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Course 2019-2020 a.y.

20354 - DATA ANALYSIS - PREPARATORY COURSE

EMIT
Department of Decision Sciences

Course taught in English

EMIT (I/II sem. - P)
Course Director:
RAFFAELLA PICCARRETA

Module: E-learning class-group
Instructors:
Class 1: RAFFAELLA PICCARRETA


Mission & Content Summary
MISSION

During the course, techniques for collecting and analyzing data are described. The main concepts of statistical thinking, both descriptive and inferential, are covered. In order to better understand inferential tools, basic concepts of probability theory are presented. Please consider that some of the topics covered in this course are necessary as basic knowledge for the course 20570- Data Analytics and Visualization. Thus, for selected topics online tests are present on the blackboard. This allows to have an immediate feedback on the level of knowledge. Tests are evaluated, and both taking the tests and the performance in them are considered in the final evaluation of exam 20570.

CONTENT SUMMARY

The course focuses on three main parts:

  1. Descriptive analysis of a data set:
    • Data collection, organizing data in tables, graphical presentation methods.
    • Measures of central and non central tendency, measures of variation.
    • Shape of a distribution. Outliers and extreme values.
    • Tabulating and graphing bivariate data.
    • Measures of association and of dependence (association and independence-contingency coefficient mean dependency, linear relationships; covariance, correlation coefficient). Simple linear regression. Some basic concepts on multiple regression analysis are also illustrated.
  2. Probability theory and Random variables:
    • Experiments, sample spaces and events. Definition of probability and rules of probability. Conditional probability and independent events.
    • Random variables: discrete and continuous.
  3. Inferential statistics:
    • Sample and Sampling distribution. Descriptive versus Inferential Statistics.
    • Point and confidence interval estimation.
    • Fundamentals of Hypothesis Testing. Hypothesis test for association (chi-square and correlation). Test for equality of the means (ANOVA). Tests on coefficients in regression models.

Teaching methods
  • Online lectures
DETAILS

Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
  • D.M. LEVINE, T.C. KREHBIEL, M.L. BERENSON, Business Statistics: A First Course, Prentice Hall, 2005, 4th edition.
  • Exam textbooks and online articles.
Last change 05/06/2019 09:07