| Description |
1 online resource |
|
text txt rdacontent |
|
computer c rdamedia |
|
online resource cr rdacarrier |
| Note |
Includes index. |
|
Online resource, title from PDF title page (EBSCO, viewed March 12, 2017). |
| Summary |
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. |
| Contents |
Front Cover -- Statistical Techniques for Transportation Engineering -- Copyright Page -- Contents -- Preface -- 1 An Overview of Statistical Applications -- 1.1 Introduction -- 1.2 Probability Functions and Statistics -- 1.2.1 Discrete Versus Continuous Functions -- 1.2.2 Distributions Describing Randomness -- 1.2.3 Data Organization -- 1.2.4 Common Statistical Estimators -- 1.2.4.1 Measures of Central Tendency -- 1.2.4.2 Measures of Dispersion -- 1.3 Applications of Normal Distribution -- 1.3.1 The Standard Normal Distribution -- 1.3.2 Characteristics of the Normal Distribution Function -- 1.4 Confidence Bounds -- 1.5 Determination of Sample Size -- 1.6 Random Variables Summation -- 1.6.1 The Central Limit Theorem -- 1.6.1.1 Sum of Travel Times -- 1.6.1.2 Hourly Volumes -- 1.6.1.3 Sum of Normal Distributions -- 1.7 The Binomial Distributions -- 1.7.1 Bernoulli and the Binomial Distribution -- 1.7.2 Asking People Questions Survey Results -- 1.7.3 The Binomial and the Normal Distributions -- 1.8 The Poisson Distribution -- 1.9 Testing of Hypothesis -- 1.9.1 Before-and-After Tests With Two Distinct Choices -- 1.9.1.1 Application: Travel Time Decrease -- 1.9.1.2 Application: Focus on the Travel Time Difference -- 1.9.2 Before-and-After Tests With Generalized Alternative Hypothesis -- 1.9.2.1 An Application: Travel Time Differences -- 1.9.2.2 One-Sided Versus Two-Sided Tests -- 1.9.3 Other Useful Statistical Tests -- 1.9.3.1 The t-Test -- 1.9.3.2 The F-Test -- 1.9.3.3 Chi-Square Test: Hypotheses or an Underlying Distribution f(x) -- 1.10 Summary -- 2 Preliminaries -- 2.1 Introduction -- 2.2 Basic Concepts -- 2.2.1 Characteristics -- 2.2.2 Attributes -- 2.2.3 Variables -- 2.2.4 Numeric Variables -- 2.2.5 Categorical Variables -- 2.2.6 Data -- 2.2.6.1 Primary Data -- 2.2.6.2 Secondary Data -- 2.2.7 Classification and Tabulation. |
|
2.3 Tabulation of Data -- 2.4 Frequency Distribution -- 2.4.1 Simple Frequency Distribution -- 2.4.2 Grouped Frequency Distribution -- 2.4.2.1 Solved Examples -- 2.5 Cumulative Frequency Table -- 2.5.1 Less Than Cumulative Frequency Table -- 2.5.2 More Than Cumulative Frequency Table -- 2.6 Measures of Central Tendency -- 2.7 Arithmetic Mean -- 2.7.1 Simple Arithmetic Average -- 2.7.1.1 Shortcut Method (Method of Deviations) -- 2.7.2 Weighted Arithmetic Mean -- 2.7.2.1 Combined Arithmetic Mean -- 2.7.2.1.1 Solved Examples -- 2.7.3 Merits of Arithmetic Mean -- 2.7.4 Demerits of Arithmetic Mean -- 2.7.5 Properties of Mean -- 2.7.5.1 Solved Examples -- 2.7.6 Statistical Applications to Transportation Engineering -- 2.8 Median -- 2.8.1 Merits of Median -- 2.8.2 Demerits of Median -- 2.8.2.1 Solved Examples -- 2.9 Mode -- 2.9.1 Merits of Mode -- 2.9.2 Demerits of Mode -- 2.9.2.1 Solved Examples -- 2.10 Geometric Mean -- 2.10.1 Merits of Geometric Mean -- 2.10.2 Demerits of Geometric Mean -- 2.10.2.1 Solved Examples -- 2.11 Harmonic Mean -- 2.11.1 Merits of Harmonic Mean -- 2.11.2 Demerits of Harmonic Mean -- 2.11.3 Relation Between AM, GM, and HM -- 2.11.3.1 Solved Examples -- 2.12 Partition Values (Quartiles, Deciles, and Percentiles) -- 2.12.1 Quartiles -- 2.12.2 Deciles -- 2.12.3 Percentiles -- 2.13 Measures of Dispersion -- 2.13.1 Characteristics of an Ideal Measure of Dispersion -- 2.13.2 Types of Measures of Dispersion -- 2.14 Range -- 2.14.1 Coefficient of Range -- 2.14.2 Merits of Range -- 2.14.3 Demerits of Range -- 2.14.4 Uses of Range -- 2.15 Interquartile Range -- 2.16 Quartile Deviation -- 2.16.1 Coefficient of Quartile Deviation -- 2.16.1.1 Merits of Quartile Deviation -- 2.16.1.2 Demerits of Quartile Deviation -- 2.17 Mean Deviation -- 2.17.1 Coefficient of Mean Deviation -- 2.17.2 Merits of Mean Deviation. |
|
2.17.3 Demerits of Mean Deviation -- 2.17.4 Uses of Mean Deviation -- 2.18 Standard Deviation -- 2.18.1 Coefficient of Standard Deviation -- 2.18.2 Merits of Standard Deviation -- 2.18.3 Demerits of Standard Deviation -- 2.18.3.1 Uses -- 3 Probability -- 3.1 Introduction -- 3.2 Classical Probability -- 3.2.1 Properties of Classical Probability -- 3.2.2 Probability of Failure -- 3.3 Relative Frequency Approach of Probability -- 3.4 Symbolic Notation -- 3.5 Axiomatic Theory of Probability -- 3.6 Independent and Dependent Events -- 3.7 Conditional Probability -- 3.8 Multiplication Theorem on Probability -- 3.8.1 Solved Examples -- 3.9 Baye's Theorem -- 4 Random Variables -- 4.1 Introduction -- 4.2 Discrete Random Variable -- 4.3 Probability Distribution for a Discrete Random Variable -- 4.3.1 Probability Mass Function -- 4.3.2 Distribution Function -- 4.3.3 Additional Properties of Distribution Function -- 4.4 Mean and Variance of a Discrete Distribution -- 4.5 Continuous Random Variable -- 4.6 Probability Density Function -- 4.7 Cumulative Distribution Function -- 4.8 Mean and Variance of a Continuous Random Variable -- 4.8.1 Solved Examples -- 4.9 Joint Distributions -- 4.9.1 Joint Probability Function -- 4.9.2 Joint Probability Distribution of Discrete Random Variables -- 4.9.3 Marginal Probability Function of a Discrete Random Variables -- 4.9.4 Joint Distributive Function of Discrete Random Variables -- 4.10 Conditional Probability Distribution -- 4.11 Independent Random Variables -- 4.12 Joint Probability Function of Continuous Random Variables -- 4.13 Joint Probability Distribution Function of Continuous Random Variables -- 4.14 Marginal Distribution Function -- 4.14.1 Marginal Density Functions -- 4.15 Conditional Probability Density Functions -- 4.16 Mathematical Expectation and Moments -- 4.16.1 Properties of Mathematical Expectation. |
|
4.26.7 Variance of Normal Distribution -- 4.26.8 Mode of Normal Distribution -- 4.26.9 Median of the Normal Distribution -- 4.26.10 Moment Generating Function of Normal Distribution With Respect to Origin -- 4.26.11 Mean Deviation of Normal Distribution -- 4.26.11.1 Solved Examples -- 4.26.12 Fitting a Normal Distribution -- 4.26.13 Linear Combination of Independent Normal Variables -- 4.26.14 Fitting a Normal Distribution -- 4.26.15 Normal Approximation to Binomial Distribution -- 4.27 Characteristic Function -- 4.28 Gamma Distribution -- 4.28.1 Mean and Variance of Gamma Distribution -- 4.28.2 Gamma Distribution of Second Kind -- 4.29 Beta Distribution of First Kind -- 4.29.1 Beta Distribution of Second Kind -- 4.30 Weibull Distribution -- 5 Curve Fitting -- 5.1 Introduction -- 5.2 The Method of Least Squares -- 5.3 The Least-Squares Line -- 5.4 Fitting a Parabola by the Method of Least Squares -- 5.5 Fitting the exponential curve of the form y=a ebx -- 6 Correlation and Regression -- 6.1 Introduction -- 6.2 Correlation -- 6.2.1 Types of Correlation -- 6.3 Coefficient of Correlation -- 6.3.1 Properties of Coefficient of Correlation -- 6.4 Methods of Finding Coefficient of Correlation -- 6.5 Scatter Diagram -- 6.6 Direct Method -- 6.7 Spearman's Rank Correlation Coefficient -- 6.7.1 Rank Correlation Coefficient When the Ranks Are Tied -- 6.8 Calculation of r (Correlation Coefficient) (Karl Pearson's Formula) -- 6.9 Regression -- 6.10 Regression Equation -- 6.11 Curve of Regression -- 6.12 Types of Regression -- 6.13 Regression Equations (Linear Fit) -- 6.13.1 Linear Regression Equation of y on x -- 6.13.2 Regression Equation of x and y -- 6.14 Angle between Two Lines of Regression -- 6.15 Coefficient of Determination -- 6.16 Coefficient Nondetermination -- 6.17 Coefficient of Alienation -- 6.17.1 Solved Examples -- 6.18 Multilinear Regression. |
| Subject |
Transportation engineering -- Statistical methods.
|
|
Transport -- Technologie -- Méthodes statistiques.
|
|
TECHNOLOGY & ENGINEERING -- Engineering (General)
|
| Added Author |
Rao, G. Shanker, author.
|
| Other Form: |
Print version: Molugaram, Kumar. Statistical techniques for transportation engineering. Oxford : Butterworth-Heinemann, [2017] 0128115556 9780128115558 (OCoLC)962355157 |
| ISBN |
9780128116425 (electronic bk.) |
|
0128116420 (electronic bk.) |
|
9780128115558 |
|
0128115556 |
| Standard No. |
AU@ 000059694182 |
|
AU@ 000059783609 |
|
AU@ 000066135442 |
|
CHBIS 011069595 |
|
CHNEW 001014168 |
|
CHVBK 499772024 |
|
GBVCP 1004856997 |
|
AU@ 000068882617 |
|
