## Questions and Answers

What is the traditional approach in Simple Random Sampling to determine individual samples?

Table of Random Numbers or lottery (fishbowl) method

What is the key feature of Systematic Sampling?

Choosing every kth name on the list

When is Stratified Sampling used?

To ensure fair representation of strata in the sample

What is another name for Cluster Sampling?

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Why is Systematic Sampling often preferred over Simple Random Sampling?

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In what situations is Multi-stage Sampling typically used?

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What is the most commonly used formula in determining the sample size?

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In simple random sampling, why is it said that each member of the population has an equal chance of being selected?

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What does the value of 'z' represent in Lynch et.al.'s sample size formula?

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Why is simple random sampling considered independent?

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What is the margin of error usually set at in the commonly used sample size formula?

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What is the largest possible proportion, 'p', often set to in Lynch et.al.'s sample size formula?

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## Study Notes

### Simple Random Sampling

- Uses two methods: Table of Random Numbers (traditional approach) or the lottery (fishbowl) method
- Both methods are used to determine individual samples/respondents

### Systematic Sampling

- Choosing every kth name on the list
- kth stands for a number between 0 and the size of the sample that you want to select
- Often preferred due to ease and less trouble
- However, it is less precise and violates the assumption of each member having an equal chance to be selected

### Stratified Sampling

- Used to ensure fair representation of strata in the population
- Strata can be entities grouped accordingly, such as class sections, year levels, barangays, etc.

### Cluster Sampling

- Used when the population is large and spread over a large area
- Divides the population into segments, and then selects several segments at random
- Also known as area sampling, often applied on a geographical basis

### Multi-Stage Sampling

- Selection of the sample is done in two or more steps
- Population is divided into first-stage units, then a sample is drawn
- Further stages involve dividing the population into a hierarchy of sampling units

### Probability Sampling

- Requires determining the population size to compute the sufficient sample size
- The Slovin's formula is commonly used: n = 𝑁 / (1 + 𝑁𝑒2)
- Another formula is Lynch, et.al.'s: n = 𝑁𝑧2.𝑝(1−𝑝) / (𝑁𝑑2 + 𝑧2.𝑝(1−𝑝))
- The computed sample size is the minimum required, and the researcher may add more but not less

### Sample Size Formulae

- Slovin's formula: n = 𝑁 / (1 + 𝑁𝑒2)
- Lynch, et.al.'s formula: n = 𝑁𝑧2.𝑝(1−𝑝) / (𝑁𝑑2 + 𝑧2.𝑝(1−𝑝))

### Simple Random Sampling (Under Probability Sampling)

- Each member of the population has an equal and independent chance of being selected
- Equal chance due to no bias, and independent chance due to the choice of one person not affecting the choice of another
- Characteristics of the sample should be close to that of the population

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## Description

Learn about probability sampling and how to determine the minimum sample size needed in research using Slovin's formula. This formula helps researchers calculate the number of respondents or participants required for their study based on the population size.