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Introduction
As technology improves, aircraft design naturally improves alongside safety measures yet accidents are unavoidable. Over the years, aircraft accidents are reportedly occurring throughout the world. The world has experienced major and minor accidents in the air. An accident that involves an aircraft is called aviation accident. The term is defined by the Convention on International Civil Aviation as the event that happened within a boarding of a person to the aircraft who has the intention of flying the vehicle which caused death or serious injury to any person riding it. It is also the event wherein the vehicle experienced a considerable amount of damage or any incident that could affect the wellbeing of the operations. The missing or the destroy of the aircraft is also considered an aviation accident.
Aircraft accidents and disasters are unavoidable. With the developments in technology, the safety of traveling through aviation has significantly improved over the years. This research is about the aircraft related accidents that occurred from 1982 to 2013 under part 121 but data earlier than 1982 is not available.
The purpose of this study is to provide the difference in the rate between the number of fatal aircraft accidents and the number of non fatal aircraft accidents. This study used the data published by FAA under all US operations for part 121. The analysis relies heavily on these data and does not take into account aircraft accidents under the different international and local aviation teams. Data earlier than 1982 is not available thus, this study only used the number of aircraft accidents from 1982 to 2013. In order to lessen the risk of false negative results which the limitation of data may bring, this study used Priori method such as T test. After the analysis and computation of the data, the result rejected the null hypothesis that the number of fatal aircraft accidents is equal to the number of non fatal accidents. This findings suggest that there is a significant difference between fatal and non fatal accidents related to aviation.
Methodology
Research Methodology and Sample Selection
The type of research that will be used in this study is quantitative research. The researcher used convenient method using the data published by FAA from 1982 to 2013.
This study will use a total of 64 US pilot operations under part 121 of which aircraft accidents occur. This will serve as the dependent variable from which the independent variables: fatal and non fatal aircraft accidents will be analyzed to determine the relationship between the two. The data available will be computed and presented in numerical representations and through statistical analysis. To ensure that the sample size is big enough, the researcher conducted a power analysis calculation. This was done by determining first the type of test plan that will be used for this study which is Independent T-test. The alpha value that will be used is 0.05 and the expected effect size is 0.7. After inserting the values, the computation resulted to the power of 1.00.
Data Analysis
There were 64 US pilot operations under part 121 in the sample for this study. Based from the data gathered from 1892 to 2013, these operations led to 80 fatal and 825 non-fatal aircraft accidents. The values for these operations are presented in Figure 1.0.
Using the data in Figure 1.0, setting the fatal aircraft accidents and non fatal aircraft accidents data as the independent variables and the number of US operations under part 121 as the dependent variable, the researcher tested the two independent samples using a priori study. The priori study is used to minimize the risk of a false negative result due to the absence of data earlier than 1982.
The claim being investigated is that there are no significant difference between fatal aircraft accidents and non fatal aircraft accidents. Since our research question does not assume a direction, we will use a non directional or two tailed test.
The following values are used for the computation:
Effect = 0.7
Alpha = 0.05
Power = 0.77
The power is reduced due to the lack of data earlier than 1982. The researcher used the data with outliers present because it shows a real case scenario and based on the data collected it provide aircraft accidents that are fatal and non fatal.
levene, p(Levene)= .0001 < alpha (α) =0.05
The result showed that the levene and the alpha are not equal so we have to perform a Normal T test. The null and alternative hypotheses are defined as follows:
Ho: µ fatal = µ non fatal
H1: µ fatal ≠ µ non fatal
Our null hypothesis states that fatal aircraft accidents are equal to non fatal accidents and our alternative hypothesis is that fatal aircraft accidents are not equal to non fatal accidents.
The sample is from an independent population so the degrees of freedom is computed as
df=(n-2)
Substituting with the values given as 64 being the population (n), it was determined that the degrees of freedom for this study is 62.
Using the values of alpha (α) equals to 0.05 and the degrees of freedom equals 62, the T-ratio is calculated. The calculated T ratio resulted to 11.978. The critical value of T for an alpha=0.05 is <insert value>. The computed T statistic of 11.978 exceeds the critical value of <insert value>, so the null hypothesis of fatal aircraft accidents is equal to non fatal accidents is rejected. Therefore, we conclude that there is a significant difference between fatal aircraft accidents and non fatal aircraft accidents.
If we subtract the mean of fatal and non fatal aircraft accidents, it gives a difference of 23.28. The effect size is computed using the formula
R^2= t^2/t^2+df
Inserting the determined values, the effect size resulted to 0.698. The 70% of the variance of fatal and non fatal accident is being explained by part 121 with power equals to 1.00. After the calculation, the 95% Confidence interval are determined as 19.33 and 27.23.
If we were to randomly select 100 from two population each of size samples of size n= 32, then 95 of those samples would have a difference in aircraft accidents being fatal and non fatal between ( 19.33, 27.23).
Zero is not a possible value and this confirms to Reject Ho. The accuracy in parameter estimation is strong because it has a narrow interval.
Discussion
The null hypothesis of this study states that the fatal aircraft accidents do not have significant difference with the number of non fatal aircraft accidents while the alternative hypothesis states that the fatal aircraft accidents are not equal with the non fatal accidents. Based on the result of this study, it was determined that the rate of difference between fatal and non fatal accidents that happened in aircraft is significant. With the larger amount of non fatal aircraft accidents, we can conclude that the safety traveling through aviation has been improved.
Limitations
Every study has its own limitations. With the absence of data in accidents related to aircraft accidents earlier than 1982, this study only used the limited data of fatal and non fatal aircraft accidents from 1982 to 2013.
Delimitations
The study only uses the values generated from all US operations under 121. Accidents related to aviation under the different teams apart of the US operations under 121 were not taken into account.
Conclusion
The determined results rejected the null hypothesis that the number of fatal aircraft accidents is equal to the number of non fatal aircraft accidents. With the outcome disproving that, I have learned that there is a significant difference between the number of fatal aircraft accidents and non fatal aircraft accidents. The knowledge I have acquired from this study allows me to feel more confident on the current technology used by the aircrafts. I feel safer traveling through aviation as I learned that it is now a lot safer to travel using aircrafts than it was in the past decades. As the technology becomes more modern and more ways are being discovered,
