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What is the difference between Sampling error and non sampling error?
In stats, a sampling error is simply one that comes from looking at a sample of the population in question and not the entire population. That is where the name comes from. But there are other kinds of stats errors. In contrast, non sampling error refers to ANY other kind of error that does NOT come from looking at the sample instead of the population. One example you may want to know about of a non sampling error is a systematic error. OR Sampling Error: There may be inaccuracy in the information collected during the sample survey, this inaccuracy may be termed as Sampling error. Sampling error = Frame error + Chance error + Response error.
How do you combine probability to non probability sampling?
There are many methods: stratified random sampling and cluster sampling are two examples. Suppose you have a school with 1000 pupil: 400 in the Junior school and 600 in the Senior school. You may wish to keep the sampling proportions in the two parts of the school the same. So if you wanted a sample of 5% = 50 pupils, you would take a probability or random sample of 5% = 20 from the Juniors and 5% = 30 from the Seniors. For the second example, imagine you want to sample 5% of all schools in the country. This could result in you spending lots of time and money travelling from place to place. Instead, you divide up the country into 100 regions - each containing the same number of schools. You then take a probability sample of 5% of these regions. In each of the regions you visit every school.
Is it a simple transformation of technology developed from databases statistics and machine learning?
No. Data mining is more than a simple transformation of technology developed from databases, statistics, and machine learning. Instead, data mining involves an integration, rather than a simple transformation, of techniques from multiple disciplines such as database technology, statistics, machine learning, high-performance computing, pattern recognition, neural networks, data visualization, information retrieval, image and signal processing, and spatial data analysis.
When to use t statistic instead of z statistic for calculating whether a parameter falls above or below the lower confidence interval?
the standard rule of thumb is to use the t-statistic when the sample size is less than 30 or if the population standard deviation is unknown/estimated from sampling data and to use the z-statistic for 30 and above.
Why do politicians simplify statistics?
Because people usually aren't clever enough to follow along precisely unless everything is made as clear as possible. That means saying things like "62% of drunk drivers" instead of "a mean of 61.63% of drivers with BAC above the legal limit in several studies" and "10% increase" instead of "9.82% above the limit from the period July to December". There's also a thing called spin-doctoring; making stuff sound as good as possible for your own side, or equivalently as bad as possible for any other side. Statistics, when simplified, can be misquoted very well and are perfect for being doctored in this fashion.
When is census necessary instead of sampling?
census is conducted for group data so if it is a sampling data is taken it would lead to lot of non sampling errors
What is differential statistics?
Differential statistics are statistics that use calculus. Normally statistics would use algebra but differential statistics uses calculus instead of algebra.
How do multistage sampling applies to real life situation?
Multistage sampling is a form of cluster sampling where instead of using the entire cluster, random samples from each cluster are used. This is typically used when doing opinion polls or surveys.
What is the difference between Sampling error and non sampling error?
In stats, a sampling error is simply one that comes from looking at a sample of the population in question and not the entire population. That is where the name comes from. But there are other kinds of stats errors. In contrast, non sampling error refers to ANY other kind of error that does NOT come from looking at the sample instead of the population. One example you may want to know about of a non sampling error is a systematic error. OR Sampling Error: There may be inaccuracy in the information collected during the sample survey, this inaccuracy may be termed as Sampling error. Sampling error = Frame error + Chance error + Response error.
What are the merits and demerits of sampling methods?
Advantages and Limitation of Sampling: 1. Sampling saves time and labour. 2. It results in reduction of cost in terms of money and manhour. 3. Sampling ends up with greater accuracy of results. 4. It has greater scope. 5. It has greater adaptability. 6. If the population is too large, or hypothetical or destroyable sampling is the only method to be used. The limitations of sampling are given below: 1. Sampling is to be done by qualified and experienced persons. Otherwise, the information will be unbelievable. 2. Sample method may give the extreme values sometimes instead of the mixed values. 3. There is the possibility of sampling errors.
Which is best defined as a literary and philosophical movement that placed emphasis on the spiritual world instead of the material or empirical world?
Transcendentalism
What are examples of incorrect sampling?
Incorrect sampling is when the wrong data or sample of something is taken or given during the testing or information gathering in a project, experiment, or work. Examples may include gathering soil samples instead of water samples.
What is log transformation in statistics?
Instead of using W as a variable in your model, you use log(W).
How can you draw a random sample?
Random sampling simply means the sample you chose from a population for a particular statistics must be random and not biased. One way is to have all names of the population to be randomly drawn by a computer system or a manual system (eg. drawing names from a fish bowl). Obtaining statistics information from a supermarket or from a particular group of social group is not random sampling as it is believe people of the same group has the same opinion. Eg. If you want to do a survey on how often people shop in Walmart, obtaining sample from Walmart shoppers is NOT random sampling because you are only doing survery on those who are already shopping in Walmart. Instead do random survery in a particular work environment unrelated to Walmart or door by door interview as this will allow access to a variety of people including those who never shop in Walmart (a data you cannot obtain from Walmart shoppers)
What would a sampling error of zero mean?
The sampling error is the error one gets from observing a sample instead of the whole population. The bigger it is, the less faith you should have that your sample represents the true value in the population. If it is zero, your sample is VERY representative of the population and you can trust that your result is true of the population.
When do you use sampling techniques?
If it is too time consuming and/or expensive to analyse the whole population of interest you can take a sample instead. If the survey is conducted using correct sampling techniques (e.g. randomised selection, adequate sample size, etc.) the survey can tell you just as much as basing your results on a census.
How is it possible to represent a complex exponential signal with a frequency of 20Hz using a sampling frequency of 30Hz?
A 20Hz signal must be sampled at a minimum of 40Hz to have a chance of sampling both peaks and to get a reasonable representation it must be sampled at a minimum of 100Hz.For a sampling rate of 30Hz the Nyquist frequency is 15Hz and since 20Hz is above that it will generate the alias signal of 10Hz in the sampled data instead of the original signal of 20Hz. Therefore it is not possible to do what you ask.
