Graduate School and Research Center in Digital Sciences

Introduction to Statistics

[Stat]
T Technical Teaching


Abstract

This course is an introduction to statistics. The goal is to equip students with fundamentals in statistics in order to apply this knowledge in solving practical engineering problems. The students will be taught different statistical methods and should be able to make meaningful inferences on relevant datasets.

Teaching and Learning Methods: The course is comprised of lectures, exercises and laboratory sessions.

Course Policies: Attendance to exercises and lab sessions is mandatory.

Bibliography

-          Sheldon M. Ross, "Introduction to Probability and Statistics for Engineers and Scientists", Elsevier Inc., 2009 (4th edition).

-          John Rice, "Mathematical Statistics and Data Analysis", Duxbury Press, 2006 (3rd edition).

-          Morris DeGroot and Mark Schervish. "Probability and Statistics." 4th ed. Pearson

Requirements

Basic calculus

Description

The course will cover the following topics:

-          Graphical and/or numerical summaries of data;

-          Confidence intervals for population characteristics;

-          Statistical tests for hypothesis

-          Linear regression   

Learning outcomes:  Upon successful completion of the course, students will be able to:

-          construct a random sample, compute the descriptive statistics;

-          construct and interpret confidence intervals for the mean other population characteristics;

-          understand the meaning of hypothesis testing and the validation;

-          carry out a linear regression procedure and interpret the result.

Nb hours: 21.00

Grading Policy:Labs and Homeworks (20%), Final exam (80%)

Nb hours: 21.00
Nb hours per week: 3.00