Psychology
Sampling Psychology
Sampling in psychology refers to the process of selecting a subset of individuals from a larger population to participate in a research study. The goal is to ensure that the sample is representative of the population, allowing researchers to make generalizations about the larger group. Various sampling methods, such as random sampling, stratified sampling, and convenience sampling, are used to achieve this.
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12 Key excerpts on "Sampling Psychology"
No longer available |Learn more- (Author)
- 2014(Publication Date)
- Orange Apple(Publisher)
________________________ WORLD TECHNOLOGIES ________________________ Chapter- 1 Introduction to Sampling Sampling is that part of statistical practice concerned with the selection of a subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for the purposes of making predictions based on statistical inference. Sampling is an important aspect of data collection. Researchers rarely survey the entire population for two reasons (Adèr, Mellenbergh, & Hand, 2008): the cost is too high, and the population is dynamic in that the individuals making up the population may change over time. 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, survey weights can be applied to the data to adjust for the sample design. 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. Process 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 Population definition Successful statistical practice is based on focused problem definition. In sampling, this includes defining the population from which our sample is drawn. A population can be
No longer available |Learn more- (Author)
- 2014(Publication Date)
- Orange Apple(Publisher)
________________________ WORLD TECHNOLOGIES ________________________ Chapter- 6 Sampling Sampling is that part of statistical practice concerned with the selection of a subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for the purposes of making predictions based on statistical inference. Sampling is an important aspect of data collection. Researchers rarely survey the entire population for two reasons (Adèr, Mellenbergh, & Hand, 2008): the cost is too high, and the population is dynamic in that the individuals making up the population may change over time. 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, survey weights can be applied to the data to adjust for the sample design. 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. Process 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 Population definition Successful statistical practice is based on focused problem definition. In sampling, this includes defining the population from which our sample is drawn. A population can be
eBook - PDFResearch Methods
A Tool for Life
- Bernard C. Beins(Author)
- 2017(Publication Date)
- Cambridge University Press(Publisher)
It might help you understand about biological responses to stress, but not about the psychological experience of stress. 124 CHAPTER FIVE As a researcher, it is up to you to decide how you will define your concept. There is no perfect way; there are simply multiple ways that have their own strengths and weak- nesses. Depending on the question you want to ask, you choose one over another. You could use Holmes and Rahe’s scale or Renner and Mackin’s, or you could find out how other researchers have decided to measure stress and adapt their strategies. In the end you have to select a method that you think will work for you. PROBABILITY SAMPLING Probability sampling is the gold standard of sampling. In its simplest definition, probabil- ity sampling means that everybody that you are interested in, your population, has an equal chance of participating in your study. Unfortunately, outside of some survey research, psychologists typically don’t employ it because it would be very costly. If we were interested in how people in general behave, we would need to test people from every country, of all ages, with diverse back- grounds. For all of its desirability, researchers forego probability sampling in favor of less costly approaches, like the samples of college students that most research employs. We know that psychology students are not typical of people in general on a lot of dimensions; they are younger, more educated, more likely to be female, etc. A critical question is whether the differences are important in your research. If you are studying reaction times to the appearance of a visual stimulus on a screen, college students may be very similar to other people. On the other hand, if you want to study voting preferences, college students may be dissimilar to people not in college. In our research, we often do not know how well our sample mirrors the population of interest.
eBook - PDFWhat is Psychology?
Foundations, Applications, and Integration
- Ellen Pastorino, Susann Doyle-Portillo, Ellen Pastorino(Authors)
- 2021(Publication Date)
- Cengage Learning EMEA(Publisher)
Because the sample will be used to make inferences or judgments about the entire population, the sample should reflect the whole population as much as possible; that is, it should be a representative sample. Random sampling of participants helps ensure a repre- sentative sample. In a random sample, every member of the population has an equal chance of being selected to participate in the study; this avoids introducing sampling bias into the research. The more representative the sample is, the more the results will generalize (or apply) to the population of interest. But random sampling is not always possible. Instead, psychological research often uses samples of convenience, or groups of people who are easily accessible to the researcher. The students in your psychol- ogy course are a sample of convenience. In fact, much psychological research re- lies on using college students as the sample of convenience! According to Current Population Survey results from the U.S. Census Bureau (2018) around 35% of people in the United States over the age of 25 have a college degree or higher, so samples of college students probably do not represent all types of people and groups. As such, these nonrepresentative samples limit a researcher’s ability to generalize their findings to the population (Levenson, 2017). In addition, online psychology labs at well-known universities across the United States as well as online crowdsourcing platforms, such as Amazon’s Mechanical Turk (MTurk) and TurkPrime, are now much more common ways to recruit partici- pants. On the plus side, researchers conducting online research have the distinct ad- vantage of soliciting a larger and more diverse sample at a fraction of the cost, with improved efficiency and data storage (Gosling & Johnson, 2010; Litman, Robinson, & Abberbock, 2017). Thousands to millions of participants from all over the world may be gathered over the Internet as opposed to a few hundred that can be collected on-site.
eBook - ePubDissertation Research Methods
A Step-by-Step Guide to Writing Up Your Research in the Social Sciences
- Philip Adu, D. Anthony Miles(Authors)
- 2023(Publication Date)
- Routledge(Publisher)
Figure 16.1 illustrates the major steps in the sampling process.Source: Adopted from Sekaran and Bougie (2013).Figure 16.1The sampling process.Before choosing a specific type of sampling technique, a broad sampling technique needs to be decided on. One of the difficult aspects of research is launching an experience-sampling study. It can provide a challenge to even the most seasoned researcher (Christensen et al., 2003 ). When a researcher decides to begin the research process, they must go through the sampling process first. The first stage in the sampling process is to clearly define the problem. Defining the problem is the basis for all research. This also relates to determining the sampling frame. The sampling frame must be representative of the population of interest. This is vital to the research.The next step is to determine the sample design. Establishing the sample design is very important to the researcher. The next step is to determine the appropriate sample size for the study. We have to remember that the population is commonly related to the number of people living in a particular area of the country. Lastly, the researcher has to execute the sampling process. Again, sampling can be used to make inferences about a population.Types of Sampling
The practice of sampling can be used to make an inference about a population or to make a generalization in relation to an existing theory. This is based on the choice of sampling technique.The practice of evaluating the characteristics of an entire population through a representative sample can be an arduous endeavor. As with many research studies, the best strategy to investigate a problem in an entire population is through the use of sampling. How, it is not always possible to conduct a study on an entire population. So, we use the practice of sampling. Thus, the researcher studies a sample of the population, which is a suitable representation of the entire population. We must think of a sample as a subset of the population; thus it is selected to be representative of the population. Again, one of the advantages of sampling is that it can be less costly and more efficient. Being able to use a sample to generalize the results to a whole population requires the use of one of the statistical sampling methods for evaluation. Taking a subset from a chosen sampling frame or entire population is the basic practice of sampling.
eBook - PDF- R. D. Savage(Author)
- 2013(Publication Date)
- Pergamon(Publisher)
SAMPLING IN PSYCHOLOGICAL RESEARCH 383 GENERAL CONSIDERATIONS It seems appropriate to discuss briefly certain specific concepts, basic to the general problem of sampling, before discussing the various techniques for drawing a sample and the problem of planning investigations. This section will, therefore, be concerned with the reason for sampling, the nature of the universe being sampled, the concept of homogeneity, experimental hypotheses and permissible statistical inferences, the universality of induc-tions from samples, control of variation by selection, size of sample, and the fundamental condition of sampling. Resort is made to sampling because of the difficulty—usually the impos-sibility—of dealing with an entire universe. The universe is considered as made up of either a finite or an infinite number of units, usually individuals in psychological research. A given investigator may, within limits, define as he pleases the universe which he wishes to consider. Thus, a psycho-logist may choose the universe of native white 12-year-old boys of urban residence. A sociologist might consider the universe of southern negro tenant families. A universe is said to be finite when there is a limited num-ber of individual units therein and infinite when the number is unlimited. The standard error formulas for a proportion and for a mean, σ ρ = and a M = , σ ? assume an infinite universe or population. In the case of ™ ' l/PQf NY sampling from a finite universe these become σ ρ = / 1 and α ι// Ν tf'/J &M = T77777 / 1 — Ζ 7 Γ > where TV' is the number of cases in the universe. ]/(N) y N' J In a given research it is sometimes difficult to decide whether the universe being sampled is finite or infinite, and, if finite, it is not always easy to deter-mine the value of N'. It might be argued that psychologists never study an infinite universe. It can readily be seen that the corrective factor in the sampling error formulas becomes negligible as N' becomes large.
eBook - PDFResearch Methods For Business
A Skill Building Approach
- Uma Sekaran, Roger Bougie(Authors)
- 2020(Publication Date)
- Wiley(Publisher)
For this purpose, the first 15 people who chose the special item might be interviewed, and their reactions obtained. In such cases, having instant information may be more gainful than obtaining the most representative facts. It should, however, be noted that the results of such convenient samples are not reliable and can never be generalized to the population. Sampling is the process of selecting a sufficient number of the right elements from the popula-tion, so that a study of the sample and an understanding of its properties or characteristics make it possible for us to generalize such properties or characteristics to the population elements. The major steps in sampling include: 1. Define the population. 2. Determine the sample frame. 3. Determine the sampling design. 4. Determine the appropriate sample size. 5. Execute the sampling process. THE SAMPLING PROCESS 226 CHAPTER 14 Sampling DEFINING THE POPULATION Sampling begins with precisely defining the target population. The target population must be defined in terms of elements, geographical boundaries and time. For instance, for a banker inter-ested in saving habits of blue-collar workers in the mining industry in the United States, the target population might be all blue-collar workers in that industry throughout the country. For an advertising agency interested in reading habits of elderly people, the target population might be the German population aged 50 and over. These examples illustrate that the research objective and the scope of the study play a crucial role in defining the target population. DETERMINING THE SAMPLE FRAME The sampling frame is a (physical) representation of all the elements in the population from which the sample is drawn. The payroll of an organization would serve as the sampling frame if its members are to be studied. Ideally, a sampling frame is a complete and correct list of the population elements. However, practical circumstances often make such a list incorrect and incomplete.
eBook - PDFResearch Methods For Business
A Skill Building Approach
- Uma Sekaran, Roger Bougie(Authors)
- 2016(Publication Date)
- Wiley(Publisher)
INTRODUCTION Experimental designs and surveys are useful and powerful in finding answers to research questions through data collection and subsequent analyses, but they can do more harm than good if the population is not correctly tar- geted. That is, if data are not collected from the people, events, or objects that can provide the correct answers to solve the problem, the research will be in vain. The process of selecting the right individuals, objects, or events as representatives for the entire population is known as sampling, which we will examine in some detail in this chapter (see shaded portion in Figure 13.1). The reasons for using a sample, rather than collecting data from the entire population, are self‐evident. In research investigations involving several hundreds and even thousands of elements, it would be practically impossible to collect data from, or test, or examine, every element. Even if it were possible, it would be prohibitive in terms of time, cost, and other human resources. Study of a sample rather than the entire population is also sometimes likely to produce more reliable results. This is mostly because fatigue is reduced and fewer errors Sampling C H A P T E R 1 3 LEARNING OBJECTIVES After completing Chapter 13, you should be able to: 1. Define sampling, sample, population, element, sampling unit, and subject. 2. Discuss statistical terms in sampling. 3. Describe and discuss the sampling process. 4. Compare and contrast specific probability sampling designs. 5. Compare and contrast specific nonprobability sampling designs. 6. Discuss precision and confidence and the trade-off between precision and confidence. 7. Discuss how hypotheses can be tested with sample data. 8. Discuss the factors to be taken into consideration for determining sample size and determine the sample size for any given research project. 9. Discuss sampling in qualitative research. 10. Discuss the role of the manager in sampling. 235
- Stephen Gorard(Author)
- 2003(Publication Date)
- Continuum(Publisher)
Nineteenth-century psychol-ogy was often based on what researchers found out about themselves (introspection), while later twentieth-century psychology was chiefly based on what psychologists found out about each other. There are some hopeful signs that in the twenty-first century psychology is becoming more concerned with people at large. NON-PROBABILITY SAMPLES An implicit assumption has been made in the chapter so far that our sample will be what is termed a 'probability' sample, where cases will be selected either randomly or systematically. There are two good reasons for this focus. First: this kind of sampling is generally more technical than its alternatives, so requiring more explanation for a new researcher. Second: this kind of sampling is preferable in 72 Quantitative Methods in Social Science almost every way to any of its alternatives in all research situations. Thus, a simple guideline would be that probability samples should be used in all circumstances in which they are possible. A high-quality sample is crucial for safe generalization to take place (for high 'external validity'). Non-probability samples should therefore be reserved only for those projects in which there is no other choice. The most common and over-used form of non-probability sampling is the convenience sample, composed of those cases chosen only because they are easily available. A researcher standing in a railway station or shopping centre or outside a student union and stopping people in an ad hoc manner would thereby create a convenience sample and not a random one. This approach is often justified by the comment that a range of people use such places, so the sample will be mixed in composition. The approach is sometimes strengthened, for example in market 'research', by determining quotas for groups of cases (such as men and women) and then deselecting people (e.g. by not stopping them) once the quota for each group is filled.
eBook - PDF- James B. Schreiber, Kimberly Asner-Self(Authors)
- 2011(Publication Date)
- Wiley(Publisher)
The sampling procedures described in this section are considered single-stage sampling, because once the desired final sample is identified, the participants are selected. The first common nonprobability approach used in social science research is convenience sampling. Convenience sampling is used because the researcher has access to the sample, can easily contact the sample, and is often less financially costly than other sampling procedures. Actually, this method is implemented in both quantitative and qualitative studies. Many research studies’ samples are a convenience sample because the researcher had access to students in the school, customers of the business, or patients in a hospital. You might be interested in studying novel problem solving with eight-year-old students, but you really only have access to the eight-year-old students at the school down the street and so they become your convenience sample. Many careers in psychology have been made from the convenience sample of the Psychology 101 student pool. Purposeful sampling occurs when the researcher selects participants because they have specific characteristics that will be representative or informative in relation to the population of interest. A student interested in the development of a new technique for diagnosing clinical eating disorders interviews counselors in this area to determine what the current assessment instruments are missing. The counselors are a purposeful sample; a sample of the general population in this scenario would cost too much from a resource perspective. Quota sampling allows the creation of a sample that meets some requirement or representation of the population. A researcher may decide that, based on census income data, there is a need for 10% of the sample to have an income less than $20,000, 20% to be between $20,000 and $40,000, and so on. The researcher will sample until all those percentages are met.
eBook - PDF- Ronald Comer, Elizabeth Gould, Adrian Furnham(Authors)
- 2014(Publication Date)
- Wiley(Publisher)
Indeed, a population of interest could some- times include everybody in the whole world. Or the desired population may be other large groups, such as all Europeans, adults, teenagers, men or women. In your reality show study, the population of interest includes everyone who watches and everyone who does not. Because they cannot usually study an entire population, researchers must obtain a subset, or sample , from their population of inter- est. This subset stands in for the popu- lation as a whole. Population sampling of this kind is used very often. Politi- cal pollsters, for example, interview samples of the voting population in order to predict which candidate will win an election. FIGURE 2.2 How do psycholo- gists conduct research? Psychologists follow certain steps and confront a number of choice points as they study questions about mental pro- cesses and behaviours. Step 4 Analyse the Data and Accept or Reject the Hypothesis Step 3 Select a Research Method, Choose Participants and Collect the Data Step 6 Build a Theory Step 5 Seek Scientific Review, Publish and Replicate Step 2 Develop a Testable Hypothesis (must be operationally defined) Step 1 Identify Questions of Interest and Review the Literature sample the group of people studied in an experiment, used to stand in for an entire group of people. CHAPTER 2 PSYCHOLOGY AS A SCIENCE 32 surveys. These methods allow researchers to describe, or demonstrate, that a relationship exists between the variables of interest. As an alternative to descriptive methods, investi- gators may conduct experiments, a method that allows them to explain the causes of behaviour (Figure 2.3). Case Studies A case study focuses on a single person. Medical and psychologi- cal practitioners who treat people with problems often conduct case studies to help determine whether therapeutic interventions produce changes in their clients’ symptoms (Lee et al., 2010).
No longer available |Learn more- Frederick J Gravetter; Lori-Ann B. Forzano; Tim Rakow, Frederick Gravetter, Frederick Gravetter, Lori-Ann Forzano, Tim Rakow(Authors)
- 2021(Publication Date)
- Cengage Learning EMEA(Publisher)
Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. C H A P T E R 5 \ Selecting Research Participants 123 For example, a researcher may select a sample that consists entirely of students from an ‘Introductory Psychology’ class at a small college in Atlanta. However, if the researcher is careful to select a broad cross-section of students (different ages, different genders, different levels of academic performance, and so on), it is sensible to expect this sample to be reasonably similar to any other sample of college students that might be obtained from other similar academic departments or other similar colleges around the USA. Unless the research study involves some special skill such as surfing or winter driving, it usually is reasonable to assume that a sample from one location is just as representative as a sample from any other location. An exception to this simple concept occurs whenever a convenience sample is obtained from a location with unusual or unique characteristics, such as a music school for extremely talented students or a private childcare centre for gifted children. The second strategy that helps minimize potential problems with convenience sampling is simply to provide a clear description of how the sample was obtained and who the participants are. For example, a researcher might report that a sample of 20 children aged 3–5 was obtained from a childcare centre in downtown Houston. Or a research report may state that a sample of 100 students, 67 females and 33 males, all between the ages of 18 and 22, was obtained from the ‘Introductory Psychology’ class at a large state university in the Midwest of the USA. Although these samples may not be perfectly representative of the larger population and each may have some biases, at least everyone knows what the sample looks like and can make their own judgements about representativeness.
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