STI Sampling Concepts PDF

SH1806 Ways and Means of Collecting Data I. Sampling Concepts Sampling is a method of acquiring representatives of a certain population to gain and determine parameters of the whole group (Merriam-Webster, 2018). The term population is a term used in research...

SH1806 Ways and Means of Collecting Data I. Sampling Concepts Sampling is a method of acquiring representatives of a certain population to gain and determine parameters of the whole group (Merriam-Webster, 2018). The term population is a term used in research that denotes a huge group of people where you can choose a sample. This sample represents the entire group. Sampling frame is the list of the members of the population to which the researcher wants to generalize or apply his or her findings about the sample. The sample unit denotes the individuals in the population. For example: Population STI Senior High School students from Metro Manila Sample 1,500 STI Senior High School students from Metro Manila Sampling Frame All STI Senior High School students from Metro Manila who attended public schools Sampling Unit All male STI Senior High School students from Metro Manila who attended public schools Researchers must be aware that there are factors that can affect sample selection. According to Babbie (2016), when selecting respondents for a study, a researcher must not only listen to his/her mind but by other factors like the ones listed below: 1. Sample Size – it refers to how small or big the sample size is. A few researchers would often base their sample size on studies, which they have previously read. The best way to determine the appropriate sample size is the representativeness of the sample with respect to the population. This can be achieved through randomization of samples. Through randomization, the chances of acquiring a 95% or higher distribution of the population is highly probable because it will target all aspects of the population unbiased of economic status, sex, educational attainment, and others. Researchers must attain a confidence level or the.05 level since it is the acceptable degree of representativeness of samples. 2. Sampling Technique – this factor falls under two (2) categories: a) probability sampling which is bias-free due to the use of randomizations; and b) non-probability sampling which uses pre- selected samples and is prone to bias. Bias is one of the leading factors that can cause sampling errors. 3. Heterogeneity of the Population – heterogeneous population is composed of individuals with varied capabilities and characteristics. It is important to choose a sampling technique that will widely distribute the selection of a large sample among all members of the population. This will cover each nook and cranny of the demographic and will prevent sampling errors. 4. Statistical Techniques – the accuracy and exactness of the samples depend on how the researcher effectively used his/her mathematical methods, in this case, statistics. Errors in using mathematical methods could yield negative and erroneous results that could alter the whole study. 5. Time and Cost – covering a sample within a population would need a lot of time and money. One good example is the Food and Nutrition Research Institute Department of Science and Technology (FNRI-DOST) and their research program called the National Nutrition Survey, which aimed in monitoring the nutritional status of Filipinos from Batanes to Tawi-Tawi which 06 Handout 1 *Property of STI [email protected] Page 1 of 5  SH1806 is the Southernmost part of the Philippines. Personnel from this government agency have roughly five (5) years to gather data from all over the Philippines and get a huge chunk of budget from the national government. Nevertheless, this is justifiable since many government agencies would need that data; from the Department of Health (DOH), the Department of Social Welfare and Development (DSWD), the National Economic and Development Authority (NEDA), and the Office of the President in Malacañang (Gavilan, 2014). II. Sampling Methods Like what we have discussed earlier, sampling techniques fall under two (2) categories: probability sampling and non-probability sampling. Let us discuss further these two (2) categories (Baraceros, 2016). 1. Probability Sampling – this method relies on the researcher’s selection of respondents on pure chance thus, everybody in the population participates. a. Simple-random Sampling – the selection of respondents is based on pure chance. b. Systematic Sampling – this is a type of probability sampling scheme in which sample members from a larger population are chosen according to a random starting point and a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size. For example, a researcher wants to create a systematic sample of 1,000 students from a school with a student population of 10, 000. The researcher will then decide, a number, let us say like four (4), as the number to begin with. This means that the individual numbered “4” will his/her first selection, and then the researcher would decide that every tenth person from then on (desired sample size) would be included in the count. The sample would then be 4, 14, 24, 34, 44, and so on until s/he reaches the individual numbered “9,994”. c. Stratified Sampling – this type of method chooses a sample that later on be subdivided into- sub-groups during the stage of data analysis. For example, a researcher might divide a sample of people based on their religious affiliation, age, and others. This sampling technique is effective for studying how an issue might differ across subgroups. d. Cluster Sampling – this is choosing respondents in clusters, rather than in separate individuals. For example, selecting five (5) classes of 50 students each from a school that has a 50,000 students population. 2. Non-Probability Sampling – this technique is prone to bias due to the pre-selection of respondents. Below are the types of non-probability sampling techniques (Crossman, 2018). a. Quota Sampling – selecting specific samples that the researcher knows will correspond to the population in terms of one (1), two (2), or even more characteristics. b. Voluntary Sampling – choosing samples who are very much willing to participate as respondents. c. Purposive Sampling – selecting respondents who are deemed by the researcher as samples with good background and knowledgeable about the study being conducted. d. Availability Sampling – choosing respondents who are easy to find and willing to communicate with the researcher. e. Snowball Sampling – also known as chain sampling, is used when the respondents cannot be easily located like homeless individuals or street children. A snowball sample is one in 06 Handout 1 *Property of STI [email protected] Page 2 of 5  SH1806 which the researcher gathers data on the few members of the target population s/he can locate, then asks those personages to provide information needed to find other members of that population whom they know. III. Designing the Research Instruments Research instruments are measurement tools designed to acquire data and information on a topic or subject of interest from research subjects. Surveys, tests, questionnaires and the like are types of research instruments used to obtain data. The two (2) commonly used research instruments are surveys and interviews. Surveys usually are self-administered. The researchers allow respondents to answer predetermined sets of questions. On the other hand, interviews are done face-to-face or in any means that would allow the researcher and the respondent to converse and engage in a discussion on a particular topic. Interviews are often used in qualitative research primarily because it can be used to explore the views, experiences, beliefs, and motivations of the participants. We must remember that qualitative research involves the use on non-numerical data. In quantitative research, surveys are often used and are commonly set in such a way that it simulates a questionnaire. Surveys enable the researcher to collect numerical descriptions of trends, behaviors, attitudes, orientation, and opinion about a sample. Though most respondents feel uneasy when answering questions especially the personal ones, it is the job of the researcher to assure the respondents of confidentiality. There are setbacks as well since surveys could yield and produce biased results. Respondents may feel obliged to answer something that will please the researcher. Ambiguity is another issue of using surveys since the respondent may perceive the questions differently or may misunderstood the query. In order to curb and solve this issue, the researcher must formulate questions that can be easily understood and with less complicated terms. Guidelines in Formulating Surveys  Ethics should be observed. A few respondents might feel awkward answering the questions so it is the researchers’ responsibility to make sure that confidentiality will be exercised.  Consider the length of the survey. If the survey is long, respondents may feel an experience called “survey fatigue” which might cause them to answer haphazardly thus resulting in biased results.  Surveys must be free from ambiguity. Questions should be understandable. Avoid abbreviating terms as this could cause confusion in the part of the respondents.  Double-barreled questions such as those that tap several issues but require only one (1) answer. These questions may result in error in the behaviors being measured for the question. Here is an example of a double-barreled question: Do you think there should be more classes about Rizal and Philippine Constitution? The question is trying to answer two (2) different issues, which later on could negatively alter the results. Combining both issues in one (1) sentence or question makes it unclear what exactly is being measured. In order to reinforce the guidelines written above, qualtrics.com have made the following infographic about what makes a good survey question. 06 Handout 1 *Property of STI [email protected] Page 3 of 5  SH1806 Figure 1. What makes a good survey question Source: www.qualtrics.com Types of Survey Questions (Torneo & Clamor-Torneo, 2017) Questions included in surveys come in the following forms: 1. Open-ended questions – these questions do not have fixed answers or even options. Respondents are allowed to answer freely. In these types of questions, it is imperative that the researcher record the statements of the respondents in verbatim. The researcher must also carry out follow- up questions to clarify certain unclear and shady items and responses. Example: Why did you choose to elect the incumbent president? Kindly explain. 2. Dichotomous Questions – these questions may have two (2) possible answers. Often these questions have responses by either a yes or a no, true or false, or agree or disagree. These questions are employed when the researcher wants to categorize the respondents’ opinions or preferences. Example: Tattoos greatly affect a person’s skills at work. __ Agree __ Disagree 06 Handout 1 *Property of STI [email protected] Page 4 of 5  SH1806 3. Multiple-response Questions – these questions have multiple answers. Example: How were you able to know the programs being offered by STI College Ortigas-Cainta? __ Internet __ Radio advertisement __ Television commercial __ Word of mouth 4. Matrix Questions – these are questions which are open-ended and task the respondents to evaluate one (1) or several rows or choices. A Likert scale is a type of a matrix question. Example: Figure 2. Likert scale. Source: https://www.fieldboom.com/blog/likert-scale/ 5. Contingency Questions – these are questions intended for specific respondents only. Normally, these are follow-up questions provided that the respondent agrees to a certain question item. Example: Have you ever tried any illegal substances in the past? __ Yes __ No If yes, what illegal substances have you tried? __ Marijuana __ Crystal Meth __ Heroine __ Cocaine __ Ecstasy (tablet or liquid form) __ Others, please specify ________ References: Babbie, E. R. (2016). The basics of social research. Boston, MA: Cengage Learning. Baraceros, E. (2016). Practical research 2. Manila: Rex Bookstore Inc. Crossman, A. (2018, February 04). Find the best sampling technique for your research. Retrieved May 24, 2018, from https://www.thoughtco.com/sampling-designs-used-in-sociology-3026562 Gavilan, J. (2014, July 01). From numbers to action, thanks to the National Nutrition Survey. Retrieved May 24, 2018, from https://www.rappler.com/move-ph/issues/hunger/62031-national-nutrition-survey-role-fnri Sampling. (n.d.). Retrieved from https://www.merriam-webster.com/dictionary/sampling Clamor-Torneo, H. & Torneo, A. (2017). Practical research 2. Quezon City: Sibs Publishing House Inc. 06 Handout 1 *Property of STI [email protected] Page 5 of 5