Guidebook for Conducting Airport User Surveys (2009) / Chapter Skim
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Pages 27-44
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From page 27... ...
With discrete data (e.g., the number of people in a travel party) , each possible value (1, 2, 3, etc.)
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From page 28... ...
3.2 Statistical Accuracy and Confidence Intervals The characteristics of interest of the population being surveyed, such as the mode of travel to the airport, will vary across the members of the population. Aggregate measures of the population, such as the proportion of air passengers accessing the airport by taxi, can be estimated from the corresponding values for the sample.
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From page 29... ...
Statistical Concepts 29 2 The theory underlying this statement can be found in any statistics textbook. 3 Under the Central Limit Theorem, the probability distribution of the sample average will approach the Normal distribution as the sample size approaches infinity.
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From page 30... ...
For example, a range of 50% ± 5 percentage points is equivalent to the range 45% to 55%. Expressing the Accuracy of Variables Expressed as a Percentage For categorical variables, results are often expressed as a percentage of the sample, for example, the percentage of air passengers who use transit to access the airport.
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From page 31... ...
For example, it is common to perform air passenger surveys in departure lounges, because passengers are more willing to be interviewed or fill out a survey form when they are no longer anxious about whether they will make their flight and they are sitting down. However, this locale constrains the sample to those passengers on a set of flights, and does not provide a truly random sample of all passengers using the airport.
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From page 32... ...
and passengers are sampled for each flight in proportion to the passengers on the flight would represent a controlled sample. Thus a self-completed air passenger survey in which flights are selected in proportion to the number of flights in broadly defined markets and survey forms are given to every adult passenger on those sampled flights would qualify as a controlled sample.
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From page 33... ...
For air passenger surveys, the sample size is typically so small relative to the population and the methodology is such that there is very little likelihood of surveying the same person twice.5 For most other airport user surveys, the methodology precludes sampling the same respondent twice. Obtaining a truly random sample is often difficult, particularly for airport surveys.
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From page 34... ...
One common application of sequential sampling in air passenger surveys is to list flights by departure time (and destination to resolve flights with the same departure time) and select every nth flight to survey.
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From page 35... ...
A common example of cluster sampling in airport surveys is the use of individual flights as clusters, with the flights to be surveyed being selected using random, sequential or stratified sampling. Then either all passengers on each selected flight or a sample of passengers on those flights are surveyed.
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From page 36... ...
by identifying the value to be gained from improved precision. For any desired degree of precision in the survey results, the need to consider subgroups of interest -- such as air passengers with ground origins in a particular area or visitors on business trips -- will increase the required sample size of the overall survey in order to ensure a large enough number of respondents in the subgroup(s)
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From page 37... ...
Table 3-3 gives the required sample size using random sampling, based on the 50% proportion, for various confidence intervals and a range of population sizes. Alternatively, the sample size for an accuracy of ±a percentage points10 can be calculated for a 95% confidence level using the following expression:11 where n is the sample size, N is the population size, a is the width of the confidence, and p is the estimated proportion of the population in the category of interest.
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From page 38... ...
Table 3-3. Required sample size using random sampling for various sized confidence intervals and a range of population sizes.*
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From page 39... ...
Examples of the mean, standard deviation, SEE and accuracy of estimate (95% confidence interval) , and required sample sizes for accuracy to within 10% of the mean for selected air passenger characteristics from some airport surveys are given in Table 3-4.
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From page 40... ...
Examples of 95% confidence intervals and sample sizes for selected air passenger characteristics from some recent airport surveys. With Sample Size = 400 Variable Mean Standard Deviation 95% Confidence Interval*
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From page 41... ...
• Cluster sampling with random sampling of flights and surveying of all passengers on those flights was found to be very inefficient, increasing the sample size required by a factor of 9 or more compared to random sampling. • Cluster sampling with stratified sampling of flights by sector greatly improves the efficiency of cluster sampling.
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From page 42... ...
In comparing the required sample sizes for different sampling methods, it should be borne in mind that true random sampling of air passengers is almost impossible to achieve, as discussed in Chapter 5. 3.4.4 Determining Desired Accuracy While the mathematics of calculating required sample size is generally fairly straightforward, deciding on the appropriate desired level of accuracy is anything but, because it depends on the consequences of being wrong.
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From page 43... ...
Some groups are over-sampled and some are under-sampled, because of the sampling approach adopted or the inevitable variability in executing the planned sampling approach. The objective of assigning weights to the individual survey responses is to correct for these differences and improve the accuracy of the results.
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From page 44... ...
Therefore, it is desirable for passenger surveys to ask how many people are traveling together on the same flight as well as how many people traveled to the airport together with the respondent. This specificity will allow separate weights to be calculated for the air travel party characteristics and the ground access travel characteristics.
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