The Business Aviation calendar includes several mainstay industry predictions on future sales and trends, based on surveys of aircraft owners and operators worldwide. What’s needed to ensure these can be considered reliable projections? Dean Roberts explores…
In recent months, polling and surveys have taken center stage in the media, with a special focus on methodologies and accuracy driven by the recent US Presidential election coverage.
But these same issues extend to the rapidly growing survey industry in Business Aviation, where accuracy and methodology are vital. Following, we’ll put survey practices into context, exploring the essentials of robust survey design and the implications of choosing the right methodology.
In Business Aviation, survey work spans everything from informal polling at industry conferences—quick polls that stimulate expert panel debates—to rigorous statistical surveys designed to refine aircraft attributes with multi-million-dollar implications.
Not all surveys are created equal. Different goals require different survey methods. It's a "right tool for the job" mentality that’s worth remembering as we revisit survey basics, examine key issues, and offer guidance on selecting the most effective survey methodology.
Statistical Accuracy: The Core Metrics
Assessing survey accuracy rests on two essential metrics: confidence level and margin of error.
1. Confidence Level: This tells us how likely it is that the sample accurately reflects the larger population. In business research, a 95% confidence level is typical.
2. Margin of Error: This represents the amount of error acceptable in the results. In business, a margin of error of ±4-5% is common, while medical research typically demands a narrower margin of ±3% (at a 99% confidence level).
With these metrics in hand, researchers can determine the ideal sample size needed for a given population. Conversely, if you know the population, the sample size achieved, and required confidence level then you can calculate the margin of error to assess the survey’s reliability.
For example, to survey the business jet/turboprop owner population of approximately 21,000 with a 95% confidence level and a margin of error of ±4-5%, a randomized sample size of around 450 respondents would be needed.
Why Random Sampling Matters in Aviation Polls
Random sampling is crucial because it ensures a survey’s results truly represent the larger population, making findings more reliable. Here’s why:
• Reduced Bias: In a random sample, every individual in the population has an equal chance of being selected, which minimizes systematic bias and prevents any one group from being over- or underrepresented.
• Enables Probability Theory Use: With a random sample, researchers can calculate meaningful metrics like margin of error and confidence level, which help quantify the reliability of results.
Random sampling is the foundation of credible survey data because it provides a balanced view of the population, enabling actionable insights. Therefore, it’s essential for the surveyor to know the population size and obtain an adequate random sample to ensure results with real statistical worth.
This article was written by Dean Roberts, VP Strategy, Sustainability and Development at Rolland Vincent Associates and published in the January 2025 edition of AvBuyer, page 30.