Discussion 6
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School
Southern New Hampshire University *
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Course
665
Subject
Industrial Engineering
Date
Dec 6, 2023
Type
docx
Pages
2
Uploaded by BrigadierNeutron15775
Synopsis: Investigating Aircraft Delays at DFW Airport
Research Problem:
This research aims to identify and understand the primary contributors to
aircraft delays at Dallas/Fort Worth International (DFW) Airport using data
provided by the United States Department of Transportation (USDOT). The
investigation seeks to shed light on the factors influencing flight delays and
explore how these factors vary across different seasons.
Research Question:
What are the main factors contributing to aircraft delays at DFW Airport, and
how do these factors exhibit variations across seasons?
Hypotheses:
Research Hypothesis (
?
1):
Flight delays at DFW Airport are influenced by seasonal variations, with
certain seasons experiencing more delays than others.
Mathematical Representation:
?
1: μ1 μ2 μ3 μ4
Null Hypothesis (
?
0):
There is no significant difference in flight delays at DFW Airport across
different seasons.
Mathematical Representation:
?
0: μ1 ≠ μ2 ≠ μ3 ≠ μ4
Variables/Data:
1.
Flight Delays: Utilizing the ���∂15 column representing the total
number of flights delayed by 15 minutes or more.
2.
Weather-Related Delays: Interpreting the impact of weather on
delays using information from columns such as ����ℎ����.
3.
Seasonal Categories: Deriving seasonal information from
the ����ℎ column, grouped to assess seasonal variations.
4.
Airline Information: Exploring the influence of different airlines using
the ������� and ����������� columns.
5.
Air Traffic Volume: Employing the �������ℎ�� column as a
proxy for air traffic volume to examine correlations with delays.
Statistical Test:
The projected statistical test for this study is ANOVA (Analysis of Variance).
ANOVA will be employed to determine whether there are statistically
significant differences in the means of flight delays across different seasons.
This test allows for the simultaneous comparison of means across multiple
groups (seasons).
Implications from Results:
Understanding the primary factors contributing to aircraft delays at DFW
Airport and discerning seasonal variations can have significant implications
for airport operations, airline scheduling, and overall aviation efficiency.
Identifying the seasons with higher delay rates may inform targeted
interventions and resource allocations to mitigate delays. Additionally, the
research may contribute valuable insights to the broader field of aviation
management and could potentially influence decision-making processes at
both the operational and policy levels.
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