ABSTRACT
This chapter provides the theory and interpretation of confidence intervals, hypothesis tests, and population comparisons, which are statistical constructs (tools) used to ask and answer questions about the transportation phenomena under study. Despite their enormous utility, confidence intervals are often ignored in transportation practice, and hypothesis tests and population comparisons are frequently misused and misinterpreted. The techniques discussed in this chapter are used to formulate, test, and make informed decisions regarding a large number of hypotheses. The chapter covers a wide variety of methods including the construction of confidence intervals, the use of p-values in hypothesis testing, and the testing of differences between population means and variances. The chapter concludes with the presentation of a number of non-parametric methods including sign and median tests, the Mann-Whitney test, Kruskal-Wallis test, and the chi-squared goodness-of-fit test.
