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Division of Engineering and Policy for Cold Regional Environment
11207 Traffic and Transportation System, Probability and Statistics for
Planning and Design
Winter
Description and rationale: This course deals with the basic discussion of experimental design and the
practical use of statistical procedures. It is important to design meaningful experiments for establishing
causal relationship. Also, it is necessary to study the principles of probability to evaluate the significance of
uncertainty on system performance. This course includes fifteen classes. Class 1 shows the need for and
significance of probability. Classes 2 to 4 study the basic experimental design. Classes 5 to 9 describe the
random phenomena and the most important inferential methods. Classes 10 to 11 describe the analysis of
variance. Classes 12 to 13 study regression and correlation analyses. The last two classes introduce the
applications of statistical procedure.
Keywords: probability, statistics, planning, design, uncertainty, model, random variable.
Pre-requisite: none
Expected students: master and doctoral
Instructors: Dr Toru HAGIWARA ([email protected])
Course outline:
(1)
(2)
(3)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(14)
Introduction
It outlines role of probability and statistics in engineering.
Rules for Research
Study five rules that are generally followed to minimize incorrect conclusions from observations.
Standard Experimental Designs(2)
Study components of experimentation, principles of experimental design and control in
experimentation.
Analytical models of random phenomena
Study definition of a random variable and many kinds of useful probability distributions, for example,
the normal distribution, the binomial distribution, the poison distribution, the exponential distribution
and so on.
Functions of random variables
Study the process how to calculate the derived probability distributions. General techniques are given
and illustrated by examples.
Estimating parameters from observational data
Study the role of statistical inference in engineering and the classical approach to estimate parameters.
Random sampling, data description, and some fundamental sampling distributions
Study the notions of population and samples, how to show properties of a set of data and some
fundamental sampling distributions, for example, t-distribution and F-distribution.
Tests of hypotheses
Study the general concepts of statistical hypothesis as a data-based decision procedure.
Analysis of Variance
Study the variance estimates and the evaluation of the F ratio.
Factorial Design
Study concepts of the single and multiple regression models and the correlation analysis.
Regression and correlation analyses (2)
Study concepts of the single and multiple regression models and the correlation analysis.
Applications for the experimental study on the road (2)
Introduce a few experimental studies for driver's behavior. These studies use the experimental design
and the inferential statistics.
Grading: 20%: class participation, 30%: assignments (4-5 assignments are required during the term) and
50%: final exam
Textbooks and references: Handout is distributed and references are indicated in the handout.
referential textbooks are introduced at the beginning of lecture.
01/2007
The