1. Sizes and parking locations of aircraft
Oliver King

2. Summary
I have conducted a study of the Essex County Airport (KCDW) in order to determine if there is a relationship between the size of the planes and where they are parked

3. Design
In order to do this, I have divided the airport into four parking zones, then recorded the amount of aircraft of each size.

4. Design Pt. 2
For the purposes of this study, I have divided the aircraft into three different categories:
Light - Any single engined propeller aircraft with a length of L<10 metres
Medium - Any twin-engined propeller aircraft with a length of L<10 metres, or any single engine propeller aircraft with a length of L<12 metres
Heavy - Any twin-engined propeller or jet aircraft with a length of L>10 metres, or any single engine propeller aircraft with a length of L>12 metres
Length was measured by determining the model of aircraft and referring to officially published specifications

5. Photos

6. Data Observed Values 1 2 3 4 Total Small 11 48 29 19 107 Medium 9
Large 8 15 53 33 23
124

7. Data Pt. 2 Expected Values 1 2 3 4 Total Small 12.94 45.73 28.48 19.85
107
Medium
1.09
3.85
2.40
1.67 9
Large
0.97
3.42
2.13
1.48 8 15 53 33 21
124

8. Test
Because I am testing the relationship between two categorical variables, I will be performing a Chi-Square test for homogeneity.

9. State
H₀: There is no difference in the distribution of aircraft size across different parking areas
Hₐ: There is a difference in the distribution of aircraft size across different parking areas
Population is all aircraft which park at the airport in a given year

10. Plan Random- The data comes from a simple random sample
10%- The sample size of 118 is less than 10% of the sample size
Large Counts- Not all expected counts are greater than 5. Therefore, we will proceed with caution
We will be using a Chi square homogeneity test with a critical value of α=0.05

11. Do
Using technology, the calculator’s x² test, with matrix A as observed, and matrix B as expected, gives values of x²= & p= , where x² is the chi-square statistic, and p is the p-value

12. Conclude
Because the p-value, p= , is greater than the critical value α=0.05, we fail to reject the null hypothesis. We do not have convincing evidence that there is a difference in the distribution of aircraft sizes across different parking areas.

13. Possible errors
Because some of the expected counts for the chi-square test were below 5, this may have skewed some of the results