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Home > Working Scientifically > Experimental Design > Sample Size |
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Introduction In most experiments it is rarely possible to take measurements from every individual in the population either in a laboratory situation or in the field. A sub set or sample is used to estimate the values that might have been obtained had we measured every individual in the population. A sample is made up of a series of sampling units which depend on the type of variable being measured; for example a data value for a particular variable (eg length) recorded for an individual sampling unit (eg a plant) in a sample of n units (eg n= 100) take from the population under investigation (eg plants in a field) Sampling should allow sufficiently reliable information about the particular population under investigation. The type of sampling or rather where the sampling occurs determines how much control; the investigator has over the individuals studied. If the sampling is to take place in the laboratory then the investigator has much greater control in the design of the experiment. Design is critical in determining the sampling strategy and analysis of results. When estimating population parameters from sample statistics, the sample size is important; larger sample sizes usually result in greater statistical reliability. However optimum sample size is a balance between statistical and practical considerations. The general principle that should be used in deciding on appropriate sample sizes or checking whether available sample sizes are adequate is based on ethical considerations in experiments involving human and animal subjects. Sample sizes should be large enough to give a high probability of providing clear evidence of any effects that are of practical importance, but should not be unnecessarily large. |
Sample Size Introduction Characteristics of a good sample Selection Strategies for field sampling Sampling in time Random sampling Simple experiments Block or Latin square designs Stratified sampling
Experimental design aspects Working Scientifically |