Quantitative Research Lesson 3

Questions and Answers

What does stratified random sampling involve?

Choosing units based on the convenience of the researcher.

Dividing the population into homogeneous subgroups and sampling from each. (correct)

Selecting every kth unit from the population.

Sampling all units within randomly selected geographic clusters.

In systematic random sampling, what is the purpose of the sampling interval 'k'?

It defines how random the selection process is.

It indicates how often each kth unit from the population is selected. (correct)

It determines how many total samples will be taken.

It specifies the types of clusters to be used in sampling.

Which of the following methods is NOT a type of non-probability sampling?

Heterogeneity Sampling

Purposive Sampling

Cluster Sampling (correct)

Accidental Sampling

What is an example of purposive sampling?

Sampling a predefined group with specific characteristics. Signup and view all the answers

Which of the following is a characteristic of cluster random sampling?

It samples all units within selected clusters. Signup and view all the answers

What sample size is needed for a population of 10,000 with a desired margin of error of 2%?

2,000 sample respondents Signup and view all the answers

Which type of sampling ensures that every unit in the population has an equal chance of being selected?

Probability Sampling Signup and view all the answers

What is the sample size required to achieve a 5% margin of error in studying the average income of families in Barangay A with 2,500 residents?

345 sample respondents Signup and view all the answers

What is one advantage of using sampling in quantitative research?

Greater accuracy Signup and view all the answers

What does the term 'sampling frame' refer to in research?

List of sampling units Signup and view all the answers

Which method would NOT typically be used in simple random sampling?

Survey responses Signup and view all the answers

What is the confidence level used for determining a sample size that yields 385 for an infinite population?

95% Signup and view all the answers

Which statement correctly describes non-probability sampling?

It does not involve random selection. Signup and view all the answers

Study Notes

Sampling & Sample Size

Recommended sample size for an infinite population is approximately 385 respondents using standard formulas.
For a 90% confidence level, a standard deviation of 0.6, and a margin of error of ±4%, the required sample size is about 406 respondents.
A sample size of 1,957 is calculated when considering a confidence level of 95% and a population proportion of 0.50.
To achieve a 2% margin of error from a population of 10,000, a sample size of 2,000 is necessary.
For a population of 2,500 residents with a 5% margin of error, a sample size of 345 respondents is adequate.

Sampling Process

Sampling is the process of selecting elements from a larger population.
The target population consists of the entire group of interest, while the sampled population refers to the specific group selected for the study.
A sampling frame is a comprehensive list of all sampling units within the target population.

Advantages of Sampling

Cost-effective approach saving money and resources.
Handles smaller groups easier, simplifying data collection and analysis.
Time-efficient, allowing quicker results.
Produces greater accuracy compared to studying an entire population.

Types of Sampling

Probability Sampling (Random Sampling)

Ensures all units in the population have an equal chance of selection, reducing bias.
Common methods include:
Simple Random Sampling: Basic technique using random selection methods such as paper strips, random number tables, or computer-generated numbers.
Stratified Random Sampling: Divides the population into subgroups and samples randomly from each subgroup.
Systematic Random Sampling: Selects every kth unit after a random starting point, where k is the sampling interval.
Cluster Random Sampling: Groups the population into clusters (e.g., geographical areas) and randomly samples entire clusters.

Non-Probability Sampling (Non-Random Sampling)

Lacks random selection, which may introduce bias.
Common types include:
Accidental, Haphazard, or Convenience Sampling: Based on what is easiest for the researcher, often seen in quick public opinion polls.
Purposive Sampling: Selects samples with a specific purpose or predefined criteria in mind.

Subcategories of Purposive Sampling

Modal Instance Sampling: Focuses on the most common cases.
Quota Sampling: Ensures representation by quotas of specific characteristics.
Expert Sampling: Involves selecting individuals with specific expertise.
Heterogeneity Sampling: Captures a wide range of variations from the population.
Snowball Sampling: Participants recruit other participants, often used for hard-to-reach populations.

Considerations for Choosing a Sampling Technique

Review related literature and studies to guide the selection of an appropriate sampling method.

Description

This quiz covers the concepts of sampling and sample size determination in quantitative research. It emphasizes the importance of understanding the equations and assumptions behind calculating the required sample size for research studies. Prepare to test your knowledge on these key concepts.