By: Christian Nol R. Sangalang NON-PROBABILITY SAMPLING METHODS SAMPLING ERRORS Search 2 TYPES OF SAMPLING METHODS: Probability Sampling Involves random selection, allowing you to make strong statistical inferences about the whole group. Non-Probability Sampling Involves non-random selection so not every individual has a chance of being included. Non-Probability Sampling Key Notes 1 Sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection. 2 This type of sample is easier and cheaper to access, but it has a higher risk of sampling bias. 3 This is a sampling method in which not all members of the population have an equal chance of participating in the study Convenience Sampling NON-PROBABILITY SAMPLING METHODS Voluntary Response Sampling Purposive Sampling Snowball sampling Quota Sampling 1 Convenience Sampling Search • A convenience sample simply includes the individuals who happen to be most accessible to the researcher. Save Cancel 1 Convenience Sampling When to Use? Researchers use Convenience Sampling: • In situations where additional inputs are not necessary for the principal research. • When there are no criteria required to be a part of the sample. • When all components of the population are eligible to be sample. 1 Convenience Sampling Advantage • Convenience and inexpensive • Collect data quickly • Readily available sample Disadvantage • No way to tell if the sample is representative of the population. • Degree of generalizability is questionable. • Bias Convenience Sampling Example: Staff in a bank is tasked to conduct research about the utilization of credit cards in shopping malls. The staff distribute the questionnaires at a crowded area in the shopping mall with randomly selected participants. 2 Voluntary Response Sampling Search • Is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves. (e.g. by responding to a public online survey). Save Cancel 2 Voluntary Response Sampling When to Use? • Researchers use Voluntary Response Sampling when it is necessary to rely on those who are willing to answer requests to provide data. 2 Voluntary Response Sampling Advantage • Easy and inexpensive • Minimal effort by the researcher. Disadvantage • Samples are always at least somewhat biased, as some people will inherently be more likely to volunteer than others Voluntary Response Sampling Example: You are conducting research about gender-based discrimination in a workplace setting. You send out the survey to all your colleagues. The majority of those who answered came from the third gender. This can certainly give you some insight into the topic, but the people who responded are more likely to be those who have strong opinions and advocate of LGBTQ rights, so you can’t be sure that their opinions are representative of all the workers in the office. 3 Purposive/Judgement Sampling Search • Researchers select the samples based purely on the researcher’s knowledge and credibility. In other words, researchers choose only those people who they deem fit to participate in the research study. Note : An effective purposive sample must have clear criteria and rationale for inclusion. Save Cancel 3 Purposive/Judgement Sampling When to Use? • Researchers use purposive sampling when they want to access a particular subset of people, as all participants of a survey are selected because they fit a particular profile. 3 Purposive/Judgement Sampling Advantage • Useful in Qualitative Research Disadvantage • Preconceived notions of a researcher where the researcher wants to gain can influence the results and it detailed knowledge about a specific involves a high level of ambiguity. phenomenon rather than make statistical inferences. Purposive/Judgement Sampling Example: You are conducting a research about the effectiveness of IT system in your office. Not all the office staff are using IT systems as some of them are performing simple and clerical tasks. Since you are very much aware of the roles of your coworkers, you will choose only those who are using IT systems in their everyday work. 4 Snowball Sampling • It helps researchers find a sample when they are difficult to locate or when the sample size is small and not easily available. • This sampling system works like the referral program. Once the researchers find suitable subjects, he asks them for assistance to seek similar subjects to form a considerably good size sample. Search Save Cancel 4 Snowball Sampling When to Use? • Researchers usually use Snowball Sampling in cases where there is no precalculated list of target population details, there is immense pain involved in contacting members of the target population and when members of the target population are not inclined towards contributing due to a social stigma attached to them or confidentiality of the organization respondents work. 4 Snowball Sampling Advantage Disadvantage • It’s quicker to find samples • Sampling bias and margin of error. • Cost effective • Lack of cooperation. • Sample hesitant subjects Snowball Sampling Example: You are conducting a research about the effectiveness and usefulness of Continuing Professional Development (CPD’s) units required in renewing a PRC License. You do not have a predetermined list of PRC license holders and you are merely relying on the referrals of those professionals that you previously interviewed. 5 Quota Sampling • The researchers create a sample involving individuals that represent a population. • Researchers choose these individuals according to specific traits or qualities and they decide and create quotas so that the market research samples can be useful in collecting data. • The researcher is interested in a particular strata within the population. Search Save Cancel 5 Quota Sampling When to Use? • Quota sampling is useful when the time frame to conduct a survey is limited, the research budget is very tight, or survey accuracy is not the priority. 5 Quota Sampling Advantage Disadvantage • Saves time & money • Impossible to find sampling error. • Research convenience • Change of sampling bias • Accurate representation of the • Some issues relating with those population of interest items which do not clearly fall in any groups are understated. Quota Sampling Example: As a human resource staff, you are conducting research on whether there is a need to provide life and health insurance to your staff. The owner of the company wants to know which age bracket has a high interest in receiving insurance rather than monetary benefits. You divide the population into age brackets such as 20-30, 30-40, 40-50, and 50+. From this information, the researcher gauges the preferred benefits among the employees. What is a Sampling Error? SAMPLING ERROR • A sampling error occurs when the sample used in the study is not representative of the whole population. • Sampling errors often occur, and thus, researchers always calculate a margin of error during final results as a statistical practice. • The margin of error is the amount of error allowed for a miscalculation to represent the difference between the sample and the actual population. Population Specification Error MOST COMMON SAMPLING ERRORS Sample Frame Error Selection Error Non-Response Error 1 Population Specification Error Search • A population specification error occurs when researchers don’t know precisely who to survey. Example: A marketing research study about the most purchased food item in Food Panda. Who are the right people to survey? Is it the food delivery driver or the buyers? It can be the driver, or it can be the buyer, or both. The drivers receives the orders, so they have direct knowledge about the topic, but the buyer's perspective is also relevant. Save Cancel 2 Sample Frame Error Search • Sampling frame errors arise when researchers target the sub-population wrongly while selecting the sample. Example: You’re doing a research for a restaurant about the customer’s satisfaction for the take-home services. It will take you too much time to collect information, so you selected a sampling fame and decided to use credit card receipts to identify your customers in the populations. Your findings may not apply to all the customers specifically those who paid with cash and online payment applications. Save Cancel 3 Selection Error Search • Occurs when the respondents’ survey participation is self- selected, implying only those who are interested respond. Selection errors can be reduced by encouraging participation. • A typical survey process includes initiating pre-survey contact requesting cooperation, actual surveying, and postsurvey follow-up. • If a response is not received, a second survey request follows, and perhaps interviews using alternate modes such as telephone or person-to-person. Save Cancel 4 Non-Response Error • Non-response errors occur when respondents are different than those who do not respond. This may occur because either the potential respondent was not contacted, or they refused to respond. The extent of this non-response error can be checked through follow-up surveys using alternate modes. • Some reasons for not responding : Search Save 1) Waste of time 2) Unwilling to answer personal questions 3) No understanding about the subject matter Cancel Controlling Your Sampling Error Statistical theories help researchers measure the probability of sampling errors in sample size and population. The size of the sample considered from the population primarily determines the size of the sampling error. Larger sample sizes tend to encounter a lower rate of errors. Researchers use a metric known as the margin of error to understand and evaluate the margin of error. Usually, a confidence level of 95% is considered to be the desired confidence level. Steps to Reduce Sampling Errors Increase sample size A larger sample size results in a more accurate result because the study gets closer to the actual population size. Steps to Reduce Sampling Errors Divide the population into groups Test groups according to their size in the population instead of a random sample. For example, if people of a specific demographic make up 20% of the population, make sure that your study is made up of this variable. Steps to Reduce Sampling Errors Know your population Study your population and understand its demographic mix. Know what demographics use your product and service and ensure you only target the sample that matters. https://www.scribbr.com/methodology/sampling-methods/ Sources: https://www.questionpro.com/blog/non-probability-sampling/ https://www.questionpro.com/blog/quota-sampling/ https://www.mathstopia.net/sampling/quota-sampling http://www2.hawaii.edu/~cheang/Sampling%20Strategies%20and%20 their%20Advantages%20and%20Disadvantages.htm https://www.questionpro.com/blog/snowball-sampling/ Sources: https://www.questionpro.com/blog/quota-sampling/ https://www.questionpro.com/blog/convenience-sampling/ https://www.qualtrics.com/au/experience-management/research/ sampling-errors/ https://www.questionpro.com/blog/sampling-error/ Thank you!
