Types of sampling design pdf

Empirical Example 1 6. Mental Gymnastics 2 Sampling Design 1. Type of universe 2. Source list or sampling frame 4.

Parameters of interest 6. Note: o Statistic: numerical characteristic of a sample o Parameter: numerical characteristic of a population 15 16 Characteristics of a Good Sample Design? Characteristics of a Good Sample Design? Simple Random Sampling, i. Quota sampling ii. SlideShare uses cookies to improve functionality and performance, and to provide you with relevant advertising.

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Next SlideShares. You are reading a preview. Create your free account to continue reading. Sign Up. Upcoming SlideShare. It is more or less impossible to study every single person in a target population so psychologists select a sample or sub-group of the population that is likely to be representative of the target population we are interested in.

This is important because we want to generalize from the sample to target the population. The more representative the sample, the more confident the researcher can be that the results can be generalized to the target population.

One of the problems that can occur when selecting a sample from a target population is sampling bias. Sampling bias refers to situations where the sample does not reflect the characteristics of the target population. The population or universe embodies the entire group of units which is the centre of the study.

Thus, the population could consist of all the persons in the country, or those in a particular topographical position, or a special cultural or economic group, depending on the rationale and exposure of the study. Thus, it is a total set of elements persons or objects that share some common features defined by the sampling criterion established by the researcher.

A sample is the group of units who took part in research. Generalisability refers to the degree to which we can correlate the findings of our research to the target population we are concerned. This population is a split or subset of the target population and is also known as the study population. It is from the accessible population that researchers draw their samples.

Sample Group or Sampling. It is the most bias thing in the universe from which data is to be collected. For example, in a study proposed for assessing the violation of human rights among hand-rickshaw pullers in the city 8. Herein, the universe will be the entire body of rickshaw pullers in Kolkata. In some studies more than one sample is drawn out of the universe for making a sound research.

Size of the sample is the total number of sampling units that the researcher will include in the sample. The size of the sample should not be vast as the purpose of studying the sample and not the universe will be lost. Similarly, the sample size cannot be too small either for it will not adequately represent the universe. Such a sample is called a biased sample. It is pertinent for the researcher to be aware and make sure that his samples are not biased, to avoid error in sampling.

It is customary for the researcher to mention the research loopholes that led to the result. While sampling errors can be predicted quite precisely as they can be calculated, the non-sampling errors can only be guessed or assumed by the researcher. Sampling errors arise due to wrong selection of samples and can be avoided is the researcher is cautious in choosing the sampling technique.

Non-sampling errors arise in the pre or post sampling process of a research. Some common sampling methods are simple random sampling,stratified sampling, cluster sampling, quota or judgment. Different sampling methods may use different estimators. For example, the formula for computing a mean score with a simple random sample is different from the formula for computing a mean score with a stratified sample. Similarly, the formula for the standard error may vary from one sampling method to the next.

The best sample design is dependent upon survey objectives and on survey resources. For example, a researcher might select the most economical design that gives a required level of accuracy.

Or, if the resources are limited, a researcher might select the design that gives the greatest accuracy without going over financial plan. Characteristics of a good Sample Design: In a field study due to time constraint and finance involved, generally, only a section of the population is considered.

These respondents are identified as the sample and are representative of the general population or universe. A sample design is a predetermined plan for getting a sample from a population. It refers to the method or the process for obtaining a sample from a given population.

This sample is required to match all the features of the entire population. If the sample Sampling error refers to the difference that may result from judging all on the basis of a small number. Research Methodology Tutorial. Job Recommendation Latest. Jobs in Meghalaya Jobs in Shillong. View All Locations. How to design your resume?

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