Random Sampling and Stratified Sampling - Research Paper Example

Fairness in choosing subjects- each member of the population gets an equal opportunity to be a subject in the study. The unbiased nature of the technology ensures a representative sample for the study. Ease of generalization of findings- because the sample used is representative of the population being studied, it is easier to generalize findings and; therefore make inferences. Random sampling has its limitations, which include: High probability of sampling error- this occurs when the sample chosen is not an accurate representation of the population (Babbie, 2009 pp. 211-212). Limited when dealing with populations with varying demographics- the techniques might not accurately account for the varying differences within a population (Babbie, 2009 pp. 211-212). Stratified sampling Also a type of probability sampling, stratified sampling refers to a sampling technique where the population is divided into sub-groups or strata based on specific criteria.

Subjects are then randomly selected proportionally from the strata (Sandal et al., 2003 p. 100). Split into two major categories: proportionate and disproportionate stratified random sampling, the size of the population and each stratum are compared. As the names suggest, the stratum in the former technique is proportionate to the size of the population, and the reverse holds for the latter technique. A sampling fraction is used to make the comparison (Sandal et al., 2003 p. 100). Advantages of stratified sampling include: Highlighting specific sub-group within a population Highlighting pre-existing relationships between sub-groups within the population Allowing researchers to study the less obvious sub-groups that are often hard to access with Higher statistical precision due to decreased variability in the sample group, which comprises a representative sample of the different strata Disadvantages of stratified sampling include: Not useful when dealing with populations with limited varying traits It is also challenging to identify appropriate strata for the research study Application to study on “High-cost airlines” More often than not, researchers interested in studying transport-related issues, and specifically air transport use both sampling techniques in combination (Richardson et al., 2000 pp. 81-84).

At first, the researcher uses random sampling to identify the flights. The passengers in the flights are then split into different strata based on various demographic information such as gender, vocation/income, and age among others. Stratified sampling proves useful in splitting the passengers into various strata. After identifying subjects, researchers use research instruments such as administering questionnaires to collect the information they need. In this case, researchers are interested in studying factors related to “High-cost airlines”. Using the techniques in combination allows the researchers to find out whether factors such as income, age, vocation, and gender among others predispose passengers to use such airlines. They are then able to make inferences, which will enable airline owners to strategize (Gov.UK, 2013).