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Sample Survey Methods
Survey Sampling is defined as a method which is mainly concerned with the conduction of survey by selecting a specimen element from the target population. In statistics, it involves a questionnaire that is helpful to evaluate the behavior of people.
The main aim of survey sampling is to mitigate the time and cost of work that it would take to conduct a population survey. A process of estimating the whole target population is termed as census. Generally, survey is a type of opinion poll and survey sampling choose the members from the target population for performing the survey.
Three major elements of Survey Sampling are Sample Selection, Data Collection and Estimation. Survey Sampling can be divided into two types:
- Probability samples: Probability samples are that where the selection of the member depends on the known probability.
- Non-Probability Samples: in this sample, probability of any member being selected cannot be computed. Used of Non probability Samples depends on the non-random factor and researcher’s judgment. There are two types of Non-Probability Samples which including Voluntary Sample and Convenience Sample.
Survey Sampling Methods deals with the various concepts, viz. Estimator based on distinct units, Unequal probability sampling, Stratified sampling, Non-sampling errors, Errors in surveys, Randomized response technique, Cluster sampling, Stratified random sampling, Unbiased variance estimators, etc. Various imperative Software that used in the Survey Sampling Methods are listed below:
- R survey package
- SPSS Complex Samples
Sampling is very effective because it minimizes the cost and collection of data is faster than measuring the whole population. Various sampling techniques are as follows:
- Random Sampling: it provides the equivalent chance to member of the target population for being selected.
- Stratified Sampling: this sampling use “Stratum” to perform the task. It used at that place where members have at least one or more familiar attributes.
- Quota Sampling: work of this sampling depends on the two steps. First, state a list according to the quotas which include education, gender, income or age and second one is to collect the information about the members that have same attributes.
- Convenience Sampling: this method is used at that place where only come of the members is eligible to become the participants in the survey.
- Purposive Sampling: in this sampling, researcher firstly set the criteria then picked the members according to it.
Cluster Sampling is a type of probability sample which is mainly used in the marketing research. It occurs when diverse groups appears in the statistical population. Main purpose of this sampling is to reduce the cost and enhance the efficiency of sampling. It enables one to acquire the information from more than one area, so sometimes it is also known as Area Sampling.
Multistage Sampling uses the smaller units to execute the sample frames. It is known as the complex form of Clustering Sampling because for selecting a simple sample, it needs to perform two or three stages. To make the data collection of entire population feasible, it divides the large cluster into various small stages. One of the major advantages of this sampling is that it enables the user to search the survey sample easily. But it doesn’t provide the accurate result all the time.
Moreover, Systematic sampling is defined as a part of Probability Sample which selects the elements from the sequential sampling frame. These samples are easy to create, understand and execute. Main advantage of this sampling is that sampling frame doesn’t require to be assembled before the occurrence of event.
Network sampling is used at that place where only some population is interested in the survey research. This sampling acts as an essential sampling for the analysis of information, biological and social networks. There are two main approaches that involved in a survey with an unspecified population are Screening and Salting. In salting, sample units obtained from the documents and records. Both approaches have some limitations. Screening needs expensive costs and Salting finds difficulties with the membership information because these records can be personal.
Snowball sampling which is also known as Chain-Referral Sampling is used at the place where the features of the simple sampling are difficult to find. This technique is useful for researchers as they used it that place where they needs to find out the hidden population. This sampling is widely used in the business studies where it mainly focuses on gathering the data from the employees of the company. To start the collection process in this is require only small planning and it collects the data in cost-effective manner.
Randomized response technique generally refers to a method which is mainly use in the survey interview. It is a research method which enables respondents to respond on the sensitive matter. Major four variants that involve in this technique are:
- Telephone number
- Manual coin toss
- Backnote Serial number
- Electronic coin toss
Beside the upper explained topics, Survey Sampling Methods includes the many other advanced topics such as Ratio estimator, Regression estimator, Non sampling error, Ratio type estimator, product estimator, Single double and sequential sampling plans, Horvitz –thompson estimator, Warner's Model, Pps sampling, Double sampling, Estimation of bias, and many more. With these topics, there are some more advanced topics that also take place in the Survey Sampling Methods fields:
- Ordered and unordered estimators
- Sampling strategies
- πPS Sampling
- Sampling with varying probabilities
- Horvitz – Thompson estimator
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Online Sample Survey Methods Assignment help tutors help with topics like Interpenetrating Subsamples, Estimation of Means and Totals over Subpopulations, Random-Response Model, Use of Weights in Sample Surveys, Adjusting for Nonresponse, Imputation, Selecting the Number of Callbacks, Bootstrap, Fundamentals of Survey Methodology, survey methodology, Steps of the process of a survey, concepts and principles of survey quality.
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Topics like Gaining the cooperation of sample units, Monitoring the progress of data collection, Response rates, Post-Survey Processing, Estimation, Editing data, Coding, Imputation, Construction of unit weights, Variance estimation, Analysis of survey data, Statistical Methods for Sample Surveys, sampling frames, area sampling, methods of estimation, stratified sampling, subsampling, sampling methods for surveys of human populations, designs and analyses of survey data & the assignment help on these topics is really helpful if you are struggling with the complex problems.
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