Cluster Sampling at Ontario International Airport: Detailed Notes

Cluster Sampling: A sampling technique where entire groups (clusters) are chosen at random, rather than selecting individuals from the whole population.
In this case, the clusters are flights out of Ontario International Airport.

Airport management aims to survey customer satisfaction among passengers.
By using cluster sampling, they can manage resources effectively and increase response rates by surveying all passengers on selected flights.

Step 1: Identify Clusters
- Flights departing from Ontario International Airport are the natural clusters.
- These flights can be ordered, for instance, by their departure times.
Step 2: Randomly Select Clusters
- Use a random sampling method (e.g., a calculator or software like R) to select which flights (clusters) will be surveyed.
- This method ensures an unbiased selection of clusters, which represents the broader population of passengers.
Step 3: Surveying the Selected Clusters
- Once a few flights are randomly chosen, all passengers on those selected flights will be surveyed for their feedback.
- This approach increases the likelihood of obtaining comprehensive feedback and insights into customer satisfaction.

Mathematical functions can be utilized to streamline the selection process:
- Use the sample() function to select random flights based on a predefined range (e.g., from the first flight to the last flight).
- Ensure all operational aspects are geared towards ensuring randomness and representativeness of the sample.

Cluster sampling is an efficient method for conducting surveys in scenarios where the population is divided into distinct groups.
Selecting entire groups (flights) rather than individuals can lead to simpler logistics and enhanced response rates, making it a highly effective sampling strategy in this context.