In proportionate stratified sampling each stratums

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In proportionate stratified sampling, each stratum’s size is proportionate to the stratum’s share of the population. Any stratification that departs from the proportionate relationship is disproportionate. ADVANTAGES = Control of sample size in strata, Increased statistical efficiency, Provides data to represent and analyze subgroups, Enables use of different methods in strata DISADVANTAGES = Increased error if subgroups are selected at different rates, Especially expensive if strata on population must be created, High cost iv. Cluster sampling
Similar to stratified sampling Involves dividing population into subgroups (i.e. clusters) Involves random sampling of the clusters and all members of the subgroup are sampled Useful when the population is divided into mutually exclusive subgroups (or clusters), e.g. Suburbs Schools Slabs of beers on a production line Planes arriving at Newcastle Airport Population divided into heterogeneous subgroups. Some are randomly selected for further study. Use when there is a need for more economic efficiency than can be provided by simple random sampling; and Unavailability of a practical sampling frame for individual elements. Several questions must be answered when designing cluster samples. How homogeneous are the resulting clusters? Shall we seek equal-sized or unequal-sized clusters? How large a cluster shall we take? Shall we use a single-stage or multistage cluster? How large a sample is needed?
ADVANTAGES = Provides an unbiased estimate of population parameters if properly done, Economically more efficient than simple random, Lowest cost per sample, Easy to do without list DISADVANTAGES = Often lower statistical efficiency due to subgroups being homogeneous rather than heterogeneous, Moderate cost - Clusters can be areas – area sampling : well defined political or geographical boundaries, low cost, frequently used - Stratified vs Cluster sample VS - Summary of probability sampling methods Stratified Population divided into few subgroups Homogeneity within subgroups Heterogeneity between subgroups Choice of Cluster Population divided into many subgroups Heterogeneity within subgroups Homogeneity between subgroups Random choice of subgroups
v. Double sampling In drawing a sample with double (sequential or multiphase) sampling, data are collected using a previously defined technique. Based on the information found, a subsample is selected for further study. ADVANTAGES = May reduce costs if first stage results in enough data to stratify or cluster the population DISADVANTAGES = Increased costs if indiscriminately used b. Nonprobability samples Subjective approach: Probability of selecting population elements is unknown. Greater opportunity for bias in the sample and distorted findings.

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