Podcast
Questions and Answers
What is the purpose of selecting a sample?
What is the purpose of selecting a sample?
- To collect data about the entire population
- To collect data to answer a research question about a population (correct)
- To estimate population characteristics without any errors
- To select elements from a process
What is a frame in the context of sampling?
What is a frame in the context of sampling?
- A subset of the population
- A set of all the elements of interest
- A list of all elements in a population
- A list of the elements that the sample will be selected from (correct)
What is the primary reason for using sampling distributions?
What is the primary reason for using sampling distributions?
- To eliminate the need for sampling
- To provide good estimates of population characteristics (correct)
- To estimate population characteristics with no error
- To provide exact values of population characteristics
What is stratified random sampling?
What is stratified random sampling?
What is cluster sampling?
What is cluster sampling?
What is systematic sampling?
What is systematic sampling?
What does the sampling distribution of x represent?
What does the sampling distribution of x represent?
In the context of sampling distributions, what does E(p) = p represent?
In the context of sampling distributions, what does E(p) = p represent?
What is used to make inferences about the value of p in sampling distributions?
What is used to make inferences about the value of p in sampling distributions?
When can the sampling distribution of p be approximated by a normal distribution?
When can the sampling distribution of p be approximated by a normal distribution?
Which sampling method involves dividing the population into subgroups and then taking random samples from each subgroup?
Which sampling method involves dividing the population into subgroups and then taking random samples from each subgroup?
In cluster sampling, how are clusters selected from the population?
In cluster sampling, how are clusters selected from the population?
What is the purpose of ensuring that the targeted population and the sampled population are in close agreement in sampling?
What is the purpose of ensuring that the targeted population and the sampled population are in close agreement in sampling?
What does the sampling distribution of x represent?
What does the sampling distribution of x represent?
In point estimation, what does E( x ) = μ signify?
In point estimation, what does E( x ) = μ signify?
What does σx represent in the context of sampling distributions?
What does σx represent in the context of sampling distributions?
When is a finite population treated as infinite in calculating σx?
When is a finite population treated as infinite in calculating σx?
What is the purpose of the finite population correction factor (N - n)/(N - 1) in calculating σx?
What is the purpose of the finite population correction factor (N - n)/(N - 1) in calculating σx?
Study Notes
Introduction to Sampling
- A population is the set of all elements of interest.
- A sample is a subset of the population.
- An element is the entity on which data are collected.
- A frame is a list of the elements that the sample will be selected from.
- The reason we select a sample is to collect data to answer a research question about a population.
Sampling Distribution of x
- The sampling distribution of x is the probability distribution of all possible values of the sample mean x.
- Expected Value of x: E(x) = μ
- The value of x is used to make inferences about the value of μ.
- Standard Deviation of x: σx = σ / √n (for infinite population)
- σx = (σ √(N - n)) / (n √(N - 1)) (for finite population)
- The finite population correction factor is (N - n) / (N - 1).
- A finite population is treated as being infinite if n/N < 0.05.
Example of Sampling Distribution of x
- For a sample size of 100, the standard error of the mean is smaller, and the values of x have less variability and tend to be closer to the population mean than the values of x with a sample size of 30.
Sampling Distribution of p
- The sampling distribution of p is the probability distribution of all possible values of the sample proportion p.
- Expected Value of p: E(p) = p
- The value of p is used to make inferences about the value of p.
- Standard Deviation of p: σp = √(p(1 - p)) / √n (for infinite population)
- σp = √(p(1 - p) * (N - n)) / (n √(N - 1)) (for finite population)
- The sampling distribution of p can be approximated by a normal distribution whenever the sample size is large.
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Description
Test your knowledge on sampling methods, point estimation, and sampling distributions as covered in Chapter 7 of the book 'Contemporary Business Statistics, 3e'. This quiz includes questions on selecting samples, introduction to sampling distributions, and more.
