It is when you specifically choose the people that you "sample", in order to collect data about them. (As opposed to picking numbers representing people out of a hat, etc... ). For example, if you wanted to collect some sort of data from every male currently living within the same postcode as yourself, that would be nonrandom.
"Non-random" varies a lot depending on what you're actually sampling. What would be "random" in one context can be "nonrandom" in another.
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
Sampling and Non sampling errors
Random Sampling
There are several types of random sampling, with the most common being simple random sampling, stratified sampling, cluster sampling, and systematic sampling. Simple random sampling gives each member of the population an equal chance of being selected. Stratified sampling involves dividing the population into subgroups and sampling from each subgroup. Cluster sampling selects entire groups or clusters, while systematic sampling involves selecting members at regular intervals from a randomly ordered list.
simple random, stratified sampling, cluster sampling
nonrandom or not random or precisely
Me and You
nonrandom or not random or precisely
nonrandom or not random or precisely
none
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
Answer is Quota sampling. Its one of the method of non-probability sampling.
Sampling techniques in researching involves to types of sampling. The probability sampling and the non-probability sampling. Simple random is an example of probability sampling.
You are correct; convenience sampling is not random sampling.
1) Simple random sampling 2) Systematic sampling 3) Stratified sampling 4) Cluster sampling 5) Probability proportional to size sampling 6) Matched random sampling 7) Quota sampling 8) Convenience sampling 9) Line-intercept sampling 10) Panel sampling
It is a form of nonrandom sampling. In essence it means obtaining observations that are easiest to get. For example, asking your friends how they plan to vote would be a political poll based on a convenience sample. Many types of formal, probability statistics are meaningless when convenience sampling is done. The researcher cannot claim to "generalize" their findings to any particular population. You probably could not accurately (i.e., within a couple percentage points) predict an election result based only on what your friends say. Therefore most typical statistical studies would avoid convenience sampling. It may be very useful for qualitative studies, but less so for quantitative work.
Sampling and Non sampling errors