Module 3: Statistics for Logistics

Course Description:

This module covers basic statistics and forecasting techniques that support analysis and planning of complex logistics and transportation systems. It also gives a comprehensive overview of multi-criteria optimization models and methods that can be used in decision making under conflicting objectives.

Contents 
  1. Measurement and describing data

    Measurement levels, exploratory data analysis (EDA) techniques, measures of central tendancy and measures of dispersion.

     

  2. Basic probability distributions

    Basic discrete and continuous distributions, choosing appropriate statistical distributions for data and determining techniques for the problem to be solved.

     

  3. Parametric and Non-parametric statistics

    The links between data and parametric and non-parametric statistical techniques used in hypothesis testing, ANOVA and regression analysis

     

  4. Elementary forecasting techniques

    Moving averages and smoothing methods; components of time series and time series decomposition, Holt’s and winters’ exponential smoothing, new-product forecasting

     

  5. Multi-criteria Decision Making
  6. Relationship with vector type optimization, ordinal and cardinal approaches, normalization methods, utility functions for aggregation, CBA: surplus approach vs. resource cost approach, basic assumptions and application

Ümit Senesen

Instructor: Emeritus Prof. Ümit Şenesen
Istanbul Technical University