Sampling Techniques In Data Science

___________ is the collection of the elements which has some or the other characteristic in common. Number of elements in the ___________ is the size of the _________.

_________ is the subset of the population. The process of selecting a ________ is known as sampling. Number of elements in the _________ is the _________ size.

Sampling is done to draw __________

Steps Involved in Sampling are:

Define Target population, Sampling Frame, Sampling Technique, and Sample Size.

Sampling techniques are grouped into two categories as:

___________ technique uses randomization to make sure that every element of the population gets an equal chance to be part of the selected sample. It’s alternatively known as random sampling.

Types of Probability Sampling are:

In _____________ Sampling: Every element has an equal chance of getting selected to be the part of the sample and it is used when we don’t have any kind of prior information about the target population.

Limitations of Simple Random Sampling are:

In ___________ sampling, the first individual is selected randomly and others are selected using a fixed ‘sampling interval’.

___________ divides the elements of the population into small subgroups (strata) based on the similarity in such a way that the elements within the group are homogeneous and heterogeneous among the other subgroups formed. Then the elements are randomly selected from each of these strata. We also need to have prior information about the population to create subgroups.

In ___________ sampling entire population is divided into clusters or sections and then the clusters are randomly selected. All the elements of the cluster are used for sampling. Clusters are identified using details such as age, sex, location etc. This type of sampling is used when we focus on a specific region or area.

Single Stage Cluster Sampling: We randomly select clusters and then from those selected clusters we randomly select elements for sampling. Two Stage Cluster Sampling: Entire cluster is selected randomly for sampling.

__________ Sampling is the combination of one or more methods described before. It is a combination of Simple Random sampling, Sampling Stratified sampling, Systematic sampling Cluster Sampling any of these sampling methods.

________ Sampling technique does not rely on randomization. This technique is more reliant on the researcher’s ability to select elements for a sample. The outcome of sampling might be biased and makes it difficult for all the elements of the population to be part of the sample equally. This type of sampling is also known as non-random sampling.

___________ Samples are selected based on the availability. This method is used when the availability of sample is rare and also costly. So based on the convenience samples are selected.

____________ is based on the intention or the purpose of study. Only those elements will be selected from the population which suits the best for the purpose of our study.

_________ sampling depends on some pre-set standard. It selects the representative sample from the population. The proportion of characteristics/traits in the sample should be the same as the population. Elements are selected until exact proportions of certain types of data are obtained or sufficient data in different categories is collected.

______________ also known as selective sampling. It depends on the judgment of the experts when choosing whom to ask to participate.

In _____________ Existing people are asked to nominate further people known to them so that the sample increases in size like a rolling snowball. This method of sampling is effective when a sampling frame is difficult to identify.