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Stratifying vs Blocking
Transcript of Stratifying vs Blocking
What is stratifying?
A stratified random sample is a sampling design in which the population is divided into several subpopulations (strata), and random samples are then drawn from each stratum. These random samples are meant to be proportional to the overall population in order to be representative.
What is blocking?
A college campus is 40% girls and 60% boys. Instead of simply gathering a random sample of 100 from the whole population, where you could potentially (however unlikely) get 20 girls and 80 boys, or 70 girls and 30 boys, stratify the population into strata by gender and take a proportional random sample of 40 girls from the girl stratum, and 60 boys from the boy stratum.
When groups of experimental units are similar, it is often a good idea to gather them into blocks. By blocking, we isolate the variables caused by any differences between the blocks, so that we can see the differences caused by treatments more clearly.
In an experimental design, controls, randomization, and replication are all required. Blocking is not.
We need to gather 20 bananas for an experiment. Banana tree #1 only has twelve bananas left on it. We gather the last eight bananas from banana tree #2. The first twelve bananas would be considered the first block, and the last eight the second block, in order to better see the differences caused from them being from different trees.
A highschool is thinking of shutting down its wrestling program. The school paper is interested to learn if the students are upset, so they design a survey. However, they feel that male and female students may have differing opinions on the importance of the wrestling team.
In order to account for this, the newspaper needs to stratify their samples. They will need to create two separate groups, proportional to the overall population, of girls and boys. Then they will need to take simple random samples from each group (stratum).
Some high school students wonder if playing classical music will help kids perform better in mathematics. they get volunteers from elementary, middle, and high schools.
An appropriate blocking variable to use in the experiment would be the schooling level of the students. Each grade level will have different knowledge levels of mathematics, which will need to be taken into consideration. It would be smart to group elementary school, middle school, and high school into 3 different blocks for this reason. Though students would not all score as high as each other, we would expect to see similar increases in math grades from all blocks.
Compare & Contrast
-done with sampling, or a survey
-divides sample into subpopultaions prior to survey
-done with experiments
-divided into blocks after experiment is arranged