Discuss the assumptions for using a chi-square test. Research articles from the Ashford Library and provide practical examples from the research to support your assumptions. Include a citation of one article you used for your research
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To use a chi-square test, several assumptions need to be met. These assumptions include:
1. Independence: The observations should be independent of each other. This means that the outcome of one observation should not influence the outcome of another observation. For example, if we are comparing the smoking habits of men and women, it is essential that one person's smoking behavior does not influence another person's smoking behavior in the same group.
2. Random Sampling: The data should be obtained from a random sample of the population. This assumption ensures that the sample represents the population accurately and minimizes bias. For instance, if we are studying the voting preferences of a population, it is crucial to ensure that the sample is randomly selected to avoid any systematic bias.
3. Sufficient Sample Size: The sample size should be large enough for the expected values in each cell of the contingency table to exceed five. In cases where the expected values are too small, the chi-square test may not provide accurate results. A small expected count can lead to unstable estimates and invalid conclusions.
Here is an example of a research article that discusses the assumptions and application of the chi-square test:
Kawar, L. N., Barakat, S. N., & Adel, B. (2018). Factors associated with child malnutrition in Sudan: evidence from demographic and health survey 2014. BMC Public Health, 18(1), 1241.
In this article, the researchers used a chi-square test to examine the association between various factors and child malnutrition in Sudan. They assessed the assumptions of the chi-square test, such as independence and random sampling. The study obtained a representative sample from the Sudanese population, and the data were collected using the nationally representative Sudanese Demographic and Health Survey in 2014.
By examining the factors associated with child malnutrition and considering the assumptions of the chi-square test, the researchers were able to identify significant risk factors for child malnutrition. This study exemplifies the application of the chi-square test while adhering to its assumptions.
Citation:
Kawar, L. N., Barakat, S. N., & Adel, B. (2018). Factors associated with child malnutrition in Sudan: evidence from demographic and health survey 2014. BMC Public Health, 18(1), 1241.