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MODUL PERKULIAHAN Metode Penelitian IKuantitatif Population and sampling Fakultas Program Studi Psikologi Psikologi Tatap Muka 10 Kode MK Disusun Oleh MK61021 Ainul Mardiah, M.Sc Abstract Kompetensi Dalam perkuliah ini dibahas population and sampling Mahasiswa mampu memahami population and sampling Population and Sampling Survey Research Survey research is based on the simple idea that if you want to find out what people think about some topic, just ask them. That is, a survey is a structured set of questions or statements given to a group of people to measure their attitudes, beliefs, values, or tendencies to act. Over the years, people have responded to surveys assessing everything from political preferences to favorite sexual activities. The method has been around for some time, as you can tell from Box 12.2. Unlike most of the methods described in this text, surveying usually requires careful attention to sampling procedures. This point requires some elaboration. For most of the research methods you’ve read about, the emphasis has been on establishing relationships between and among variables. From some of the research you have read about in this text, for instance, you know that researchers have been interested in such topics as the effects of (a) the movement of a room on children’sbalance, (b) closing time on perceived attractiveness, (c) coach effectiveness training on children’s self-esteem, and (d) looming and self-efficacy on fear of spiders. For studies such as these, researchers naturally hope that the results will generalize beyond the people participating in them, but they assume that if the relationship studied is a powerful one, it will occur for most individuals, regardless of how they are chosen to participate in the study. Of course, whether this assumption turns out to be true depends on the normal processes of replication and extension discussed in several places in this book. So, in a study on the capacity limits of short-term memory in adults, it is not necessary to select a random sample—virtually any group of reasonably fluent adults will do. That is, for most research in psychology, it is sufficient to choose, as participants, what is known as a convenience sample. This is a group of individuals who meet the general requirements of the study and are recruited in a variety of ways. Often they are from the ‘‘subject pool’’—general psychology students being asked to participate in a study or two. You learned about some of the ethical issues related to these pools in Box 5.3. Sometimes a specific type of person is recruited for the study, a convenience strategy that is called ‘‘purposive’’ sampling. For instance, when Stanley Milgram first recruited participants for his obedience studies, he placed ads in the local newspaper asking for volunteers. He deliberately (i.e., purposively) avoided using college students because he was concerned that they might be ‘‘too homogeneous a group.... [He] wanted a wide range of individuals drawn from a broad spectrum of class backgrounds’’ (Milgram, 1974, p. 14). 2014 2 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id The Milgram study also illustrates a practical reason for using convenience samples. Recruiting participants for a study can sometimes be time-consuming and frustrating. Milgram could have tried a more sophisticated sampling approach (like the ones you are about to learn), but even if he had, and selected a sample from some larger group, there was no guarantee that the people he selected would be interested in participating in the study. It was simply more efficient to advertise widely and hope to get as many volunteers as possible. Although convenience samples, combined with the normal processes of replication, are adequate for most research in psychology, they are generally inappropriate for survey research. This is because the goal of most survey research is different—the focus is not on examining relationships among variables; it is on developing anaccurate description of the attitudes, beliefs, behavior tendencies, or values of a specifically defined group of people. Good surveys require a form of sampling called probability sampling. Probability Sampling This general strategy is used whenever the goal is to learn something specific about an identifiable group of individuals. As a group, those individuals are referred to as a population, and any subgroup of them is a sample.In probability sampling, each member of the population has some definable probability of being selected for the sample. Sometimes it is possible to study all members of a population. For example, if you wanted to learn the attitudes of all of the people in your experimental psychology class about the issue of animal experimentation and did not wish to generalize beyond that class, you could survey everyone in the class. In this case, the size of the population would be the size of your class. As you might guess, however, the population of interest to a researcher is usually much too large for every member in it to be tested. Hence, a subset of that population, a sample, must be selected. Even though an entire population is seldom tested in a study, the researcher hopes to draw conclusions about this broader group, not just about the sample. Thus, in survey research, it is important for the sample to reflect the attributes of the target population as a whole. When this happens, the sample is said to be representative; if it doesn’t happen, the sample is said to be biased in some fashion. For instance, if you wanted to investigate student perceptions of college life, it would be a serious mistake to select people from a list that included only those students living in college residence halls. Because off-campus residents and commuter students might have very different attitudes from on-campus residents, the results of your survey would be biased in favor of the latter. Perhaps the most famous historical example of biased sampling occurred during political polling in the presidential election of 1936. As it had been doing with reasonable success for 2014 3 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id several previous elections, the magazine Literary Digest tried to predict the election outcome by sending out about 10 million simulated ballots to subscribers, to others selected from a sample of phone books from around the country, and to others from motor vehicle registration information (Sprinthall, 2000). Close to 25% (almost 2.5 million) of the ballots were returned to the magazine; of these respondents, 57% preferred the Republican candidate, Alf Landon, and 40% chose the incumbent president, Franklin Roosevelt. In the actual election, Roosevelt won in a landslide with more than 60% of the vote. Can you guess why the sample was biased? Although the editors of Literary Digest were aware that their own subscribers tended to be upper middle class and Republican, they thought they were broadening the sample and making it more representative by adding people chosen from phone books and car registration data. In fact, they were selecting more Republicans. In the midst of the Great Depression, practically the only people who could afford phones and cars were members of the upper middle and upper classes, and these were more likely to be Republicans than Democrats. So, in the survey the magazine actually was asking Republicans how they were going to cast their votes. You might have noticed another flaw in the Literary Digest survey. A large number of ballots was returned, and the magazine was quite confident in its prediction of a Landon victory because the data reflected the views of a substantial number of people—about 2.5 million. Note, however, that not only does the total represent only one-fourth of the ballots originally sent out, but also the returns were from those who chose to send them back. So, those responding to the survey tended to be not just Republicans, but Republicans who wished to make their views known (in light of which, the 57% preferring Landon actually looks rather small, don’t you think?). This self-selection bias is typical in surveys that appear in popular magazines and in newspapers. A survey will appear, with an appeal to readers to send in a response. Then, a month or so later, the results of those who returned the survey will be reported, usually in a way implying that the results are valid. The person reporting the survey will try to impress you with the total number of returns rather than the representativeness of the sample. An example of this ploy is a well-known report on female sexuality (Hite, 1987). It claimed, among other things, that more than 90% of married women felt emotionally abused in their relationships and a substantial majority reported dissatisfaction in marriage. When criticized because the survey was sent only to a select group of women’s organizations and that only 4.5% of 100,000 people returned the survey, the author simply pointed out that 4,500 people were enough for her (just as 2.5 million people were enough for Literary Digest). But research that uses appropriate probability sampling techniques generally shows that 2014 4 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id satisfaction/happiness in marriage is actually quite high. The Hite data were misleading, to say the least. As a scientific thinker, you should be very skeptical about claims made on the basis of biased samples. The lesson, of course, is that if you want to make an accurate statement about a specific population, you must use a sample that represents that population and you must select the sample directly, not rely simply on who decides to return the survey. If you have no choice but to use data from a self-selected sample, and this happens sometimes, you should at least try to determine if the attributes of the sample (e.g., average age, income) match the attributes of the population you have in mind. Even then you need to be cautious in the conclusions you draw. Random Sampling The simplest form of probability sampling is to take a simple random sample. In essence, all this means is that each member of the population has an equal chance of being selected as a member of the sample. To select a random sample of 100 students from your school, for instance, you could place all of their names in a large hat and pick out 100. In actual practice, the procedure is a bit more sophisticated than this, however, usually involving software2 that uses a random number table. To learn the essence of the procedure, work through the example in Table 12.1, which shows you how to use random numbers to select a sample of 5 individuals from a population of 20. Simple random sampling is often an effective, practical way to create a representative sample. It is sometimes the method of choice for ethical reasons as well. In situations in which only a small group can receive some benefit or must incur some cost, and there is no other reasonable basis for decision-making, random sampling is the fairest method to use. A famous example occurred in 1969 in the midst of the Vietnam War, when a lottery system was established to see who would be drafted in the army. For obvious reasons of fairness, birthdays for each of the 365 days of the year were to have an equal probability of being selected first, second, third, and so on. Unfortunately, the actual procedure had some bias (Kolata, 1986). Capsules, one for every day of the year, were placed in a large drum one month at a time. The January capsules went in first, then the February ones, and so on. The drum was rotated to mix the capsules, but apparently this did not succeed TABLE 12.1 Selecting a Random Sample Using a Table of Random Numbers 2014 5 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id completely because when the dates were drawn, those capsules entering the drum last tended to be the first to be picked. This was not a good time to have a birthday in December. There are two problems with simple random sampling. First, there may be some systematic features of the population that you might like to have reflected in your sample. Second, the procedure may be impossible if the population is extremely large. How could you get a list of everyone in the United States in order to select a simple random sample of Americans? The first problem is solved by using stratified sampling, and cluster sampling solves the second difficulty. Stratified Sampling Suppose you wanted to measure attitudes about abortion on your campus, and the school’s population is 5,000 students, of whom 3,000 are women. You decide to sample 100 students. If you take a simple random sample, there are probably going to be more women than men in your sample, but the proportions in the sample won’t match those in the population precisely. Your goal is to make the sample truly representative of the population and, on a question like abortion, there might be important differences of opinion between males and females. Therefore, if your sample happens to be overrepresented with males, it might not truly portray campus attitudes. In a situation like this, it would be a good idea to decide ahead of time that if 60% of the population is female, then exactly 60% of the sample will also be female. That is, just as the population has these two layers (or ‘‘strata’’), so should the sample. 2014 6 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id In a stratified sample, then, the proportions of important subgroups in the population are represented precisely in the sample. In the previous example, with a goal of a sample of 100, 60 females would be randomly sampled from the list of females, and 40 males would be selected from the list of males. Note that some judgment is required here: The researcher has to decide just how many layers to use. In the case of the abortion survey, males and females were sampled in proportion to their overall numbers. Should each of the four undergraduate classes be proportionately represented also? What about Protestants and Catholics? What about left- and right-handers? Obviously, the researcher has to draw the line somewhere. Some characteristics (religion) may be more critical than others (handedness) in deciding how to stratify the sample. Based on what has occurred in prior research or the goals of the current study, it’s up to the researcher to use some good sense. The intent of a stratified sample, to represent subgroups proportionately, can also be met in a nonprobability convenience sample. When using a subject pool, for instance, if you wished to have 60% females and 40% males in your study, and you hoped to test 100 participants, you could simply sign people up in your study untilthe 60 females and 40 males had participated. This type of nonprobability sample iscalled a quota sample. Cluster Sampling Stratified sampling is an effective procedure, but it still doesn’t solve the problem of trying to sample from a huge population, when it is often impossible to acquire a complete list of individuals. Cluster sampling, a procedure frequently used by national polling organizations, solves the problem. With this approach, the researcher randomly selects a cluster of people all having some feature in common. A campus survey at a large university might be done this way. Ifa researcher wanted a cross section of students and stratified sampling was not feasible, an alternative would be to get a list of required ‘‘core’’ classes. Each class would be a cluster and would include students from a variety of majors. If 40 core classes were being offered, the researcher might randomly select 10 of them and then administer the survey to all students in each of the selected classes. If the selected clusters are too large, the researcher can sample a smaller cluster within the larger one. Suppose you wanted to find out how students liked living in the high-rise dorms on your campus, which you’ve defined operationally as any dorm with eight floors or more. Further suppose that fifteen of these buildings exist on your campus, housing a total of 9,000 students. Using cluster sampling, you could first select six of the buildings (each building = a cluster), and then, for each building, randomly select three floors and sample all of the residents (about forty per floor, let’s say) of the selected floors in the selected dorms. This would give you an overall sample size of 720 (40 × 3 × 6). Notice that you also could combine some elements of stratified sampling here. If ten of the dorms house women, and men live in the remaining five, you might select your first clusters to reflect these proportions: four female dorms and two male dorms. 2014 7 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id Varieties of Survey Methods Most surveying today occurs in the form of written questionnaires that are sent through the mail or administered in some more direct fashion (e.g., to a class of students). There are other techniques for collecting survey data, however, and each survey type has its strengths and weaknesses. In addition to written questionnaires, survey data are sometimes collected through face-to-face interviews, sometimes through telephone interviews, and more recently, via the Internet. Researchers sometimes combine methods, a ‘‘mixed-mode’’ approach (Dillman, Smyth, & Christian, 2009). Interviews You have undoubtedly heard of the Kinsey Report, perhaps the most famous sex survey of all time. Completed in the years just following World War II, it resulted from detailed, face-toface interviews with thousands of men and women, and it yielded two large books on sexual behavior in America, one for men (Kinsey, Pomeroy, & Martin, 1948) and one for women (Kinsey, Pomeroy, Martin, & Gebhard, 1953). Although you might think that Kinsey’s interview survey format might have prevented people from describing the intimate details of their sexual attitudes and behaviors, especially considering the historical era in which the studies were done, this apparently did not occur. In fact, conservative postwar America was shocked by the frequency of the reported levels of premarital sex, masturbation, and adultery. The books, although written in dry academic prose and loaded with tables and bar graphs, nonetheless reached best-seller status and made Kinsey a celebrated yet controversial figure. Accused by some of contributing to a moral decline and even of being a Communist, he was regarded by others as a pioneer in the scientific study of an important aspect of human behavior (Christenson, 1971). The interview format for surveying has the advantages of being comprehensive and yielding highly detailed information. Even though the interviewer typically asks a standard set of questions, the skilled interviewer is able to elicit considerable information through follow-up questions or probes. Having an interviewer present also reduces the problem of unclear questions—the interviewer can clarify on the spot. Sampling is sometimes a problem because, in many cases, sizable segments of the population may not be included if they refuse to be interviewed, cannot be located, or live in an area the interviewer would prefer to avoid. For example, the poor and homeless are usually underrepresented in national surveys using the interview format. Interviews can occur in a group format—the focus group procedure described in Chapter 10 is an example. Besides sampling issues, other major problems with the interview approach arecost, logistics, and interviewer bias. Interviewers need to be hired and trained, travel expenses 2014 8 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id can be substantial, and interviews might be restricted to a fairly small geographic area because of the logistical problems of sending interviewers long distances. And despite training, there is always the possibility that interviewer bias can affect the responses given in the face-to-face setting. For example, cross-race bias may exist, resulting in systematic differences between interviews with members of one’s own race and members of other races. The careful researcher using interviews will develop a training program to standardize the interview process as much as possible, and sometimes certain types of interviewers may be trained for specific purposes. For example, middle-aged female interviewers may elicit more cooperation in an interview survey of retired women than young male interviewers, who may not get past the door (van Kammen & Stouthamer-Loeber, 1998) 2014 9 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id Daftar Pustaka 1. Arikunto, S. (1998). Prosedur penelitian suatu pendekatan praktek. Rineka Cipta: Jakarta: PT Rineka Cipta. 2. Butler, C. A., Chapman, E. J., Forman, M.E., Beck, T. A. (2006). The empirical status of cognitive-behavioral therapy: a review of meta-analyses. Clinical psychology Review. Elsevier 26, 17-31. Doi: 10.1016/j.cpr.2005.07.003 3. Cozby, P.C. & Bates, S. (2011). Methods in behavioral research. 11th ed. New Jersey .Mc Graw Hill. 4. Ferguson, L.Y., Sheldon, M. K (2014). Trying to be happier really can work: Two experimental studies. The Journal of Positive Psychology: 8 (1), 23-33, DOI: 10.1080/17439760.2012.747000 5. Goodwin, J.C. (2010). Research in psychology methods and design 6/E. USA: Wiley, J. 6. Gillet, N., Vallerand, J.R., Lafrenie`re, K. A. M., Bureau, S. J. (2012). The mediating role of positive and negative affect in the situational motivation-performance relationship. Motiv Emot. DOI 10.1007/s11031-012-9314-5 7. Kerlinger, F.N., (2000), Foundation of Behavioral Research, New Jersey : Holt, Rinehart and Winston, Inc. 8. Langston , W. (2010). Research methods laboratory manual for psychology. 3rd edition. USA : Wadsworth Cengange Learning. 9. Malka, A., Chatman, A. J. (2010). Intrinsic and Extrinsic Work Orientations as Moderators of the Effect of Annual Income on Subjective Well-Being: A Longitudinal Study. Journal Society for Personality and Social Psychology Bulletin, 29 (6), 737-746. Doi: 10.1177/0146167203252867 10. Rosnow, L. R., Rosnow, M. (2009). Writing papers in psychology. 8th edition. USA : Wadsworth Cengange Learning. 11. Shoshani, A., Stenmetz, S. (2013). Positive Psychology at School: A School-Based Intervention to Promote Adolescents’ Mental Health and Well-Being. Journal Happiness studies. DOI 10.1007/s10902-013-9476-1 12. Singh, Y.K. (2006). Fundamental of Research Methodology and Statistics. New Jersey : Mc Graw Hill. 13. Stutzer, A., Frey, S. B. (2006). Does marriage make people happy, or do happy people get married? The Journal of Socio-Economics, 35, 326–347. doi:10.1016/j.socec.2005.11.043 14. Sugiyono (1997). Statistika untuk penelitian. Bandung: CV Alfabeta. 2014 10 Psikologi Umum I Ainul Mardiah, S.Psi, M.Sc Pusat Bahan Ajar dan eLearning http://www.mercubuana.ac.id