L2: Sampling Flashcards
Sampling
selecting units from a population to estimate its characteristics
Population
Aggregate of units under examination
Why sample?
very large population or if investigation is destructive, expensive, time consuming, and labourious
Random Sampling
units are selected randomly (purest form of probability sampling, each member has an equal chance of being selected)
Stratified Sampling
When population is split into several groups of units, called strata, based on characteristics. Units are randomly selected from each stratum.
Systematic Sampling
First unit selected randomly, then consecutive units are chosen at specified intervals.
Authoritative Sampling
Person makes an educated guess on which units are best to sample
Criteria for selecting sampling plan
objectives, cost, environment, patterns of environmental contamination, site considerations, public concerns
Parameter
refers to population characteristic under examination (mean, sd, etc)
Statistic
refers to sample parameters used to estimate population characteristics (sample mean, sample error)
Bias
refers to how far the average statistic lies from parameter it’s estimating (Error that occurs when estimating a quantity)
Sampling Distribution
Probability distribution, under repeated sampling (numerical quantity calculated from data values in sample)
Probability Distribution
Mathematical definition used to ascertain probability of population parameter to acquire specific value or lie within specific range of values (discrete, continuous)
Distribution
normal, t, F, x2, exponential, lognormal, bionomial, poisson
Random Sampling (rectangular plot)
choose 2 random numbers from table (U1, U2), use formulas x=XU1, y=YU2