Sampling Distribution
Chapter notes, video classes, MCQ practice tests and quick-revision one-liners for Advanced Bank Management — CAIIB.
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What is a sampling distribution?
A sampling distribution is the probability distribution of a given statistic (such as the sample mean) based on a large number of samples drawn from a specific population.
What is the sampling distribution of the sample mean?
Probability distribution of means from all possible samples of size n
What is the Central Limit Theorem (CLT) and why is it important in banking?
The CLT states that the sampling distribution of the sample mean approaches a normal distribution as sample size increases, regardless of the population's shape. This allows banks to make reliable inferences from large loan or transaction datasets.
What is the shape of the sampling distribution when population is normally distributed?
Always normal, regardless of sample size
What is the standard error of the mean?
The standard error of the mean is the standard deviation of the sampling distribution of the sample mean, calculated as σ/√n, where σ is the population standard deviation and n is the sample size.
What is the variance of the sampling distribution of the mean?
Population variance divided by sample size (σ²/n)
How does increasing sample size affect the standard error?
Increasing sample size decreases the standard error, making the sample mean a more precise estimate of the population mean, which is critical for accurate risk assessment in banking.
What is the standard error of the proportion?
Square root of p(1-p)/n
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