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MATH 2
Lesson 3 -1
| Question | Answer |
|---|---|
| refers to an entire group that is under study or investigation | population |
| is a subset taken from a population, either by random or non-random sampling techniques | sample |
| is a representation of the population with which one hopes to draw valid conclusions from about the population. | sample |
| is a selection of n elements derived from a population N, which is the subject of the investigation or experiment, in which each sample point has an equal chance of being selected using an appropriate sampling technique | random sample |
| a sampling technique where in every member of the population has an equal chance of being selected. | Lottery sampling |
| a sampling technique in which members of the population are listed and samples are selected in intervals called sample intervals. | Systematic random sampling |
| a sampling procedure wherein the members of the population are grouped based on their homogeneity. | Stratified random sampling |
| sometimes called area sampling, it is applied on a geographical basis. It is generally done by sampling at the higher levels first before going down to the lower levels. | Cluster sampling |
| done using a combination of different sampling techniques. For instance, when selecting respondents for a national election survey, we can make use of the lottery method first for regions and cities. | Multi-stage sampling |
| only those whom the researcher meets by chance are included in the sample when using this technique | Accidental sampling |
| includes a specified number of persons of certain types to be taken as samples | Quota sampling |
| most convenient and fastest sampling technique that makes use of the telephone, mobile phones, or the internet | Convenience sampling |
| used in very small sample sizes. For example, this can be used if the subjects of the study are deans of certain universities or area managers of certain institutions. | Purposive sampling |
| is a number which describes a sample. It can be directly computed and observed. An example of a statistic is the sample mean, which serves as an estimator for the population mean. | statistic |
| is a descriptive measure of a population. While a statistic can be directly computed and observed, the value of a parameter can be approximated and is not necessarily equal to the statistic of a sample. | parameter |
| is the probability distribution when all possible samples of size n are repeatedly drawn from a population | sampling distribution |
Created by:
annebelle
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