Solution: We are given:
Margin of error

Confidence level

or

Since we are not given the proportion of passengers who prefer aisle seats, therefore we assume it to be


Now, the formula for finding the sample size is:

Where:
is the critical value at 0.1 significance level

rounded to nearest integer