CAIIB · ABM · Chapter 2

Sampling Techniques

Chapter notes, video classes, MCQ practice tests and quick-revision one-liners for Advanced Bank Management — CAIIB.

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Q

What is a sampling distribution?

A

A sampling distribution is the probability distribution of a given sample statistic based on a random sample.

Q

What is the formula for the standard error of the mean when sampling WITHOUT replacement from a finite population?

A

σ_x̄ = (σ / √n) × √[(N − n) / (N − 1)], where N is population size and n is sample size

Q

What does the Central Limit Theorem guarantee about the sampling distribution of the sample mean?

A

The CLT guarantees that as sample size grows, the sampling distribution of the sample mean approaches normality regardless of the population's shape.

Q

What is the 5% rule for applying the Finite Population Multiplier (FPM)?

A

Apply FPM when the sampling fraction n/N ≥ 0.05 (i.e., you are sampling 5% or more of the population)

Q

What is the formula for the standard error of the mean?

A

The standard error of the mean is Sigma_x-bar = Sigma / sqrt(n), where Sigma is the population standard deviation and n is the sample size.

Q

What is the FPM value when a bank samples n = 50 accounts from a population of N = 500 accounts without replacement?

A

FPM = √[(500 − 50) / (500 − 1)] = √(450 / 499) = √0.9018 ≈ 0.9496

Q

What does the first statement of the CLT say about the mean of the sampling distribution of x-bar?

A

The mean of the sampling distribution of x-bar equals the population mean mu, expressed as E(x-bar) = mu.

Q

In the bank savings accounts example, if σ = ₹600 and n = 100, what is the standard error of the mean?

A

σ_x̄ = 600 / √100 = 600 / 10 = ₹60

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