Sampling Methods for Transport Research

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Sampling methods

Sampling Method	Description	Advantages	Disadvantages
Simple random	Gives an equal chance for selecting every item in a population	No need for much prior information about the population	Low levels of efficiency. May ignore particular interest groups.
Systematic	Measures samples based on fixed conditions.	High precision Easy computation of errors and analysis of data	Potential data bias because of the periodic ordering of sample elements. Leaves out particular interest groups Low efficiency
Stratified	A random sample from identifiable groups	Captures specific interest groups. Highest precision. Allows optimal allocation and disproportionate sampling	Prior knowledge of population needed Complexities in data analysis.
Cluster	Used when small samples are needed.	Low cost Allows sampling individuals without particular details.	Lowest precision Complexity in data analysis.
Convenience	Test samples selected based on availability and accessibility.	Simplest and easiest. No advance planning needed.	No statistical advantage. Relatively unrepresentative.

Application of sampling methods for collective passenger transport research

Various probability sampling methods can be used to conduct the research because they give equal chances of choosing the participants and makes it easy to analyse and measure outcome accuracy. Simple random, stratified, systematic, and cluster sampling methods are applicable to the research. Through simple random sampling, the researcher selects participants randomly, with every member of the population having an equal chance of selection because it is an equal probability technique. For the study, the researcher creates a table with random numbers and uses the sampling frame to assign numbers to everyone in the population. The method is applicable for the study because collective passenger transport affects a major portion of the population, and there is little geographical dispersion in the area of study.

Stratified sampling is applicable to the research because it enables the research to develop subgroups from the general population based on similar characteristics. After developing subgroups, the researcher chooses samples from each group to obtain a more representative sample for the study. Furthermore, the researcher uses disproportionate or proportionate stratification based on the population size. The technique is applicable to the research given a large number of stakeholders in the collective passenger transport. Through systematic sampling, the researcher is able to develop a constant function to use in sample selection. For instance, the research may decide to include every n^th individual in the study population. The sampling interval varies depending on the population size and the sample size needed for the study, and it always remains constant.

The sample size is determined by the sampling rate, which determines the number of participants chosen. This approach is to help the research because collective passenger transport makes it difficult to identify individual sampling units in the sample frame. Finally, applying cluster sampling in the study is possible given the random natural occurrence of people in the area of study. By sampling using clusters in the area, the study achieves a representative sample. Collective passenger transport involves a large number of people, sometimes dispersed in a different location, which makes the method more appropriate. The approach requires the researcher to identify the most effective clustering method based on a definite factor such as geography, and then selects a sample from the clusters, which would represent the whole population.

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Sampling Methods for Transport Research

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