Provide brief answers to the following questions. Use specific situations and examples where applicable ( In Your Own Words)
Using an example, explain stratified sampling
Stratified sampling
Let us concentrate on the word stratified first. Stratified is made up of STRATA. Strata means smaller groups.
Stratified sampling is a kind of sampling technique that involves classifying the population of interest into smaller groups. From each such group, samples are selected for analysis. From such analysis, inference is derived for the entire population.
Following is an example of stratified random sampling
Let us say there is a school having 1000 students. 100 students of Grades 6 to 10 are selected and questioned about their favorite subjects.
| Grade | Students |
| 6 | 150 |
| 7 | 250 |
| 8 | 300 |
| 9 | 200 |
| 10 | 100 |
| 1000 |
| Grade | Stratified Sample |
| 6 | = 100 / 1000 * 150 = 15 |
| 7 | = 100 / 1000 * 250 = 25 |
| 8 | = 100 / 1000 * 300 = 30 |
| 9 | = 100 / 1000 * 200 = 20 |
| 10 | = 100 / 1000 * 100 = 10 |
Provide brief answers to the following questions. Use specific situations and examples where applicable ( In...
Provide brief answers to the following questions. Use specific situations and examples where applicable Explain briefly interval sampling
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Evaluate and provide examples of the differences between using the general addition rule and conditional probability. In what situations are the approaches most applicable? Provide an example of appropriate use of each approach. (300 words)
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Use specific examples, explain the difference convincingly and in your own words between geometric and configurational isomers
Evaluate and provide examples of the differences between using the general addition rule and conditional probability. In what situations are the approaches most applicable? Provide an example of appropriate use of each approach.
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