0
Suppose that a population that a population has mean equals 64 and standard deviation equals 18. A sample of size 36 is selected. What is the mean of the sampling distribution of means?
Wiki User
∙ 13y ago
64.
Wiki User
∙ 13y ago
Add your answer:
Earn +20 pts
Example of stratified random sampling?
In stratified sampling, the population to be sampled is divided into groups (strata), and then a simple random sample from each strata is selected. For example, a state could be separated into counties, a school could be separated into grades. These would be the 'strata'.
What are the principles of random sampling?
Each member of the population must have the same probability of being included in the sample. Equivalently, each set of elements comprising a sample must have the same probability of being selected.
Are normally distributed with a mean of 68 inches and a standard deviation of 2 inches What is the probability that the height of a randomly selected female college basketball player is more than 66?
84% To solve this problem, you must first realize that 66 inches is one standard deviation below the mean. The empirical rule states that 34% will be between the mean and 1 standard deviation below the mean. We are looking for the prob. of the height being greater than 66 inches, which is then 50% (for the entire right side of the distribution) + 34%
When individuals all have an equal chance of being selected and all samples have an equal chance of being selected its called a stratified random example convenience cluster or simple random sample?
Simple random sampling.
What is the difference between convenience judgment and random sampling?
Non-probability or Judgement Samples has to do with a basic researcher assumptions about the nature of the population, the researcher assumes that any sample would be representative to the population,the results of this type of samples can not be generalized to the population(cause it may not be representative as the research assumed) and the results may be biased. Probability or Random samples is a sample that to be drawn from the population such that each element in the population has a chance to be in the selected sample the results of the random samples can be used in Statistical inference purposes
The standard error of the mean is the standard deviation of the sampling distribution of the sample mean?
a large number of samples of size 50 were selected at random from a normal population with mean and variance.The mean and standard error of the sampling distribution of the sample mean were obtain 2500 and 4 respectivly.Find the mean and varince of the population?
What is probability sampling and non probability sampling?
In probability sampling,every item in the population has a known chance of being selected as a member.In non-probability sampling, the probability that any item in the population will be selected for a sample cannot be determined.
What is population sampling?
Population sampling is the process in which a group of individuals are selected to represent a population for the purpose of statistical analysis. Population sampling allows the analyzers to learn about a population without studying every individual in it.
When every member of a population has the chance of being selected based on the probability or frequency of its representation in that population you are using which type of sampling?
Systematic sampling
When every Member of a population has the chance of being selected based on probability what type of sampling is this?
Simple random sampling.
What is the definition of nonprobability sampling?
Non-probability sampling is a type of sampling technique whereby all the units of a population do not have an equal chance of being selected in the sample.it may further be divided intoConvenience: Sampling units are selected as per convenience of the researcherPurposive: The units selected in a sample are selected because they posses some requires characteristic e.g., clinical knowledge etc
What is The process of selecting representative elements from a population?
The process of selecting representative elements from a population is called sampling. Sampling involves selecting a subset of individuals or items from a larger group in order to draw conclusions or make inferences about the entire population. Various sampling techniques, such as random sampling or stratified sampling, can be utilized to ensure that the selected elements accurately represent the population characteristics.
Why is quota sampling different from other samplings?
Both being sub-parts of probability sampling, Random sampling differs in the sense as the sample is chosen out of a whole population randomly. whereas cluster sampling is extracted from a population already been selected by the same organization. eg. out of a whole population an area is selected by the management, which is the cluster, and is handed over to you to perform the tests necessary. Stratified sampling on the other hand is extracted according to the the categories the selected sample belongs to. These sectors selected might be on the basis of their nature of work, dealings etc. eg. industrial, commercial, residential and so on.
Sampling errors and non sampling errors?
Sampling Errors: differences between your sample and the actual population that come about as a result of the observations that happened to be selected for the sample; (in sampling a population, regardless of how hard you try, there will always be some deviation from your sample as compared to your population because your sample may be slightly different from your population)Non Sampling Error: differences due to mistakes in the acquisition of data or because of the improper formation of a sample.Errors in data acquisition: i.e. recording the wrong answer, measurements from faulty equipment, mistakes in transferring info from primary sources, or misinterpretation of questions/responses, etc.Non response errors: when people in the sample don't respond = no dataSelection bias: when sampling makes it highly unlikely that some people will be included in the sample (i.e. selecting only those who are in the phone book would eliminate the chances for someone who isn't in the phone book to be selected)
How does sampling becomes random?
When each member of the population has the same probability of being selected as a member of the sample.
The variation in the population as measured by the standard deviation has little or no effect in determining the size of a sample selected from the population True or False?
The answer is False
How can sampling error be reduced?
The best way to reduce sampling error is to use random sampling in the study. This means selecting the population to study through a random process. This will ensure that each member of the population under study has an equal chance of being selected.
