Special Issue on Survey Sampling

In statistics, survey sampling refers to the process of a sample of elements is selected from a target population to conduct a survey. It is important to determine the right kind and number of a participant in a sample group, which is one of the basic steps in conducting surveys. Sampling methods can be classified as probability and non-probability. Probability methods include random sampling, stratified sampling, cluster sampling, multistage sampling and systematic sampling. Non-probability methods include convenience sampling, judgment sampling, quota sampling and snowball sampling.

The goal of this special issue is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in the area of research on the survey sampling.

In this special issue, we intend to invite front-line researchers and authors to submit original research and review articles on exploring survey sampling. Potential topics include, but are not limited to:

• Selecting target population
• Basic sampling techniques
• Calculating appropriate sample size
• Probability vs. non-probability sampling methods
• Estimation process in survey sampling
• Statistical analysis of sample survey data
• Sampling error and confidence interval in survey sampling

Authors should read over the journal’s For Authors carefully before submission. Prospective authors should submit an electronic copy of their complete manuscript through the journal’s Paper Submission System.

Please kindly specify the “Special Issue” under your manuscript title. The research field “Special Issue – Survey Sampling” should be selected during your submission.

According to the following timetable:

Guest Editor:

For further questions or inquiries

Please contact Editorial Assistant at

ojs@scirp.org