Sample - A subset of the population or community that you choose to study that will help you understand the population or community as a whole, Random sampling - is a probability sample that includes respondents selected from a list of the entire population of interest so that each respondent has an equal chance of being selected., Sampling bias - occurs when some members of the population are more or less likely to be selected for participation in your data gathering efforts than others, Generalization - is possible when data gathered from a sample accurately represent the general population from which the sample was drawn., Convenience sampling bias  - occurs when data are collected from respondents who are easy to reach, or who are easy to work with. , Population - A set of similar people, items or events that is of interest for some question or experiment., Sampling unit - The individual person, category of people, or object from whom/which the measurement (observation) is taken, Sample frame - A specific list of units (men, women, households, individuals, children, adolescents, etc.) that you will use to generate your sample. Examples could be a census list or a list of employed teachers, a registration log or a list of project participants, Stratified sample - A type of sampling method in which the population is divided into separate subgroups, called strata. Then, a probability sample is drawn from each subgroup, which allows for the statistical comparison of results within the sample., Margin of error - expresses the maximum expected difference between the true population and the sample estimate, Confidence level - refers to the percentage of all possible samples that can be expected to include the true population parameter., Purposive sampling - primarily used when you want to collect qualitative data, it is a non-probability sample where sampling units that are investigated are based on the judgement of the researcher, Anonymization  - Stripping data of any identifiable information, making it impossible to derive insights on a discrete individual, even by the party that is responsible for the data analysis. , Pseudonymization - Replacing personally identifiable information fields with a code that protects a respondent’s identity,

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