ways and means of collecting data

• Contingency questions are a type of survey question.
• Availability Sampling is a method where respondents are chosen based on their availability and willingness to communicate with the researcher.
• Snowball Sampling, also known as chain sampling, is used when the respondents cannot be easily located like homeless individuals or street children.
• Research instruments are 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.
• Surveys usually are self-administered, allowing respondents to answer predetermined sets of questions.
• 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.
• The two commonly used research instruments are surveys and interviews.
• Open-ended questions may have two (2) possible answers and often have responses by either a yes or a no, true or false, or agree or disagree.
• Dichotomous questions have multiple answers.
• Multiple-response questions are questions that are open-ended and ask the respondents to evaluate one (1) or several rows or choices.
• A Likert scale is a type of matrix question.
• The 5 factors that can affect sample selection are Sample size, Sampling Technique, Heterogeneity of the population, Statistical techniques, Time and cost.
• Sampling techniques fall under two categories: probability sampling and non-probability sampling.
• Probability sampling relies on the researcher’s selection of respondents on pure chance, meaning everybody in the population participates.
• Simple random Sampling is a type of probability sampling where the selection of respondents is based on pure chance.
• Systematic Sampling is a type of probability sampling where respondents are chosen from a larger population according to a random starting point and a fixed, periodic interval.
• Stratified Sampling is a type of probability sampling where a sample is chosen that will be subdivided into sub-groups during the stage of data analysis.
• Cluster Sampling is a type of probability sampling where respondents are chosen in clusters, rather than in separate individuals.
• Non-Probability Sampling is a technique that is prone to bias due to the pre-selection of respondents.
• Quota Sampling is a type of non-probability sampling where specific samples that the researcher knows will correspond to the population in terms of one, two, or even more characteristics are selected.
• Voluntary Sampling is a type of non-probability sampling where respondents are chosen who are very much willing to participate as respondents.
• Purposive Sampling is a type of non-probability sampling where respondents are selected who are deemed by the researcher as samples with good background and knowledgeable about the study being conducted.
• Sampling is a method of acquiring representatives of a certain population to gain and determine the parameters of the whole group.
• Population denotes a huge group of people from whom you can choose a sample.
• 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.
• Sample unit denotes the individuals in the population.
• Sample size refers to how small or big the sample size is.
• Sampling technique falls under two (2) categories: probability sampling which is bias-free due to the use of randomizations and non-probability sampling which uses pre-selected samples and is prone to bias.
• Heterogeneity of the population can prevent sampling errors.
• Statistical Techniques may have errors in using mathematical methods could yield negative and erroneous results that could alter the whole study.
• Covering a sample within a population would need a lot of time and money.