PRE-FINALS - MMW

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Data

are raw information or facts that become useful information when organized in a meaningful way. 

It could be of qualitative and quantitative nature.

Data Management 

is concerned with “looking after” and processing data.

Census 

is the procedure of systematically acquiring and recording information about all members of a given population.

Sample Survey

sampling is a selection of a subset within a population, to yield some knowledge about the population of concern.

1. Experiment

this is performed when there are some controlled variables (like certain treatment in medicine) and the intention is to study their effect on other observed variables (like health of patients). One of the main requirements to experiments is the possibility of replication.

Observation study

this is appropriate when there are no controlled variables and replication is impossible.

Nonprobability sampling

is any sampling method where some elements of the population have no chance of selection or where the probability of selection can’t be accurately determined.

a. Probability Sampling

it is possible to both determine which sampling units belong to which sample and the probability that each sample will be selected. The following sampling methods are example of probability sampling:

Simple Random Sampling (SRS),

all samples of a given size have an equal probability of being selected and selections are independent.

Systematic Sampling – 

relies on dividing the target population into strata (subpopulations) of equal size and then selecting randomly one element from the first stratum and corresponding elements from all other strata.

Stratified Sampling –

when the population embraces a number of distinct categories, the frame can be organized by these categories into separate “strata”. Each stratum is then sampled as an independent sub-population

Cluster Sampling – 

sometimes it is cheaper to ‘cluster’ the sample in some way (e.g. by selecting respondents from certain areas only, or certain time-periods only)

Matched random sampling –

 in this method, there are two (2) samples in which the members are clearly paired, or are matched explicitly by the researcher (for example, IQ measurements or pairs of identical twins)