non response, in accurate response and selection bias
A systematic error. This may arise because the measuring instrument is not properly calibrated or because there is a bias in recording the results.
Sampling and Non sampling errors
Pros and Cons of a non-probability sampling
the difference is just that non-probability sampling does not involve random selection, but probability sampling does.
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.
Both. But sampling error can be reduced through better design.Both. But sampling error can be reduced through better design.Both. But sampling error can be reduced through better design.Both. But sampling error can be reduced through better design.
non response, in accurate response and selection bias
yes
I believe you are considering the sampling error as calculated from data. I will give you some examples: If you get the exactly same response from all participants in a survey, you will calculate zero sampling error. For example, if I ask 10 people if Obama Barack is the President of the US, I would probably get 10 "yes" responses. Now the answer was well known, so I would expect very few "no" response. If your measurements are not very sensitive or are recorded with a lack of precision, then there can be zero sampling error. For example, I take the body temperature of students at the college and consider any temperature from 97 to 99 degree F to be normal. I find all students in my sample have normal temperatures. So, zero sampling error can occur because a) sample is small, b) variation in response is either non-existent or very small. In theoretical calculations, where sample error is based on the probability distribution of the population, one can calculate for discrete variables, the probability that a sample error will be zero.
ome suggested ways: Larger samples, Better sample design, Better measurement, Better data validation, Better survey/questionnaire design.
A systematic error. This may arise because the measuring instrument is not properly calibrated or because there is a bias in recording the results.
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)
There are several advantages of sampling over census (i.e. selection of wholepopulation for analysis).Firstly, the costs on sampling should be much lower than that on census. For example,for the government by-census (note: population census is usually conducted onceevery ten years and a by-census is conducted in the middle of the intercensal period),one fifth of the population is large enough to declare what the government wants toknow. There is no need to spend several times of dollars to interview the entirepopulation in the society.Secondly, a quality guru (Deming, 1960) argued that the quality of a study was oftenbetter with sampling than with a census. He suggested that, "Sampling possesses thepossibility of better interviewing(testing), more thorough investigation of missing,wrong , or suspicious information, better supervision, and better processing than ispossible with complete coverage". Research findings substantiate this opinion. Morethan 90% of survey error in one study was from non-sampling error1, and 10% or lesswas from sampling error2. (Donald et al., 1995)Thirdly, sampling can save the time. The speed of execution reduces the time betweenthe recognition of a need for information and the availability of that information.1 Non-sampling error is the error of research due to factors other than the sample size and samplingmethod, including non-response, bad communication with interviewees, measurement error, etc.2 Sampling error is the error during research due to the sample size and sampling method.
Answer is Quota sampling. Its one of the method of non-probability sampling.
Sampling and Non sampling errors
Non probability sampling is where the samples are not selected randomly.