STA301 Final Term Current and Past Solved Questions
- Type
- Final term past paper
- Course
- STA301 Statistics and Probability
- Size
- PDF 1.1 MB
- Updated
- 23 Oct 2026
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2)If we draw a card from an ordinary deck of 52 cards. Can king and diamond be mutually exclusive events? Give reason to support your answer. No. " Mutually exclusive" means it could be one or the other, but not both. It's certainly possible to draw the king of diamonds (and be both), so they are not mutually
exclusive events.
Q3. Suppose that we toss a fair coin three times. What is its sample space?
If we draw a coin 3 time then sample space is 2^3 or 23 means 8 and sample space is {(H,H,H) (H,H,T) (H,T,H) (H,T,T) (T,H,H) (T,T,H) (T,T,T)}
Q4. Why we take B2 =3 as the criteria for measuring the kurtosis of any distribution?
Q5. Define level of significance?
Answer ; -
In statistics, a result is called statistically significant if it is unlikely to have occurred by chance
Q6. How we decide that the drawn sample is “Small sample” or a “large sample”?
3 Marks
7)If mean of a distribution is 0.925 and standard deviation is 0.132. Find out the limits by applying chebychev’s inequality for k=2. How much fraction of data will
lie between the twolimits?
Jal, read lecture # 12 for this but solve ker dia hay ☺,
For 1st inequality is 1-1/k For 2nd inequality it is 1-1/k2 And for 3rd it is 1-1/k3 Kyun k Question main unhain nay sirf k dia hua hay so it is 1st inequality and the formula for 1st inequality is 1-1/k = 1-1/2 = 1 Or es ko elaborate yun kerain gay
X kS X kS ab values put ker do bus es formula main
[0.925 (1)(0.132),0.925 (1)(0.132)] Abb es ko +, -, * tau ker lo gi aap bus darmyaan main jo , lga hay us ko lga rahnayd aina us ko kuch mat kerna ☺
8)If E(XY)=7.5, E(X)=2.4 and E(Y)=4.3, calculate covariance of X and Y.
Cov (X, Y) = E(XY) – E(X) E(Y).
Now put the values 7.4 – (2.4)(4.3) now multy ply and minus ☺
9)Hypothesis se question tha ? kon sa ☺
10)Z-test ka formula complete kerna tha ek(dun have math type to write)
Q11. Write down the two properties of sampling distribution of proportion p’, when the sampling is performed with replacement?
Property 1
The mean of the sampling distribution of proportions, denoted by µp is equal to the population proportion p, that is p p µ =
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