Advantages of Sampling Sampling is a necessity in many geographic
research problemsPopulation may be simply too big for 100% contact
Sampling is an efficient and cost-effective method of collecting informationLess time, cost, personnel, etc. required vs.
collecting data on the entire population Sampling can provide highly detailed
informationIn-depth analysis of the few vs. cursory analysis of
the many
Advantages of Samplingcontinued
Sampling allows repeated collection of information quickly and inexpensivelyPhenomena under study may
frequently/rapidly change, requiring updates Sampling can provide a high degree of
accuracyFewer data points allow for detailed study
vs. superficial look at many points
Sampling Error
Randomness must be incorporated to represent population accuratelyBut samples are never 100% accurate
Methodology may introduce systematic errorSampling elements other than the elements
of interest
Sampling Errorcontinued
Improper sampling designWhat method produces the required level of
accuracy? Operational, logistic, personnel
problemsInconsistent collection practices, errors in
recording data
Sampling Procedure
Step 1: Conceptually define target population and target areaTarget Population: the complete set of
individuals from which information is to be collected
Target Area: the entire region or set of locations from which information is to be collected
Sampling Procedurecontinued
Step 2: Designate sample population and sampled area from sampling frameSampling frame: practical structure that
contains the entire set of elements from which the sample will actually be drawn
Sampled population: set of all individuals contained in the sampling frame, from which the sample is drawn
Sampled area: set of all locations within the study area from which the sample is drawn
Sampling Procedurecontinued
Step 3: Select Sampling DesignProbability sampling preferred over
non-probability samplingTypes of probability samples include
random, systematic, stratified, cluster ,and hybrid
Spatial and non-spatial variations in sampling design exist
Sampling Procedurecontinued
Step 4: Design research instrument and operational planDirect observation, field measurement,
questionnaires, personal & telephone interviews
Establish protocols for handling anticipated problems
Logistic & procedural tasks completed before sampling
Sampling Procedurecontinued
Step 5: Conduct pretestTrial run/pilot survey of sample collection
methodCorrect discovered problemsResults may indicate sample size
Sampling Procedurecontinued
Step 6: Collect sample dataConsistency in collection methods and
procedures is essentialEnsure high level of quality control
Simple Random Sampling
All individuals in the sampling frame have an equal chance at selection
All individuals ordered sequentially and chosen by random number generator
Stratified Sampling
Population divided into subgroups/areas then sampled
Stratified Sampling can beProportional: population ratios maintained in
subgroupsDisproportional: population rations not
maintained in subgroups
20% of a city live in apartments – do the subgroups sampled have 20% in apartments?
Cluster Sampling
Population divided into subgroups/areas Some subgroups/areas selected 100% of selected subgroups/areas
sampled
Hybrid Sampling
Combination of sampling designsExample: cluster of individuals sampled on a
systematic time frequency
Point Samplingcontinued
HybridsStratified systematic unaligned point sample
(most widely used)
Disproportional stratified systematic aligned point sample
Point Samplingcontinued
HybridsCluster systematic point sample
Disproportional stratified cluster point sample
Additional Material
Experiment-Resources.com US Census Wiki YouTube