Math Stats

• A population refers to an entire group that is under study or investigation
• A sample is a subset taken from a population, either by random or non-random sampling techniques. A sample is a representation of the population
• A random sample is a selection of n elements derived from a population N, which is the subject of the investigation or experiment
• Lottery sampling – a sampling technique where in every member of the population has an equal chance of being selected.
• Systematic random sampling – a sampling technique in which members of the population are listed and samples are selected in intervals called sample intervals.
• Stratified random sampling– a sampling procedure wherein the members of the population are grouped based on their homogeneity.
• statistic is a number which describes a sample
• parameter is a descriptive measure of a population.
• sampling distribution is the probability distribution when all possible samples of size n are repeatedly drawn from a population.
• Cluster sampling – sometimes called area sampling, it is applied on a geographical basis.
• Multi-stage sampling – done using a combination of different sampling techniques.
• A non-random sampling is used when the sample is not a proportion of the population and there is no system for selecting a sample.
• Accidental sampling – only those whom the researcher meets by chance are included in the sample when using this technique
• Quota sampling – includes a specified number of persons of certain types to be taken as samples
• Convenience sampling – most convenient and fastest sampling technique that makes use of the telephone, mobile phones, or the internet
• Purposive 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.