Sampling, recruiting, and retaining diverse samples. Each of the sampling techniques described in this chapter has advantages and disadvantages. The primary goal of sampling is to get a representative sample, or a small collection of units. Random sampling refers to a variety of selection techniques in which sample members are selected by chance, but with a known probability of selection. Sampling has always been discussed on the basis of one classification. Simple random sampling is an effective, low resource consuming method of sampling that can be used in a variety of situations as a reliable sampling method. For instance, to draw a simple random sample of 100 units, choose one unit at random from the frame. Pdf as an estimator of the population mean, the sample mean.
If you want to produce results that are representative of the whole population, you need to use a probability sampling technique. Simple random sampling in an ordered systematic way, e. Sampling provides an uptodate treatment of both classical and modern sampling design and estimation methods, along with sampling methods for rare, clustered, and hardtodetect populations. Proportional allocation is used when the sample size from different stratum will be kept proportional to the strata size. Roy had 12 intr avenous drug injections during the past two weeks. Simple random sampling methods of drawing a random sample. A manual for selecting sampling techniques in research.
However, the difference between these types of samples is subtle and easy to overlook. With probability sampling,a researcher can specify the probability of an elements participants being included in the sample. Every unit of population does not get an equal chance of participation in the investigation. Random selection of 20 students from class of 50 student. With nonprobability sampling, there is no way of estimating the probability of. This work is licensed under a creative commons attribution. Learn more with simple random sampling examples, advantages and disadvantages.
If sampling for attributes then read off the sample size for the population proportion and. This chapter begins with a discussion of selecting a simple random sample. Often what we think would be one kind of sample turns out to be another type. This can be seen when comparing two types of random samples. Every element has an equal chance of getting selected to be the part sample. This method carries larger errors from the same sample size than that are found in stratified sampling. Simple random sampling is the most basic and common type of sampling method used in quantitative social science research and in scientific research generally.
The sample was drawn by a simple random sampling method, which eliminates the bias by giving all individuals an equal chance to be chosen. It is also considered as a fair way of selecting a sample from a given population since every member is given equal opportunities of being selected. Hence the sample collected through method is not random in nature. Simple random sampling works best when you can manage a small percentage of the overall demographic. In simple random sampling each member of population is equally likely to be chosen as part of the sample. The entire process of sampling is done in a single step with each subject selected independently of the other members of. History of sampling contd dates back to 1920 and started by literary digest, a news magazine published in the u. Use simple random sampling equations for data from each stratum.
Simple random sampling suffers from the following demerits. Every member of the population is equally likely to be selected. In the absence of data on the subject, a decision taken is just like leaping into the dark. Random sampling refers to a variety of selection techniques in which sample members are selected by. To resolve this disparity between statistical theory and practice, the variance formulas used in simple random sampling are changed somewhat. Simple random sampling srs is a method of selection of a sample comprising of n number of sampling units out of the population having n number of sampling units such that every sampling unit has an equal chance of being chosen. A simple random sample and a systematic random sample are two different types of sampling techniques. In the section which sampling technique to use in your research, it has been tried to. A practical guide to sampling national audit office. A sampling frame is a list of the actual cases from which sample will be drawn.
Ch7 sampling techniques university of central arkansas. Most social science, business, and agricultural surveys rely on random sampling techniques for the selection of survey participants or sample units, where the sample units may be persons. Simple random sampling is a type of probability sampling technique see our article, probability sampling, if you do not know what probability sampling is. The next step is to create the sampling frame, a list of units to be sampled. Simple random sampling is a statistical tool used to describe a very basic sample taken from a data population. A sample of 6 numbers is randomly drew from a population of 2500, with each number having an equal chance of being selected.
Thus the rst member is chosen at random from the population, and once the rst member has been chosen, the second member is chosen at random from the remaining n 1 members and so on, till there are nmembers in the sample. Simple random sampling must endure the same overall disadvantage that every other form of research encounters. Unlike simple random sampling, there is not an equal probability of. Random sampling is a part of the sampling technique in which each sample has an equal probability of being chosen. Like simple random sampling, systematic sampling is a type of probability sampling where each element in the population has a known and equal probability of being selected. With the simple random sample, there is an equal chance probability of selecting each unit from the population being studied when creating your sample see our article, sampling. This sample represents the equivalent of the entire population.
A manual for selecting sampling techniques in research munich. List all the clusters in the population, and from the list, select the clusters usually with simple random sampling srs strategy. Sampling methods chapter 4 divides the population into preexisting strata simple random sampling is applied to each strata only those participants selected are included in the study ensures that members of each identified group are included in the sample example. Although there are distinct advantages to using a simple. Unlike other forms of surveying techniques, simple random sampling is an unbiased approach to garner the responses from a large group. It is also the most popular method for choosing a sample among population for a wide range of purposes. Simple random sampling srs occurs when every sample of size n from a population of size n has an equal chance of being selected. Simple random sampling in the simple random sampling method, each unit included in the sample has equal chance of inclusion in the sample.
This technique provides the unbiased and better estimate of the parameters if the population is homogeneous. It is also the most popular way of a selecting a sample because it creates samples that are very highly representative of the population simple random is a fully random technique of selecting subjects. Random sampling is one of the most popular types of random or probability sampling. Failed in 1936 the literary digest poll in 1936 used a sample of 10 million, drawn from government lists of automobile and telephone. Sampling techniques basic concepts of sampling essentially, sampling consists of obtaining information from only a part of a large group or population so as to infer about the whole population. Sampling wiley series in probability and statistics. Methods in sample surveys simple random sampling systematic sampling lecture 2. Probability sampling means that every member of the population has a chance of being selected. Simple random sampling srs provides a natural starting point for a discussion of probability sampling methods, not because it is widely usedit is notbut because it is the simplest method and it underlies many of the more complex methods.
Simple random sampling, advantages, disadvantages mathstopia. As a prelude to defining simple random sampling, we will introduce the notation that the sample size is given by n and the population size by n. Simple random sampling is defined as a technique where there is an equal chance of each member of the population to get selected to form a sample. In simple random sampling, a researcher develops an accurate sampling frame, selects elements from the sampling frame. General strengths of random sampling proper use of random sampling generates a sample more likely to be representative of the targeted population than any other method assumes reasonably high and similar rates of successful recruitment for all segments of.
This is the purest and the clearest probability sampling design and strategy. Pros of simple random sampling one of the best things about simple random sampling is the ease of assembling the sample. It is used when we dont have any kind of prior information about the target population. In this technique, each member of the population has an equal chance of being selected as subject. With the advent of computers, the problems associated with this method can be even reduced because a computer can be used to generate the samples based on an algorithm that generates the. The three will be selected by simple random sampling. All units elements in the sampled clusters are selected for the survey. Both give rise to simple random sampling see also part ii. A survey of the presidents popularity is conducted across racial groups. Convenience sampling 21 and simple random sampling techniques 22. This means that it guarantees that the sample chosen is representative of the population and.
Pdf the nature of simple random sampling researchgate. Digest successfully predicted the presidential elections in 1920, 1924,1928, 1932 but. Simple random sampling researchers use two major sampling techniques. The discussion assumes that sampling is performed without replacement. Population divided into different groups from which we sample randomly. Simple random sampling a simple random sample is one in which each element of the population has an equal and independent chance of being included in the sample i. The following sampling methods belong to a class known as probability samples. To compare the difference for the strata, selecting equal. This third edition retains the general organization of the two previous editions, but incorporates extensive new materialsections, exercises, and.