1) It is the set of all possible values of a variable. a) population b) sample c) set d) subset 2) it consists of one or more data drawn from the population a) population b) sample c) set d) subset 3) Type of sampling techniques that involve random selection a) probability sampling b) non-probability sampling 4) A sampling technique that do not involve random selection of data a) probability sampling b) non-probability sampling 5) the most basic random sampling wherein each element in the population has an equal probability of being selected a) cluster sampling b) stratified sampling c) simple random sampling d) snowball sampling 6) This sampling technique can be done by listing all the elements in the population and selecting every kth element in your population list. a) systematic random sampling b) simple random sampling c) stratified random sampling d) cluster sampling 7) it is random sampling wherein the population is divided into different strata or divisions. The number of samples will be proportionately picked in each stratum that is why all strata are represented in the sample. a) snowball sampling b) cluster random sampling c) stratified random sampling d) systematic random sampling 8) is a random sampling wherein population is divided into clusters or groups and then the clusters are randomly selected. All elements of the clusters randomly selected are considered the sample of the study. a) cluster sampling b) systematic sampling c) simple random sampling d) stratified random sampling 9) The researcher gathers data from nearby sources of information exerting minimal effort. a) systematic sampling b) cluster sampling c) stratified sampling d) convenience sampling 10) a non probability sampling technique in which the samples have traits that are rare to find, which existing subjects provide referrals to recruit samples required for a research study. a) convenience sampling b) snowball sampling c) cluster sampling d) systematic random sampling

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