Statistics Project: Assessing the Probability of Flight
Delays Due to Weather Conditions
Objective
Determine the likelihood of flight delays under various weather conditions using
Probability Theory.
Data Sources
● Flight Data: Date, flight number, scheduled departure time, actual departure time,
delay duration (in minutes).
● Weather Data: Date, temperature, weather condition (clear, rainy, snowy), visibility.
Steps to Address the Task and Analysis
1. Generate Data:
● Flight data for 1,000 flights.
● Weather conditions for corresponding days.
2. Data Preparation:
● Merge flight and weather data based on the date.
● Classify delays: No Delay (delay < 15 minutes), Minor Delay (15 ≤ delay <
60 minutes), Major Delay (delay ≥ 60 minutes).
3. Descriptive Analysis:
● Calculate the overall probability of delays.
● Summarize weather conditions on days with the highest frequency of
delays.
4. Probability Calculations:
● Determine the probability of delays given specific weather conditions.
● Calculate conditional probabilities, e.g., P(Delay | Snowy).
5. Comparative Analysis:
● Compare delay probabilities across different weather conditions.
6. Interpretation and Conclusion:
● Discuss which weather conditions most significantly impact flight delays. 7. Reporting and Presentation:
● Prepare a report and presentation summarizing the methodology, findings,
and implications.
Execution
Let's implement the first few steps, including generating data and performing
preliminary analyses.
Note: The execution focuses on creating the data and initial descriptive analysis.
Further probability calculations and deeper analysis would follow similarly structured
steps.
Descriptive Analysis Results
The preliminary analysis of our dataset provides the following insights into flight delays
under different weather conditions:
● Clear Weather:
● No Delay: 71.89%
● Minor Delay: 23.40%
● Major Delay: 4.72%
● Rainy Weather:
● No Delay: 71.88%
● Minor Delay: 24.38%
● Major Delay: 3.75%
● Snowy Weather:
● No Delay: 67.33%
● Minor Delay: 26.67%
● Major Delay: 6.00%
Interpretation
From this analysis, we observe that: ● Clear and rainy weather conditions have similar probabilities for no delays and
minor delays. However, clear weather has a slightly higher probability of major
delays compared to rainy weather.
● Snowy weather has a lower probability of no delays and a higher probability of
both minor and major delays compared to clear and rainy weather.
This suggests that snowy weather is more likely to cause both minor and major flight
delays, aligning with expectations that adverse weather conditions can impact flight
schedules.
Continuing the Project
Following this descriptive analysis, the next steps would involve more detailed
probability calculations to quantify the risk of delays under various conditions precisely.
For example, calculating the conditional probability of delays given snowy weather, or
applying Bayesian inference to update delay probabilities as new weather information
becomes available.