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Strategies for Effective Transportation Data Collection and Sample Size Estimation

Learn about data collection techniques, sample size estimation, statistical inference in transportation planning. Explore various data collection methods and sample size terminology with practical scenarios.

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Strategies for Effective Transportation Data Collection and Sample Size Estimation

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Presentation Transcript

  1. Transportation Planning CE 573 Lecture 5

  2. Topics • Data collection issues • Sample size estimation • Statistical inference

  3. Data Collection • Location • Cordon • Screen line • Isolated point • Time • Peak • Off-peak • Days of week • Days of year • Survey instrument • Questions • Device • Personnel • Work shifts • Individual capabilities • Communications

  4. Sample Size Terminology • Mean ( ) • Sample standard deviation (sx) • Sample size (n) • Confidence level (α) • Confidence interval limits (+/-Δ) • Test statistic (t) • Population size (N) • More help: http://edis.ifas.ufl.edu/PD006

  5. Sample Size • Test statistic • Critical value (see table given α/2 and degrees of freedom) n-1 • Calculated value  • Confidence interval limit as proportion of the mean  • n  

  6. Sample Size Adjustment • Adjusting for small population size (N) • Redefine n as n’, with n being the adjusted sample size • n’  unadjusted population size calculated • n  adjusted population size

  7. Survey Scenario • What kind of sampling should you do? • Random or • Stratified random • Depends on • Cost of sending survey • Cost of processing survey

  8. Survey Scenario • Say n must be at least 50 for each cell or population category • Random sample • Smallest proportion  0.05 • Total sample size is 50/0.05 = 1,000 observations • Stratified sample • Preliminary survey of 1,000 • Get addresses of 50 households in each cell • Total sample size is 4 * 50 = 200 (50 for each cell) • Do you need to adjust the sample size by cell?

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