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Why systematic sampling is not good for periodic data?
It checks bias in subsequent selections of samples
What are the causes of non-sampling errors?
non response, in accurate response and selection bias
When you sample with replacement are the trials independent?
They are, if the sampling and replacement processes don't introduce any bias.
Is there any Advantages of simple random sampling?
Cheap, simple, easily applied to a small population ensures bias is not introduced
How to reduce sampling error?
The only way to get rid of sampling error is to use the entire population under study. This is usually impossible, so the next best thing is to use large samples and good sampling methods.
What can be done to reduce bias in sampling?
The thing that can be done to reduce bias is sampling random things
Advantages and disadvantages of simple random sampling?
advantages: reduce bias easy of sampling disadvantages: sampling error time consuming
What is the difference between Sampling error vs sampling bias?
Sampling error leads to random error. Sampling bias leads to systematic error.
What are the major source of sampling error?
The major source of sampling error is sampling bias. Sampling bias is when the sample or people in the study are selected because they will side with the researcher. It is not random and therefore not an adequate sample.
How can a scientist reduce bias in a scientific investigation?
To reduce bias in a scientific investigation, a scientist can use randomization in sampling, blind studies, and double-blind studies. Randomization helps to minimize selection bias, while blind studies prevent participants from knowing which group they are in, reducing response bias. In double-blind studies, both the participants and the researchers are unaware of who is receiving the treatment, further minimizing bias.
What is intentional Bias?
Unintentional bias means the source of the bias is in the data collection or sampling method. Its not done purposefully, but rather ignorantly.
Which sampling would be apporiate to survey 120000 people?
A random sampling technique, such as simple random sampling or stratified random sampling, would be appropriate for surveying 120,000 people to ensure each person in the population has an equal chance of being selected. These techniques help reduce bias and ensure the sample is representative of the population as a whole.
What is bias sample?
Sampling bias occurs when the sampling frame does not reflect the characteristics of the population which is being tested. Biased samples can result from problems with either the sampling technique or the data-collection method. Essentially, the group does not reflect the population which is supposed to be represented in the given survey or test. For example: If the question being asked in a survey was "do American's prefer Coca-Cola or Pepsi?" and all people asked were under 18 and from California, there would be a sampling bias as the sampling frame would not accurately represent "American's".
What is the difference between the sample mean and the population mean known as?
Sampling bias.
Sampling error refers to?
Sampling error occurs when the sampling protocol does not produce a representative sample. It may be that the sampling technique over represented a certain portion of the population, causing sample bias in the final study population.
What are the different advantages of Sampling?
Sampling allows researchers to collect data from a smaller subset of a population, saving time and resources. It can provide insights into the characteristics of a larger population without having to survey everyone. Additionally, sampling can reduce bias in data collection and improve the overall quality of research findings.
Why systematic sampling is not good for periodic data?
It checks bias in subsequent selections of samples
