Discussion board response to underlined part. 200 words

Initial Post

1) Goodness of Fit

The goodness of fit test is a non-parametric test, which is applied to determine how the observed value of a specific phenomenon is expressively dissimilar from the expected value. This test evaluates the level to which theoretical distribution fits the empirical distribution.

This test can be used in EMS to predict hospital admission in emergency department by exploiting administrative data. This means that this test can be used to early predict the necessity for emergency admission and also assist recognize patients that deserve early admission planning, distribution of resources and hence, diminish emergency department crowding (Sun et al., 2011).

2) Test for Homogeneity

Test for homogeneity is a test constructed on the chi-square statistic and used to examine if numerous populations are similar or equal or homogeneous in some features.

This test can be used to improve emergency medical response time by determining whether response time within a given location differs significantly from that of another region and using the observed differences to implement changes so as to improve response time.

3) Test of Independence

The Chi-Square Test of independence is a test based on Chi-Square statistic and it is used to examine whether there is a substantial association between two nominal (categorical) variables. The frequency for every class for one nominal variable is equated along the class of the subsequent nominal variable. The data is then presented on a contingency table within which every row signifies a class for one variable and every column signifies a class for the next variable.

The test of independence can be used by EMS in the fight against the current Opioid overdose by determining how the use of naloxone during resuscitation efforts relates to survival rates of patients (Sumner et al., 2016).

References

Sumner, S. A., Mercado-Crespo, M. C., Spelke, M. B., Paulozzi, L., Sugerman, D. E., Hillis, S. D., & Stanley, C. (2016). Use of naloxone by emergency medical services during opioid drug overdose resuscitation efforts. Prehospital Emergency Care, 20(2), 220-225.

Sun, Y., Heng, B. H., Tay, S. Y., & Seow, E. (2011). Predicting hospital admissions at emergency department triage using routine administrative data. Academic Emergency Medicine, 18(8), 844-850.

Reply

Thanks for sharing your post. Chi-Square analysis plays an essential role in statistics. Chi-Square is used to determine if there is a similarity between variables or not. As stated by Lind, Marchal & Wathen (2015), is most commonly used to evaluate tests of independence especially when using a cross-tabulation. Chi-Square analysis is susceptible to sample sizes especially if the sample population is higher than 500 because any small differences will appear to be statistically significant. I also liked your example that demonstrated the importance of Chi-Square in statistics.