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Statistical techniques for transport...

Molugaram, Kumar.

Statistical techniques for transportation engineering

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistical techniques for transportation engineeringKumar Molugaram, G. Shanker Rao.
作者:	Molugaram, Kumar.
其他作者:	Rao, G. Shanker.
出版者:	Oxford :Butterworth-Heinemann,2017.
面頁冊數:	1 online resource
附註:	Includes index.
標題:	Transportation engineeringStatistical methods.
電子資源:	https://www.sciencedirect.com/science/book/9780128115558
ISBN:	9780128116425 (electronic bk.)

Statistical techniques for transportation engineering
Molugaram, Kumar.

Statistical techniques for transportation engineering[electronic resource]/Kumar Molugaram, G. Shanker Rao. - Oxford :Butterworth-Heinemann,2017. - 1 online resource

Includes index.

Statistical Techniques for Transportation Engineering is written with a systematic approach in mind and covers a full range of data analysis topics, from the introductory level (basic probability, measures of dispersion, random variable, discrete and continuous distributions) through more generally used techniques (common statistical distributions, hypothesis testing), to advanced analysis and statistical modeling techniques (regression, AnoVa, and time series). The book also provides worked out examples and solved problems for a wide variety of transportation engineering challenges.

ISBN: 9780128116425 (electronic bk.)Subjects--Topical Terms:

543982
Transportation engineering
--Statistical methods.Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: TA1145 / .M65 2017

Dewey Class. No.: 629.04

Statistical techniques for transportation engineering
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300 $a 1 online resource
500 $a Includes index.
520 $a Statistical Techniques for Transportation Engineering is written with a systematic approach in mind and covers a full range of data analysis topics, from the introductory level (basic probability, measures of dispersion, random variable, discrete and continuous distributions) through more generally used techniques (common statistical distributions, hypothesis testing), to advanced analysis and statistical modeling techniques (regression, AnoVa, and time series). The book also provides worked out examples and solved problems for a wide variety of transportation engineering challenges.
588 0 $a Online resource, title from PDF title page (EBSCO, viewed March 12, 2017).
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