Table of Contents
What is Sampling Error?
Sampling error is the variability of the estimates due to the random selection of the units in the sample. The variability of the estimates is measured by the standard error.
Sampling Error Definition
It is the difference between the results of a study and the results that would have been obtained if the study had been conducted using a different sample of people. However sampling error can be caused by many factors, including the selection of a biased sample or the use of a flawed questionnaire.
What is Sampling and Sampling Error?
Sampling is the process of selecting a subset of a population in order to study it. The goal of sampling is to obtain information about the population that would not be possible if the entire population were studied.
There are two types of errors that can occur in sampling: sampling error and non sampling error. Sampling error is the error that results from the selection of a sample rather than the entire population. Non sampling error is the error that results from any factor other than the selection of a sample.
Key Takeaways
- Bitcoin is a digital asset and a payment system invented by Satoshi Nakamoto.
- Transactions are verified by network nodes through cryptography and recorded in a public dispersed ledger called a blockchain.
- Bitcoin is unique in that there are a finite number of them: 21 million.
- Over 17 million bitcoins are in circulation as of February 2019.
- Bitcoin used to purchase goods and services, as well as store value.
- The price of bitcoin determined by supply and also demand.
- Bitcoin not backed by a government or central bank, and its value is highly volatile.
Sampling Error Meaning
Sampling error is the difference between the results of a study and the actual population value. Therefore this can be caused by the method of sampling used, the size of the sample, or the variation in the population.
The Role of Sample Size
The size of the sample has a significant impact on the precision of the estimate. The larger the sample size, also more precise the estimate will be.
Formula for Sampling Error
The sampling error for a statistic is the error that results from using a sample to estimate a population parameter. Therefore the sampling error is the difference between the sample statistic and the population parameter.
Step by Step Calculation of Sampling and Sampling Error
Sampling Error Formula
The sampling error is the difference between the value of the population and the value of the sample. However it calculated by taking the standard deviation of the sample.
Sampling Error = Standard Deviation of the Sample
How can Sampling Error Corrected?
There are a few ways to correct sampling error:
1. Increase the sample size. This will decrease the variability of the sample and make it more representative of the population.
2. Use a random sampling method. This will help ensure that the sample is representative of the population.
3. Use a stratified sampling method. Therefore this will help ensure that the sample is representative of the population by dividing it into strata (groups) and selecting a sample from each stratum.
Questions to Solved (Sampling Error Example)
1. What is the margin of error for a 95% confidence interval for the proportion of Republicans in the sample?
2. What is the margin of error for a 95% confidence interval for the proportion of Democrats in the sample?
3. What is the margin of error for a 95% confidence interval for the difference between the proportions of Republicans and Democrats in the sample?
Common mistakes to avoid on Sampling Errors
1. Assuming that the sampled population is representative of the entire population.
2. Not accounting for the sampling bias.
3. Choosing a convenience sample instead of a random sample.
4. Drawing conclusions from a small sample size.
5. Drawing conclusions from a non-random sample.
