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Sampling for Quantities & Qualitative Research Abeer AlNajjar 1 Population Target group (universe in texts) Census (to study every member of a population) because measuring every member of a population usually is not feasible most researchers employ a Sample Sample ( a subgroup of the population) 2 Communication researchers are interested in a population (also called a universe when applied to texts) of communicators, all the people who posses a particular characteristic, or, in the case of those who study texts, all the messages that share a characteristic of interest. The population of interest to researchers (often called the target group) might be members of a business, communication majors at a university, all students at a university, all people living in a city, all eligible voters in a country. Texts ( editorials published in a specific newspaper for a week, or a large universe such as every editorial published In every newspaper in the UAE, or even larger such as all persuasive messages). The best way to generalize to a population is to study every member of a population (Census) If every member is studied, we know, by definition, the population’s response at the point in time the study was done Sample The results from the sample are then generalized back to (used to represent) the population Representative sample ( population validity) Its similarity to its parent population 3 The results from the sample are then generalized back to (used to represent) the population). For such generalization to be valid (demonstrate population validity), the sample must be representative of its population. That is, it must accurately approximate the population. Types of sampling Random sampling (probability sampling) Involves selecting a sample in such a way that each person in the population of interest has an equal chance of being included Nonrandom sampling (nonprobability sampling) Is what ever researchers do instead of using procedures that ensure that each member of a population has an equal chance of being selected Sampling error Is a number that express how much the characteristic of a sample probably differ from the characteristics of a population 5 There are 2 different types of sampling procedures, and differ in terms of how confident we are about the ability of the selected sample to represent the population from which it is drawn Random sampling (probability sampling) Involves selecting a sample in such a way that each person in the population of interest has an equal chance of being included By giving everyone an equal chance , random sampling eliminates the danger of researchers biasing the selection process because of their own opinions or desires. By eliminating bias, random sampling provides the best assurance that the same characteristics of the population exist in the sample, and, therefore, that the sample represents the population. Nonrandom sampling: it sometimes is .
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Designing Samples
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Surveys and Questioning
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11.
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