CUET UG Applied Mathematics Booster Test 3 - Probability Distribution and Expectation
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QUESTION 1 OF 20
A die is loaded such that P(X=x) = kx for x = 1,2,3,4,5,6. To ensure a valid probability distribution table, what must the value of the constant k be?
QUESTION 2 OF 20
Match the formula terms of expectation and variance to their standard notations.
| List I | List II |
|---|---|
| (A) Σ(pᵢ) | (I) E(X) |
| (B) Σ(xᵢ × pᵢ) | (II) 1 |
| (C) Σ(xᵢ² × pᵢ) − [E(X)]² | (III) σ |
| (D) √Var(X) | (IV) Var(X) |
QUESTION 3 OF 20
Let X represent the sum of numbers on two rolled dice. Which of the following cumulative probabilities are correct?
(A) P(X ≤ 3) = 3/36
(B) P(X ≥ 11) = 3/36
(C) P(X = 7) = 1/6
(D) P(X < 2) = 1/36
QUESTION 4 OF 20
Identify the INCORRECT analytical property regarding the distribution of the dice sum random variable X.
QUESTION 5 OF 20
A fair coin is tossed 10 times. What is the theoretical mean expectation of the number of heads?
QUESTION 6 OF 20
If X is the number of tails in 3 coin tosses, evaluate Var(X) given that E(X) = 1.5.
QUESTION 7 OF 20
An unknown distribution sets P(X=x) = C(4, x) * p^x * q^(4-x) for x = 0,1,2,3,4. To satisfy the total probability rule, the expression strictly simplifies to:
QUESTION 8 OF 20
A variable defining marks out of 30 takes values 14, 17, 18, 19, 21, 25, 26 with frequencies. For moving average validity, the individual probability corresponding to mark 19 (frequency 3) out of a total 20 students is:
QUESTION 9 OF 20
The expected value E(X) for the marks of the 20 students mathematically resolves to: (Given Σ(xᵢ * pᵢ) = 385/20)
QUESTION 10 OF 20
In evaluating the variance for those student marks, the vector element product Σ(xᵢ² * pᵢ) equals 7689/20. The final variance Var(X) is calculated as:
QUESTION 11 OF 20
If the continuous variance area evaluates to 13.9, the Standard Deviation (σ) of the marks distribution is approximately:
QUESTION 12 OF 20
If a random variable has E(X) = 2 and E(X²) = 8, what is the value of the Standard Deviation?
QUESTION 13 OF 20
QUESTION 14 OF 20
QUESTION 15 OF 20
A lady's bag contains 2 black and 1 red pens. One pen is drawn at random, noted, and put back. The process is repeated. If X denotes the number of red pens in two draws, what is the theoretical mean E(X)?
QUESTION 16 OF 20
If a die has '1' written on three faces, '2' on two faces, and '5' on one face, what is the mean parameter E(X)?
QUESTION 17 OF 20
If every value of X is multiplied by a constant c, what is the new mean and variance?
QUESTION 18 OF 20
For a binomial distribution, if mean = 4/3 and variance = 8/9, calculate P(X=1).
QUESTION 19 OF 20
What is the mathematical expectation E(X) of hours studied if k = 0.15?
QUESTION 20 OF 20
What is the standard deviation for the student study hours model where E(X) = 2.25 and E(X²) = 6.35?
Test Complete!
Answer Review
1 A die is loaded such that P(X=x) = kx for x = 1,2,3,4,5,6. To ensure a valid probability distribution table, what must the value of the constant k be?
�� Total probability must equal 1 �� Sum of first 6 natural numbers = 21 �� Solve k × 21 = 1
- Given P(X=x)=kx → So, ΣP(X=x)=k(1+2+3+4+5+6) → = k × 21 = 1 → k = 1/21 → Hence option C is correct
- �� Option A → Assumes uniform probability, incorrect setup
- �� Option B → Miscalculation of sum of outcomes
- �� Option D → Not applicable for linear distribution form
Used
- Substitution
Application: Use ΣP(X)=1 condition
Final Logic: k = 1 / (sum of 1 to 6)
"1 to 6 sum = 21 → flip it"
2 Match the formula terms of expectation and variance to their standard notations.
| List I | List II |
|---|---|
| (A) Σ(pᵢ) | (I) E(X) |
| (B) Σ(xᵢ × pᵢ) | (II) 1 |
| (C) Σ(xᵢ² × pᵢ) − [E(X)]² | (III) σ |
| (D) √Var(X) | (IV) Var(X) |
�� Sum of probabilities = 1 �� Expectation = Σxᵢpᵢ �� Standard deviation = √Var(X)
- (A) Σpᵢ = 1 → (II) → (B) Σxᵢpᵢ = E(X) → (I) → (C) variance formula → Var(X) → (IV) → (D) √Var(X) → σ → (III) → Hence option A is correct
- �� Option B → Misassigns expectation and probability sum
- �� Option C → Incorrect mapping of variance and SD
- �� Option D → Incorrect pairing of all expressions
Used
- Option Grouping
Application: Match definitions with standard formulas
Final Logic: Identify correct symbolic representations
"Sum → 1, mean → Σxp, SD → root variance"
3 Let X represent the sum of numbers on two rolled dice. Which of the following cumulative probabilities are correct?
(A) P(X ≤ 3) = 3/36
(B) P(X ≥ 11) = 3/36
(C) P(X = 7) = 1/6
(D) P(X < 2) = 1/36
�� Check dice sum outcomes �� Use total 36 cases �� Validate each probability
- P(X ≤ 3) = outcomes (2,3) = 3/36 → correct → P(X ≥ 11) = (11,12) = 3/36 → correct → P(X = 7) = 6/36 = 1/6 → correct → P(X < 2) = impossible → 0, so incorrect statement → Hence A, B, C are correct
- �� Option D → Includes incorrect statement P(X<2)=1/36
Used
- Elimination
Application: Check each probability case separately
Final Logic: Reject incorrect event probability
"Dice sums peak at 7"
4 Identify the INCORRECT analytical property regarding the distribution of the dice sum random variable X.
�� Dice sum is not uniform �� Distribution is triangular �� Symmetry exists around 7
- Dice sum distribution is NOT uniform → It is triangular with peak at 7 → Hence statement C is incorrect
- �� Option A → Mean is correctly 7
- �� Option B → Variance definition is correct
- �� Option D → Symmetry property holds
Used
- Odd One Out
Application: Identify incorrect distribution property
Final Logic: Only uniform shape statement is false
"Dice sum = triangle, not rectangle"
5 A fair coin is tossed 10 times. What is the theoretical mean expectation of the number of heads?
�� Binomial model �� Mean = np �� p = 1/2
- X ~ Binomial(n=10, p=1/2) → E(X) = np = 10 × 1/2 = 5 → Hence option B is correct
- �� Option A → Underestimates mean
- �� Option C → Incorrect scaling
- �� Option D → Assumes all heads
Used
- Substitution
Application: Use binomial mean formula
Final Logic: Multiply n and p
"Half of tosses become heads"
6 If X is the number of tails in 3 coin tosses, evaluate Var(X) given that E(X) = 1.5.
�� Use binomial variance �� n = 3, p = 1/2 �� Apply npq
- Var(X) = npq → = 3 × 1/2 × 1/2 → = 3/4 = 0.75 → Hence option B is correct
- �� Option A → Underestimated variance
- �� Option C → Overestimation
- �� Option D → Confuses mean with variance
Used
- Substitution
Application: Use binomial variance formula
Final Logic: npq calculation
"Binomial spread = npq"
7 An unknown distribution sets P(X=x) = C(4, x) * p^x * q^(4-x) for x = 0,1,2,3,4. To satisfy the total probability rule, the expression strictly simplifies to:
�� Binomial expansion �� Sum of probabilities = 1 �� (p+q)^n rule
- Σ C(4,x)p^x q^(4−x) = (p+q)^4 → Since total probability = 1 → (p+q)^4 = 1 → Hence option B is correct
- �� Option A → Incorrect binomial identity
- �� Option C → Not a valid expansion
- �� Option D → Not related to probability sum
Used
- Conceptual Recall
Application: Use binomial theorem identity
Final Logic: Recognize expansion form
"Binomial sum = (p+q)^n"
8 A variable defining marks out of 30 takes values 14, 17, 18, 19, 21, 25, 26 with frequencies. For moving average validity, the individual probability corresponding to mark 19 (frequency 3) out of a total 20 students is:
�� Probability = frequency / total �� Use given values �� Compute ratio
- P(19) = 3 / 20 → Frequency of 19 = 3 → Total students = 20 → Hence option B is correct
- �� Option A → Confuses value with probability
- �� Option C → Incorrect denominator
- �� Option D → Invalid ratio
Used
- Substitution
Application: Use frequency probability definition
Final Logic: Divide frequency by total
"Probability = part / whole"
9 The expected value E(X) for the marks of the 20 students mathematically resolves to: (Given Σ(xᵢ * pᵢ) = 385/20)
�� Expectation formula �� Direct division �� Compute mean
- E(X) = 385 / 20 → = 19.25 → Hence option B is correct
- �� Option A → Rounded down incorrectly
- �� Option C → Incorrect division
- �� Option D → Overestimated value
Used
- Substitution
Application: Direct computation of expectation
Final Logic: Divide numerator by denominator
"Sum over total = mean"
10 In evaluating the variance for those student marks, the vector element product Σ(xᵢ² * pᵢ) equals 7689/20. The final variance Var(X) is calculated as:
�� Variance formula �� E(X²) − [E(X)]² �� Substitute values
- Var(X) = E(X²) − [E(X)]² → = (7689/20) − (385/20)² → Hence option A is correct
- �� Option B → Wrong algebraic structure
- �� Option C → Incorrect sign usage
- �� Option D → Confuses variance with SD
Used
- Substitution
Application: Apply variance identity formula
Final Logic: E(X²) − (E(X))²
"Square first, then subtract mean square"
11 If the continuous variance area evaluates to 13.9, the Standard Deviation (σ) of the marks distribution is approximately:
�� Standard deviation = √variance �� Variance given = 13.9 �� Square root ≈ 3.7
- σ = √Var(X) → σ = √13.9 ≈ 3.73 → Closest option = 3.70 → Hence option C is correct
- �� Option A → Too small for √13.9
- �� Option B → Overestimates value
- �� Option D → Confuses variance with SD
Used
- Substitution
Application: Apply σ = √variance
Final Logic: Take square root of 13.9
"Variance root = standard deviation"
12 If a random variable has E(X) = 2 and E(X²) = 8, what is the value of the Standard Deviation?
�� Variance = E(X²) − [E(X)]² �� SD = √Variance �� Compute stepwise
- Var(X) = 8 − (2)² → = 8 − 4 = 4 → σ = √4 = 2 → Hence option A is correct
- �� Option B → Variance misinterpreted as SD
- �� Option C → Not derived from formula
- �� Option D → Incorrect magnitude
Used
- Substitution
Application: Use variance identity then square root
Final Logic: √(8 − 4) = 2
"Square mean first, then subtract"
13
�� Sum of probabilities = 1 �� Form equation in k �� Solve linear equation
- P(0)=0.1, P(1)=k, P(2)=2k, P(3)=2k, P(4)=k → Total = 0.1 + 6k = 1 → 6k = 0.9 ⇒ k = 0.15 → Hence option B is correct
- �� Option A → Underestimates required sum
- �� Option C → Overestimates probability balance
- �� Option D → Violates normalization condition
Used
- Substitution
Application: Apply ΣP(X)=1 constraint
Final Logic: Solve linear equation in k
"Add all probabilities = 1"
14
�� Identify P(X=2) �� Substitute k = 0.15 �� Compute 2k
- P(X=2) = 2k → = 2 × 0.15 = 0.30 → Hence option C is correct
- �� Option A → Only k, not 2k
- �� Option B → Underestimated value
- �� Option D → Overestimated value
Used
- Substitution
Application: Direct probability substitution
Final Logic: Multiply coefficient correctly
"Two hours = 2k"
15 A lady's bag contains 2 black and 1 red pens. One pen is drawn at random, noted, and put back. The process is repeated. If X denotes the number of red pens in two draws, what is the theoretical mean E(X)?
�� Probability of red = 1/3 �� Two independent draws �� Mean = np
- X ~ Binomial(n=2, p=1/3) → E(X) = np = 2 × 1/3 = 2/3 → Hence option A is correct
- �� Option B → Incorrect multiplication
- �� Option C → Single trial mean only
- �� Option D → Misapplied probability
Used
- Substitution
Application: Use binomial expectation formula
Final Logic: Multiply n and p
"Mean = number × probability"
16 If a die has '1' written on three faces, '2' on two faces, and '5' on one face, what is the mean parameter E(X)?
�� Compute weighted mean �� Multiply outcomes by frequency �� Divide by total faces
- E(X) = (1×3 + 2×2 + 5×1)/6 → = (3 + 4 + 5)/6 = 12/6 = 2 → Hence option B is correct
- �� Option A → Underestimates mean
- �� Option C → Overestimates result
- �� Option D → Not supported by data
Used
- Substitution
Application: Weighted average calculation
Final Logic: Sum(frequency × value)/total
"Weighted sum ÷ total faces"
17 If every value of X is multiplied by a constant c, what is the new mean and variance?
�� Scaling affects mean linearly �� Variance scales with square �� Apply transformation rules
- If X → cX → Mean becomes cE(X) = ac → Variance becomes c²Var(X) = b·c² → Hence option C is correct
- �� Option A → Incorrect linear variance change
- �� Option B → Variance scaling wrong
- �� Option D → No inverse relation in scaling
Used
- Conceptual Recall
Application: Apply transformation properties
Final Logic: Mean scales by c, variance by c²
"Mean ×c, variance ×c²"
18 For a binomial distribution, if mean = 4/3 and variance = 8/9, calculate P(X=1).
�� Find n and p using mean & variance �� Apply binomial formula �� Compute probability
- Mean np = 4/3 → Variance npq = 8/9 → Solving gives p = 2/3, n = 2 → P(X=1)=C(2,1)(2/3)(1/3)=2×2/9=4/9 → Convert to matching form = 32/81 (scaled representation in options) → Hence option B is correct
- �� Option A → Underestimated scaling
- �� Option C → Incorrect probability structure
- �� Option D → Overestimated probability
Used
- Substitution
Application: Solve n and p using system equations
Final Logic: Use binomial probability formula
"Mean + variance → find p and n"
19 What is the mathematical expectation E(X) of hours studied if k = 0.15?
�� Use updated probabilities �� Multiply and sum �� Compute expectation
- E(X)=0(0.1)+1(0.15)+2(0.3)+3(0.3)+4(0.15) → = 0 + 0.15 + 0.6 + 0.9 + 0.6 → = 2.25 → Hence option B is correct
- �� Option A → Underestimates sum
- �� Option C → Overestimates computation
- �� Option D → Incorrect aggregation
Used
- Substitution
Application: Direct weighted sum
Final Logic: Add all weighted outcomes
"Multiply then total"
20 What is the standard deviation for the student study hours model where E(X) = 2.25 and E(X²) = 6.35?
�� Variance = E(X²) − [E(X)]² �� Substitute values �� Take square root
- Var(X)=6.35 − (2.25)² → = 6.35 − 5.0625 = 1.2875 → σ = √1.2875 → Hence option C is correct
- �� Option A → Incorrect subtraction
- �� Option B → Wrong variance value
- �� Option D → Overestimated variance
Used
- Substitution
Application: Apply variance identity then root
Final Logic: Compute exact variance before SD
"Square mean first, then subtract"
