ISI MStat Entrance 2021 Problems and Solutions PSA & PSB

This post contains ISI MStat Entrance PSA and PSB 2021 Problems and Solutions that can be very helpful and resourceful for your ISI MStat Preparation.

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PSA Paper
PSB Paper
ISI MStat 2021 PSA Answer Key and Solutions

Click on the links to learn about the detailed solution. (Coming Soon)

  1. 49 (Rolle's Theorem)

2. 2 (4 - number of linear constraints)

3. k = 2 (a = -d, and form a biquadratic which has two real solutions)

4. 0 (divide by $x^4$, use $\frac{sinx}{x}$ limit result)

5. $\frac{p}{q}$ must be a rational number. (The product must be a rational number.)

6. $\alpha = 1, \beta =1$ (Use sandwich theorem on an easy inequality on ceiling of x)

7. $\frac{2n}{n+1}$ (Use geometry and definite integration)

8. $2+ \sqrt{5}$ (Just write down the pythagoras theorem in terms of the variables and solve)

9. 10 (Use the roots of unity)

10. $\frac{3}{8}$ (Find out the cases when it is non zero, and use classical probability)

11. $\frac{(n+1)^n}{n!}$ (Use ${{n} \choose {r}}={{n-1} \choose {r-1}}+{{n-1} \choose r}$)

12. $P(\pi)$ is even for all $\pi$. (Observe that there is one more odd than number of evens, so there will be one odd-odd match)

13. is equal to 12. (The $i,j$th element is $a_{ii}b{ij}c{jj}$. Use gp series then.)

14. 160 (Use the fact any permutation can be written as compositions of transpositions. Observe that the given condition is equivalent to that 2 transpositions are not possible)

15. $m_t < \infty$ for all $t \geq 0$ (All monotone functions are bounded on [a,b])

16.$H(x) = \frac{1-F(-x)+ F(x)}{2}$ (If $F(x)$ is right continuous, $F(-x)$ is left continuous.).

17. $\frac{1}{25}$ (Use the distribution function of $\frac{X}{Y}$)

18. 3 (Find the distribution of order statistic, and find the expectation)

19. (II) but not (I) (If $F(x)$ is right continuous, $F(-x)$ is left continuous.).

20. $20\lambda^4$ (Use gamma integral to find the $E(X_{1}^4)$.)

21. The two new observations are 15 and 5. (Use the condition to find two linear equations to find the observations).

22. It is less than 2. (Use the beta coefficients in terms of sample covariance and sample variance, and compare)

23. 4:3 (Use Bayes' Theorem)

24. The two-sample t-test statistic and the ANOVA statistics yield the same power for any non-zero value of $\mu_1 - \mu_2$ and for any $n,m$. (Both the test statistic are one to one function of one another)

25. t³-1 - 2(t-1)

26. $\frac{2 \sum_{i=1}^{n} X_i}{n(n+1)}$ (Use the invariance property of MLE)

27. $Y_1^2 + Y_2^2 + Y_1Y_2$ (Write the bivariate normal distribution in terms of $Y_1, Y_2$ and use Neyman Factorization Theorem.)

28. can be negative (Simson's Paradox)

29. $2z$ (There are three random variables, $N$ = stopping time to get $Y=1$, $Y$ and $X$. Use the conditioning properly. Take your time)

30. $\frac{40}{3}$ (Use the property that Poisson | Poisson in the given problem follows Binomial)


ISI MStat 2021 PSB Solutions
Coming soon.

ISI MStat PSB 2021 Problem 1

Solution

ISI MStat PSB 2021 Problem 2

Solution

ISI MStat PSB 2021 Problem 3

Solution

ISI MStat PSB 2021 Problem 4

Solution

ISI MStat PSB 2021 Problem 5

Solution

ISI MStat PSB 2021 Problem 6

Solution

ISI MStat PSB 2021 Problem 7

Solution

ISI MStat PSB 2021 Problem 8

Solution

ISI MStat PSB 2021 Problem 9

Solution

Please suggest changes in the comment section.

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ISI MStat and IIT JAM Training Program

ISI MStat Entrance 2020 Problems and Solutions PSA & PSB

This post contains ISI MStat Entrance PSA and PSB 2020 Problems and Solutions that can be very helpful and resourceful for your ISI MStat Preparation.

ISI MStat Entrance 2020 Problems and Solutions - Subjective Paper


ISI MStat 2020 Problem 1

Let f(x)=x2−2x+2. Let L1 and L2 be the tangents to its graph at x=0 and x=2 respectively. Find the area of the region enclosed by the graph of f and the two lines L1 and L2.

Solution

ISI MStat 2020 Problem 2

Find the number of 3×3 matrices A such that the entries of A belong to the set Z of all integers, and such that the trace of AtA is 6 . (At denotes the transpose of the matrix A).

Solution

ISI MStat 2020 Problem 3

Consider $n$ independent and identically distributed positive random variables $X_{1}, X_{2}, \ldots, X_{n}$. Suppose $S$ is a fixed subect of ${1,2, \ldots, n}$ consisting of $k$ distinct ekements where $1 \leq k<n$.
(a) Compute
$$
\mathrm{E}\left[\frac{\sum_{i \in s} X_{i}}{\sum_{i=1}^{\infty} X_{i}}\right]
$$
(b) Assume that $X_{i}$ is have mean $\mu$ and variance $\sigma^{2}, 0<\sigma^{2}<\infty$. If $j \notin S$, show that the correlation between ( $\left.\sum_{i \in s} X_{i}\right) X_{j}$ and $\sum_{i \in}X_{i} $ lies between $-\frac{1}{\sqrt{k+1}}$ and $\frac{1}{\sqrt{k+1}}$.

Solution

ISI MStat 2020 Problem 4

Let X1,X2,…,Xn be independent and identically distributed random variables. Let Sn=X1+⋯+Xn. For each of the following statements, determine whether they are true or false. Give reasons in each case.

(a) If Sn∼Exp with mean n, then each Xi∼Exp with mean 1 .

(b) If Sn∼Bin(nk,p), then each Xi∼Bin(k,p)

Solution

ISI MStat 2020 Problem 5

Let U1,U2,…,Un be independent and identically distributed random variables each having a uniform distribution on (0,1) . Let X=min{U1,U2,…,Un}, Y=max{U1,U2,…,Un}

Evaluate E[X∣Y=y] and E[Y∣X=x].

Solution

ISI MStat 2020 Problem 6

Suppose individuals are classified into three categories C1,C2 and C3 Let p2,(1−p)2 and 2p(1−p) be the respective population proportions, where p∈(0,1). A random sample of N individuals is selected from the population and the category of each selected individual recorded.

For i=1,2,3, let Xi denote the number of individuals in the sample belonging to category Ci. Define U=X1+X32

(a) Is U sufficient for p? Justify your answer.

(b) Show that the mean squared error of UN is p(1−p)2N

Solution

ISI MStat 2020 Problem 7

Consider the following model:
$$
y_{i}=\beta x_{i}+\varepsilon_{i} x_{i}, \quad i=1,2, \ldots, n
$$
where $y_{i}, i=1,2, \ldots, n$ are observed; $x_{i}, i=1,2, \ldots, n$ are known positive constants and $\beta$ is an unknown parameter. The errors $\varepsilon_{1}, \varepsilon_{2}, \ldots, \varepsilon_{n}$ are independent and identically distributed random variables having the
probability density function
$$
f(u)=\frac{1}{2 \lambda} \exp \left(-\frac{|u|}{\lambda}\right),-\infty<u<\infty
$$
and $\lambda$ is an unknown parameter.
(a) Find the least squares estimator of $\beta$.
(b) Find the maximum likelihood estimator of $\beta$.

Solution

ISI MStat 2020 Problem 8

Assume that $X_{1}, \ldots, X_{n}$ is a random sample from $N(\mu, 1)$, with $\mu \in \mathbb{R}$. We want to test $H_{0}: \underline{\mu}=0$ against $H_{1}: \mu=1$. For a fixed integer $m \in{1, \ldots, n}$, the following statistics are defined:

\begin{aligned}
T_{1} &=\left(X_{1}+\ldots+X_{m}\right) / m \\
T_{2} &=\left(X_{2}+\ldots+X_{m+1}\right) / m \\
\vdots &=\vdots \\
T_{n-m+1} &=\left(X_{n-m+1}+\ldots+X_{n}\right) / m .
\end{aligned}

Fix $\alpha \in(0,1)$. Consider the test

reject $H_{0}$ if max {${T_{i}: 1 \leq i \leq n-m+1}>c_{m, \alpha}$}

Find a choice of $c_{m, \alpha}$ $\mathbb{R}$ in terms of the standard normal distribution
function $\Phi$ that ensures that the size of the test is at most $\alpha$.

Solution

ISI MStat 2020 Problem 9

ISI MStat 2020 - Objective Paper


ISI MStat 2020 PSA Answer Key

Click on the links to learn about the detailed solution.

1. C2. D3. A4. B5. A
6. B7. C8. A9. C10. A
11. C12. D13. C14. B15. B
16. C17. D18. B19. B20. C
21. C22. D23. A24. B25. D
26. B27. D28. D29. B30. C

Please suggest changes in the comment section.

ISI MStat 2020 Probability Problems Discussion [Recorded Class]

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How to roll a Dice by tossing a Coin ? Cheenta Statistics Department

How can you roll a dice by tossing a coin? Can you use your probability knowledge? Use your conditioning skills.

Suppose, you have gone to a picnic with your friends. You have planned to play the physical version of the Snake and Ladder game. You found out that you have lost your dice.

The shit just became real!

Now, you have an unbiased coin in your wallet / purse. You know Probability.

Aapna Time Aayega

starts playing in the background. :p

Can you simulate the dice from the coin?

Ofcourse, you know chances better than others. :3

Take a coin.

Toss it 3 times. Record the outcomes.

HHH = Number 1

HHT = Number 2

HTH = Number 3

HTT = Number 4

THH = Number 5

THT = Number 6

TTH = Reject it, don't ccount the toss and toss again

TTT = Reject it, don't ccount the toss and toss again

Voila done!

What is the probability of HHH in this experiment?

Let X be the outcome in the restricted experiment as shown.

How is this experiment is different from the actual experiment?

This experiment is conditioning on the event A = {HHH, HHT, HTH, HTT, THH, THT}.

\(P( X = HHH) = P (X = HHH | X \in A ) = \frac{P (X = HHH)}{P (X \in A)} = \frac{1}{6}\)


Beautiful right?

Can you generalize this idea?

Food for thought

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Books for ISI MStat Entrance Exam

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Simple Linear Regression - Playlist on YouTube