Course: SAMPLING THEORY
In systematic sampling, we use the same formula for finding a sample size as when we are dealing with a simple random sample. What are the consequences of doing this? Make sure to comment on each population type.
Systematic sampling is more easier than simple random sampling and it will give more correct information because it will contain every type of data present in the sample. And in random sampling by mistake we can pick same type of data from population.
Systematic sampling:we need to arrange the given data in an order and then pick every nth value. e. g. Suppose you want to know the everage age from a village. You sample 100 people and ask for their age. In order to do so you can collect a list naming all persons in village and then select every 20th person and ask their age. In this sampling you should have knowledge of population size in advance.
Simple random sampling: In this method you have to pick any n(sample size) people randomly. Here is no need to know population size in advance.
Course: SAMPLING THEORY In systematic sampling, we use the same formula for finding a sample size...
Simple random sampling uses a sample of size n from a population of size N to obtain data that can be used to make inferences about the characteristics of a population. Suppose that, from a population of 58 bank accounts, we want to take a random sample of four accounts in order to learn about the population. How many different random samples of four accounts are possible?
Simple random sampling uses a sample of size n from a population of size N to obtain data that can be used to make inferences about the characteristics of a population. Suppose that, from a population of 60 bank accounts, we want to take a random sample of nine accounts in order to learn about the population. How many different random samples of nine accounts are possible?
Simple random sampling uses a sample of size n from a population of size N to obtain data that can be used to make inferences about the characteristics of a population. Suppose that, from a population of 60 bank accounts, we want to take a random sample of six accounts in order to learn about the population. How many different random samples of six accounts are possible?
Simple random sampling uses a sample of size from a population of size to obtain data that can be used to make inferences about the characteristics of a population. Suppose that, from a population of 75 bank accounts, we want to take a random sample of five accounts in order to learn about the population. How many different random samples of five accounts are possible?
CLUSTER SAMPLING WITH ESTIMATION Suppose a population of size N is divided into K- N/M groups of size M. We select a sample of size n -km the following way: » First we select k groups out of K groups by simple random sampling . We then select m units in each group selected on the first step by simple random sampling . The estimate of the population mean is the average Y of the sample. Let μί be the...
Suppose we use iid sampling to obtain a sample of size 16 from a normal population with standard deviation, sigma = 10. What is the probability that our sample mean will be within 2 of the population mean?
(1 point) For each problem, select the best response. (a) A simple random sample of size n is defined to be A. a sample of size n chosen in such a way that every unit in the population has the same chance of being selected. B. a sample of size n chosen in such a way that every set of n units in the population has an equal chance to be the sample actually selected. C. a sample of size...
1 point) For each problem, select the best response. (a) A simple random sample of size n is defined to be A. a sample of size n chosen in such a way that every unit in the population has a known nonzero chance of being selected. B. a sample of size n chosen in such a way that every unit in the population has the same chance of being selected. C. a sample of size n chosen in such a...
Would you agree to the statement on random sampling methods. Please explain why. In probability samples “each population element has a known (non-zero) chance of being chosen for the sample.” (StatTrek 2020). Some examples of probability samples are, simple random sampling, stratified sampling, cluster sampling, multistage sampling, and systematic random sampling. Simple random sampling is the population and sample consists of “N” objects, and an example is when people play the lottery. Stratified sampling is based on some type of...
Suppose we are interested in estimating the proportion of a population using a simple random sample of size n. i. State a suitable estimator of the population proportion as well as its sampling distribution. Mention any assumptions which you make. ii. Explain statistically how to determine the minimum sample size necessary to estimate a population proportion to within e units. iii. Provide a practical marketing example of a 95% confidence interval for a proportion. iv. Explain the purpose of the...