Correlation

Correlation

Question 8 A: Variables

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Two variables can be considered in responding to this question. The two are public vehicles and waiting times. Assume the following information is provided:

Public vehicles	43	21	25	42	57	59
Minutes to wait	99	65	79	75	87	81

 

The correlation coefficient between the two variables, as calculated, is r = 0.5298, which lies between 0.4 and 0.6. Notably, it indicates a moderate or medium association. According to Jayatilake et al. (2021), there is a positive relationship between automobiles and waiting time whereby they argue that as the number of public automobiles increases, personal cars reduce, leading to shorter wait times due to less traffic.

Question 8 B: Concept Learned and Its Application

Consider the association between the percentage of helmet use by motorcyclists and the fatality rate. A negative relationship between the two variables will be expected by considering fatality as the dependent variable and the use of helmets as the independent variable (Wang et al., 2021). Notably, this is so because as the number of people who wear helmets increases, the number of people who die in motorcycle accidents decreases. Assuming the following information is made available:

Year	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Percentage of Helmets Used by Motorcyclists (%)	58	48	51	58	63	67	64	66	60	60
Fatality rate	4028	4576	4837	5174	5312	4469	4518	4630	4986	4668

The fatality rate matches the prediction made before the actual test is conducted. As a result, I have used the charts and graphs learned in class to estimate the association between two variables. In the future, I will be using the obtained knowledge to test the relationship among various items and make meaningful conclusions. For instance, in the case above, I would remind people always to wear helmets to reduce the number of accidents. Further, I will apply the knowledge to estimate the opening and closing prices in the stock market.

References

Jayatilake, S., Bunker, J. M., Bhaskar, A., & Miska, M. (2021). Time-space analysis to evaluate the cell-based quality of service in bus rapid transit station platforms through the passenger-specific area. Public Transport, 13(2), 395-427.

Wang, X., Chen, J., Quddus, M., Zhou, W., & Shen, M. (2021). Influence of familiarity with Traffic regulations on delivery riders crashes and helmet use: Two mediators ordered logit models. Accident Analysis & Prevention, 159, 106277.

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Unit 8 Discussion: CorrelationUnit 8 Discussion: Correlation
Question 8 A
Pick any two variables that you feel may be related and estimate what you think the strength of the correlation coefficient would be for those two variables. In your response, estimate the value of r. For example, specify a strong (.7 to .9), medium (.4 to .6), or low (0 to .3) value for r. The value of the coefficient can be positive or negative. For example, consider an increase in police patrols in a neighborhood and the number of burglaries that occur in that neighborhood. I would say that would be a strong inverse relationship with an r-value of -0.8; as one (patrols) increases, the other (burglary rate) goes down. Describe the factors that you think would contribute to why the variables would have the relationship that you estimate it to be.

Question 8 B
Now that you have completed this course in Statistics, please describe a concept covered in the course that you feel might be of assistance to you now or in the future. For example, using charts and graphs to graphically describe data at your job, or using one of the sampling methods discussed at the beginning of the course to generate sample data. Please be specific in explaining how you would use what you have learned in class to your benefit.