...| 2108 | Nonprobability sampling in management research ESS has made a survey created to measure attitudes cross-nationally in Europe, using probability sampling. Measuring an attitude across countries is a tough job, but to successfully apply the methods of probability sampling too, seems close to impossible. This essay will look at the sample-problems that this survey faces, and how a non-probability sample can be successfully integrated. Before starting to analyse the survey, I would like to briefly explain what a sample is, and the main differences between the two sampling techniques. First of all the objective of most surveys or research projects is to obtain information about the parameters of a population. To do this a sample is collected representing a subgroup of the population selected for participation in the project. The sample characteristics are used to “make inferences about the population parameters”. (Malhotra, 2010: 370) Meaning that you by selecting a small representation of the population can tell something about the whole population. Non-probability sampling can be defined briefly as “Sampling techniques that do not use chance selection procedures, but rather rely on personal judgement of the researcher” (Malhotra and Birks, 2000, 358) An example of this would be a person who choices people on the street to take part in a survey by using his personal judgement. There are different types of non-probability sampling, the most common are: Convenience...
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...Probability And Non Probability Sampling Cultural Studies Essay A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection. Probability sampling methods are those in which every item in the universe has a known chance, or probability of being chosen for sample. This implies that the selection of the sample items is independent of the person making the study that is the sampling operation is controlled so objectively that the items will be chosen strictly at random. Types of probability sampling Simple Random Sampling: The simplest form of random sampling is called simple random sampling. Neither of these mechanical procedures is very feasible and, with the development of inexpensive computers there is a much easier way. Simple random sampling is simple to accomplish and is easy to explain to others. Because simple random sampling is a fair way to select a sample, it is reasonable to generalize the results from the sample back to the population. Simple random sampling is not the most statistically efficient method...
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...explanation to an unexplained phenomenon to clarify the doubtful facts and to correct the misconceived facts. The term ‘Research’ should be used in a technical sense as an academic activity. (C.R Kothari, 2009 [58]) According to Clifford Woody Research consists of: • Defining and redefining problems. • Formulating hypothesis or suggested solutions. • Collecting, organising and evaluating data. • Making deductions. • And Reaching conclusions • Carefully testing the conclusions to determine whether they fit the formulating hypothesis. Characteristic of Research- (Research Methodology, 2007 [59]) • It is a systematic and important investigation. • Investigation is purposive and its object is to describe and explain a fact. • Appropriate scientific method is used. • It is objective and logical, undergoes possible test, uses measuring tools to validate and reach the findings or results. • Research is based on observation or empirical evidence. • Research is to find answers to some questions and solutions to the problem. • It emphasizes the development of generalization, principles or theories. • Purpose of research is not only to find conclusion but also to criticize the findings. 7.2 Research Approach (Sekaran, 2003 [60]) According to Sekaran there are two types of research approaches. • Inductive Research Approach • Deductive Research Approach • Inductive Approach (Specific to General Approach): Inductive Research happens when a researcher works moving from the specific observations...
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...SAMPLING: In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a population to estimate characteristics of the whole population. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. The sampling process comprises several stages: * Defining the population of concern * Specifying a sampling frame, a set of items or events possible to measure * Specifying a sampling method for selecting items or events from the frame * Determining the sample size * Implementing the sampling plan * Sampling and data collecting PROBABILITY AND NON-PROBABILITY SAMPLING: A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined. The combination of these traits makes it possible to produce unbiased estimates of population totals, by weighting sampled units according to their probability of selection. Non-probability sampling is any sampling method where some elements of the population have no chance of selection (these are sometimes referred to as 'out of coverage'/'under covered'), or where the probability of selection can't be accurately determined. It involves the selection of elements based on assumptions regarding the...
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...census, less costly to administer than a census and it is possible to obtain statistical results of a sufficiently high precision based on samples. There are two types of sampling techniques, probability and non-probability sampling. Probability Sampling A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection. To produce our results, we combine the responses from the sample in a way which takes account of the selection probabilities. Our aim is that, if the sampling were to be repeated many times, the expected value of the results from the repeated samples would be the same as the result we would get if we surveyed the whole population. Because we know the probability of getting each sample we select, we can also calculate a sampling error for the results. The sampling error tells us the amount of variation in the results due to the sampling alone. It gives a measure of the quality of the sample design, and of the survey results. A simple random sample is a sample in which each member of the population...
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...over factors that could interfere with the validity of the research results. In this research, quantitative method is an appropriate method for this study and the study instruments will be survey or questionnaire. According to Wimmer and Dominick (2011) the quantitative research method refers as a research method that uses standardized questioning. Shuttleworth (2008) define quantitative research method is the standard experimental method of most scientific disciplines. The researcher had selected the...
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...e-journal resource for the public opinion and survey research community Special Issue on Non-probability Samples This issue covers only one topic – nonprobability sampling. Andy Peytchev selected the articles and edited the issue. Some articles have formulas and the content of many articles is too complex for display using the software we use to publish SP, so we are experimenting with PDFs. The articles span a broad spectrum, including the evaluation of bias in a nonprobability sample, the review of assumptions in a nonprobability sampling method that provide the potential for bias, the conditions under which a nonprobability sampling design can lead to valid conclusions in comparative research, case studies on the use of nonprobability methods and samples to facilitate a probability-based study, and a proposed method to combine probability and nonprobability samples under certain conditions. Gerty Lensvelt-Mulders and colleagues use a probability-based web survey with telephone follow-up and propensity score matching in order to evaluate bias in a nonprobability web panel survey. This design and analytic approach allow them to attempt to separate bias due to self-selection from bias due to undercoverage in the panel survey. Although not nearly as much in the survey literature, Respondent Driven Sampling has received considerable attention as a nonprobability sampling method that claims to produce representative estimates. In her article, Sunghee Lee dissects...
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...Sampling and Data Collection in Research Paper BSHS 435 Roxanne January 12, 2015 Heather Suggs Sampling and Data Collection in Research Paper Research is essential to improve the effectiveness of the delivery of human services and to further the education of human service professionals. Research allows human service professionals to understand and apply what was learned in research to better assisting clients to accomplish their objectives and goals. There are different ways to conduct research in human services. I will be discussing two ways to conduct research which are sampling and data collection. I will discuss the purpose of sampling and data collection and how it relates to human service. Sampling Sampling is one way to conduct research in human services. Sampling can be obtained from a certain population, depending on the research. The sample is generally composed of one or two elements which are obtained from the population being studied. In order to attain a preferable sample, first you have to identify the type of population to get a sample. In case you are not able to obtain a good sample, it is more likely to affect your conclusion. There are two types of sampling, which are probability sampling and non-probability sampling. Probability sampling can be used to achieve every element that has the opportunity to be incorporated in the sample. Probability sampling is usually done randomly like how people pull names out of a hat or drawing straws. There...
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...Sampling Techniques Psychology 341 August 11, 2013 ABSTRACT The present research paper was designed to discuss the different types of sampling methods used to conduct research in the field of Psychology. The sampling techniques included in this paper are probability sampling, non probability sampling, surveys and questionnaires. The use of examples for each type of technique is given to further the understanding of each specific type. Furthermore, some the most important aspects that should considered before selecting a method are outlined in detail. Sampling Techniques When conducting research, it is almost impossible to study the entire population that we are interested in looking at more in depth. For example, if we were interested in comparing the level of romantic satisfaction among college students in the United States, it would be practically impossible to survey every single person who is attending college in the country. Not only would it take an extremely long time to do so, but it would also be very expensive. That is why researchers will use small samples from the population to gather their data instead. A sample is particularly useful because it allows the researcher to make inferences about a specific population without having to actually survey the entire population (Trochim, 2006). There are several sampling techniques used to gather information about a sample. Some of these include probability sampling, non probability sampling, surveys, and questionnaires...
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...Sampling is one of the most important factor in educational research, sampling is a way of sele cting a fraction of people in a population of research in order to find the needed information which can generalised and extend their results further than the respondents, The researcher may not manage to collect the information for every individual of interest as it is costly, time consuming and stress nous, as(Mcmillin,1996) stated that when conducting an educational research, it is usually impractical and unnecessary to measure all the elements in the population of interest. The are two main types of sampling procedures suitable for conducting educational research, which is probability also known as random sampling and non-probability or non-random sampling. This paper will further discuss the two categories of sampling procedures that are commonly used in educational research and highlight the strength and weakness of using the discussed sampling procedures. Probability sampling is the type of research in which the researcher chooses the respondents randomly. In this type of research each respondent has an equivalent possibility of taking part in the research. probability sampling is a way of choosing the respondents randomly as (Mcmillin,1996) highlighted that “this way of random selection implies at least every member of the population or the subgroups has an equal chance of being selected” Each of the population has equal chance of being picked up into the sample, moreover...
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...Total number of elements in the sample SAMPLING * the process of selecting a small number of elements from a larger defined target group of elements such that the information gathered from the small group will allow judgments to be made about the larger groups SAMPLING TECHNIQUES * PROBABILITY SAMPLING a method of selecting a sample wherein each element in the population has a known, nonzero chance of being included in the sample. Simple Random Sampling a probability sampling method wherein all members of the population have equal chances of being included in the study. When to use: * If the members of the population are not so spread geographically. * If the members are homogeneous with respect to the characteristic under study. Systematic Sampling probability sampling method wherein the selection of the first member (random start - r) is at random (using simple random sampling) and the selection of the other members in sample is systematic by successively taking every kth member from the random start, where k is the sampling interval. When to use: * If the arrangement of the members is according to magnitude. * If there is no available list of members of the population. Stratified Sampling * a probability sampling method where we divide the population into nonoverlapping subpopulations or strata and then select sample (using simple random sampling or systematic sampling) from each stratum based on a stratification...
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...now Sampling (statistics) From Wikipedia, the free encyclopedia Jump to: navigation, search This article is about statistically selecting a random (or a wishfully "representative") subset of a population. For computer simulation, see pseudo-random number sampling. In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a population to estimate characteristics of the whole population. Researchers rarely survey the entire population because the cost of a census is too high. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. Each observation measures one or more properties (such as weight, location, color) of observable bodies distinguished as independent objects or individuals. In survey sampling, weights can be applied to the data to adjust for the sample design, particularly stratified sampling (blocking). Results from probability theory and statistical theory are employed to guide practice. In business and medical research, sampling is widely used for gathering information about a population. Contents [hide] * 1 Process * 2 Population definition * 3 Sampling frame * 4 Probability and nonprobability sampling * 5 Sampling methods * 5.1 Simple random sampling * 5.2 Systematic sampling * 5.3 Stratified sampling ...
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...SAMPLING: In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a population to estimate characteristics of the whole population. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. The sampling process comprises several stages: * Defining the population of concern * Specifying a sampling frame, a set of items or events possible to measure * Specifying a sampling method for selecting items or events from the frame * Determining the sample size * Implementing the sampling plan * Sampling and data collecting PROBABILITY AND NON-PROBABILITY SAMPLING: A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined. The combination of these traits makes it possible to produce unbiased estimates of population totals, by weighting sampled units according to their probability of selection. Non-probability sampling is any sampling method where some elements of the population have no chance of selection (these are sometimes referred to as 'out of coverage'/'under covered'), or where the probability of selection can't be accurately determined. It involves the selection of elements based on assumptions regarding...
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...1.1 create a plan for the collection of primary and secondary data for a given business problem. Primary Data Primary data can collect by using experiments, surveys, questionnaires, interviews, and observations. If you’ve already gathered this information, we can then analyze it and then come up with accurate results based on your needs. But if you haven’t already gotten this information together, no problem! We can also help with that step of data collection as well. (datacollectionservice.net, 2015) We make primary data collection easy * We create a questionnaire and interview * We design a survey * We choose the sample * We analyze the data Secondary Data Secondary data comes from resources that have already been published. You may have a running list of certain sources but there are so many published items in the world, it can be hard to find the one thing that will make a difference to your project. Collection of data from secondary sources is a treasure hunt and we are skilled researchers with an eye for diamonds. We have developed extensive lists of secondary sources of data collection and will utilize them for your project. Just because something is listed, as a secondary source for data collection doesn’t mean that it’s less important though. (datacollectionservice.net, 2015) Secondary data collection has never been easier * We define the values * We surf the webpages * We create a custom Table * We analyze and...
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...CLUSTER SAMPLING 4. CONVENIENCE SAMPLING 5. DESCRIPTIVE RESEARCH 6. DESCRIPTIVE DATA 7. EXPLORATORY RESEARCH 8. FOLLOW-UP 9. LONGITUDINAL STUDY 10. NON PARAMETRIC STATISTIC 11. NON-PROBABILITY SAMPLING 12. PARAMETRIC STATISTIC 13. POPULATION 14. PILOT TEST 15. PURPOSIVE SAMPLING 16. PROBABILITY SAMPLING 17. QUOTA SAMPLING 18. RESEARCH ETHICS 19. RESEARCH OBJECTIVES 20. SAMPLING FRAME 21. SEMANTIC DIFFERENTIAL RATING SCALE 22. SIGNIFICANCE TESTING 23. SIMPLE RANDOM SAMPLING & SNOWBALL SAMPLING 24. STRATIFIED RANDOM SAMPLING 25. SYSTEMATIC SAMPLING 26. CRITICAL VALUES: The value of the standard statistic (z or t) beyond which we reject the null hypothesis. It is the boundary between the acceptance & rejection regions. Eg. For a 2 tailed hypothesis test being tested at α = 5% the critical values are ± 1.96. 27. TYPE I ERROR (OR) LEVEL OF SIGNIFICANCE (OR) PRODUCER’S RISK (α): A value indicating the % of sample values that are outside certain limits, assuming that the null hypothesis is true. It is the probability of rejecting the null hypothesis when it is true. Eg: α=5% indicates that 5 times out of 100 the null hypothesis gets rejected when it is true. 28. TYPE II ERROR (OR) CONSUMER’S RISK (β): It is the probability of accepting the null hypothesis when it is false. 29. POWER OF A TEST: It is the probability of rejecting...
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