 paper come with solutions?
Yes. Every question on this Mathematics for Data Science past paper includes a step-by-step solution, plus instant AI feedback when you attempt it on Kekkei.
How many marks is the Master in Data Science (SMS, TU) Mathematics for Data Science 2078 paper?
The Master in Data Science (SMS, TU) Mathematics for Data Science 2078 paper carries 45 full marks and is meant to be completed in 120 minutes, across 6 questions.
Is practising this Mathematics for Data Science past paper free?
Yes — reading and attempting this Mathematics for Data Science past paper on Kekkei is completely free.