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Sampling Methods in Research, Study notes of English

English

An overview of the different sampling methods used in research, including probability sampling techniques such as random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. It explains the key characteristics and applications of each method, highlighting the importance of ensuring that the sample is representative of the larger population. The fundamental concepts and principles of sampling, which are crucial for designing effective research studies and drawing valid conclusions. It serves as a comprehensive guide for researchers, students, and professionals who need to understand the various sampling approaches and their appropriate use in different research contexts.

Typology: Study notes

2022/2023

Available from 08/02/2024

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LESSON: SAMPLING METHODS
Sampling Methods - This refers to the techniques on how to choose the samples
from a population.
- * to draw samples/ samples size in population
There are two types of sampling:
I. Probability Sampling
II. Non-Probability Sampling
1. Probability Sampling
It is a sampling technique that uses randomization to make sure that every
element of the population gets an equal chance to be part of the selected sample.
I. PROBABILITY SAMPLING – chance to be selected or to be drawn
1. Random Sampling
2. Systematic Sampling
3. Stratified Sampling
a. Equal Allocation
b. Proportional Allocation
4. Cluster Sampling
5. Multi-Stage Sampling
1. Random Sampling
Random sampling is a part of the sampling technique in which each sample has an
equal probability of being chosen.
*lotto, bingo, raffle draws
2. Systematic Sampling
Systematic sampling is defined as "a type of probability sampling method in which
sample members from a larger population are selected according to a random
starting point but with a fixed, periodic interval." We call this interval the sampling
interval.
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LESSON : SAMPLING METHODS

Sampling Methods - This refers to the techniques on how to choose the samples from a population.

    • to draw samples/ samples size in population There are two types of sampling: I. Probability Sampling II. Non-Probability Sampling
  1. Probability Sampling It is a sampling technique that uses randomization to make sure that every element of the population gets an equal chance to be part of the selected sample. I. PROBABILITY SAMPLING – chance to be selected or to be drawn
  2. Random Sampling
  3. Systematic Sampling
  4. Stratified Sampling a. Equal Allocation b. Proportional Allocation
  5. Cluster Sampling
  6. Multi-Stage Sampling
  7. Random Sampling Random sampling is a part of the sampling technique in which each sample has an equal probability of being chosen. *lotto, bingo, raffle draws
  8. Systematic Sampling Systematic sampling is defined as "a type of probability sampling method in which sample members from a larger population are selected according to a random starting point but with a fixed, periodic interval." We call this interval the sampling interval.

*The interval is every after 3 if you are going to use systematic sampling

  • Select staring points and apply interval
  1. Stratified Sampling Stratified Sampling is a category under probability sampling which is based on dividing a population into strata, and members of the sample are selected randomly from these strata. In stratified sampling, the strata must be homogenous and also collectively exhaustive, and mutually exclusive as well. The strata must define a part of the population. ● Equal allocation- same or equal number of participants ● Proportional allocation- divide them to the percentage *group to similar characteristics
  • members of the sample are selected randomly
  1. Cluster Sampling Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample. The clusters should ideally each be mini-representations of the population as a whole.