spdf sampleStratified(FinalClassImg, 200, sp T) This generates 200 points per landcover class but what I really need is a variable number of samples based on the overall landcover pixel totals. If we had not used STRATIFIED RANDOM SAMPLING we might have reached a similar proportion, or by chance, we might have had over representation of one of the groups. In other words a proportional stratified random sample. The sample we selected is exactly proportional to the population with regards to teaching level. Compare disproportionate stratified sampling. Stratified sampling is when the population is divided into specific groups and then randomly sampled from those groups. Stratified sampling lowers the chances of researcher bias and sampling bias, significantly. It is a smart way to ensure that all the sub-groups in your research population are well-represented in the sample. We do the same for the high school teachers and select 60. A probability sampling method in which different strata in a population are identified and in which the number of elements drawn from each stratum is proportionate to the relative number of elements in each stratum. Stratified sampling helps you to save cost and time because you’d be working with a small and precise sample. Similarly, we use a list of all of the middle school teachers and randomly select 40 (20% of 200). To achieve this, we obtain a list of all of the elementary teachers in the system. Since 50% of those teachers need to be elementary teachers, we need 100 elementary teachers in our sample (200 X. Let’s also assume that we want to sample 200 teachers.

Because those percentages exist in our population, we want our sample to have the same percentages. Stratified sampling is a variance reduction technique that constrains a proportion of sample paths to specific subsets (or strata) of the sample space. The first of these designs is stratified random sampling. For this example, we will use 50%, 20% and 30% respectively. Assume we want the teaching level (elementary, middle school, and high school) in our sample to be proportional to what exists in the population of Hartford teachers.įirst we must determine what percentage of the teachers in the Hartford system are elementary, middle school, and high school. Suppose we wish to study computer use of educators in the Hartford system. STRATIFIED RANDOM SAMPLING – A representative number of subjects from various subgroups is randomly selected.

Stratified proportional random sampling