Name: Pangilinan, Maria Angela Q. Section: BSMT1-1D Biostatistics Activity n0.2

Name: Pangilinan, Maria Angela Q.
Section: BSMT1-1D
Biostatistics
Activity n0.2
Answer the following by writing in the blank space below each number. (10 points each)
1. Describe how a random sample of 50 doctors may be drawn from the lists of all doctors
at Zamboanga medical center?
Random sample is the most basic type of sampling technique in which every member of the
population has an equal chance of being chosen to be part of the sample. Hence, one way to do a
random sampling is by using the lottery method. For example, the doctors from ZCMC are assigned
with a unique number. Then, the numbers are written on pieces of paper with identical shape and
sizes. These pieces of paper are then folded and placed in a box where they are thoroughly mixed
together. Without looking, the representative picks the required number of folded pieces of paper.
All the elements bearing the numbers picked by the representative becomes the elements of the
sample.
2. Discuss how to get a random sample of 15 out of 75 students using a systematic

random sampling.
Systematic random sampling is a type of random sampling technique that is simple and
straightforward. Given the equation for systematic sampling: k= N/n, where k is the sample
interval, N is the population size, and n is the sample size is how I can get the random sample of
15 out of 75 students.
k = N/n
k = 75/15
k=5
5 is the sampling interval
The next step is to randomly select a number from 1-5.
(ex. 3) 1st student selected = the 3rd on the list
3. Explain stratified random sampling.
Stratified random sampling is a type of random sampling technique in which the population is first
divided into strata and then the samples are randomly selected separately from each stratum. By
means of strata, it is the population divided into several subgroups based on their characteristics
like gender, year, age, etc. For example, I want to interview 200 students in Universidad de
Zamboanga about their opinion in our new school uniform. I am going to choose my sample by using
stratified sampling by subdividing the population of the students into several strata.
4. Explain how to draw a random sample of 100 respondents from a population with socio-
economic (low, average, high) using stratified proportional allocation?
Proportional allocation is a procedure for dividing a sample among the strata in a stratified sample
survey. Thus, the proportionate stratified random sample will be obtained using this formula:
(sample size/population size) x stratum size.
5. Explain multistage sampling.
Multistage sampling is a sampling technique that divides the population into groups (or clusters) for
conducting research. It is also known to be similar to cluster sampling but in more complex form.
This technique is usually used in larger scales where the preparation of the list of all elements in the
population is difficult. For instance, the researcher of Universidad de Zamboanga used multistage
sampling to survey the teachers living in ZC on their attitudes and opinions towards adolescent food
and nutrition education.
6. When is systematic random sampling preferred over simple random sampling?
Systematic random sampling is preferably used over random sampling when the relevant data does
not exhibit patterns, and the researchers are at low risk of data manipulation that will result in
poor data quality.
7. When is stratified random sampling preferred over systematic random sampling?
Stratified sampling techniques are generally used when the population is heterogeneous, or
dissimilar, where certain homogeneous, or similar, sub-populations can be isolated (strata). For
example, a research team is seeking opinions about religion amongst various age groups. Meanwhile,
systematic sampling is preferably used when you want to be straightforward with your data.
8. When is simple random sampling preferred over systematic random sampling?
Simple random sampling is where the elements are chosen randomly from a population, and each
item has an equal probability of being chosen. Systematic random sampling, on the other hand,
involves selecting items from an ordered population using a skip or sampling interval. Thus, the use
of systematic sampling is more appropriate when doing certain researches because there’s a lower
risk of data manipulation. Meanwhile, random sampling is the best method to use in a larger
population and if you want to eliminate sampling bias.
9. Compare stratified random sampling from cluster sampling.
Cluster sampling is a random sampling technique in which the entire population is broken into
small groups and then, some of the clusters are randomly selected. Stratified sampling on the
other hand, is where the samples are randomly chosen from non-overlapping, homogeneous
strata. Consequently, we must always remember that the strata formed in stratified and cluster
sampling should be distinctive and non-overlapping.
10. Contrast stratified sampling from cluster sampling.
Stratified sampling uses more specific characteristics thus, can provide a more accurate
representation of the population based on what's used to divide it into different subsets. Moreover,
cluster sampling selects only certain groups from the entire population. Meaning, the method
requires fewer resources for the sampling process.

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Name: Pangilinan, Maria Angela Q.

2. Discuss how to get a random sample of 15 out of 75 students using a systematic

3. Explain stratified random sampling.

5. Explain multistage sampling.

6. When is systematic random sampling preferred over simple random sampling?

7. When is stratified random sampling preferred over systematic random sampling?

9. Compare stratified random sampling from cluster sampling.

10. Contrast stratified sampling from cluster sampling.

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