esade

Statistics (2225.YR.009384.2)

General information

Type:

 OPT

Curs:

 3

Period:

 S semester

ECTS Credits:

 6 ECTS

Teaching Staff:

Group Teacher Department Language
Year 3 Jordi Montserrat Adell Operaciones, Innovación y Data Sciences ENG

Prerequisites

Mathematics

Previous Knowledge

The concepts of real function, continuity and derivability and their applications.
The concept of the definite integral. Calculating primitives of elementary functions.

Workload distribution

50% In-class activities
50% Individual study

COURSE CONTRIBUTION TO PROGRAM

Statistics is an essential tool for decision-making in environments where the amount of data and/or level of uncertainty do not allow the information contained to be extracted directly. This course provides some of the theoretical and practical foundations needed for decision-making in the face of uncertainty.

Course Learning Objectives

Upon completing this course students should be able to:

- Use statistical reasoning for its practical applications.
- Understand the different branches of Statistics, their concepts and techniques to be able to use them in the appropriate situations.
- Relate the course to other courses being studied and their future professional career.
- Summarise the information provided by a set of data using descriptive, univariate and bivariate statistical techniques.
- Prepare descriptive statistical reports.
- Use probabilities calculation and probability models to make decisions.
- Apply the techniques learnt in an ethical manner.

CONTENT

1. Descriptive Statistics

Contents:
- Introduction
- Frequency distribution: tables and charts
- Frequency distribution: numerical measures

2. Probability

Contents:
- Introduction to probability: random experiments
- Definition of probability
- Conditional probability & independence
- Probability trees: total probabilities and Bayes' theorem

3. Discrete Random Variables

Contents:
- Introduction to discrete random variables
- Discrete models: Bernouilli, Binomial, Hypergeometric, Geometric, Poisson
- Two-dimensional discrete random variables

4. Continuous Random Variables

Contents:
- Introduction to continuous random variable
- Continuous models: Uniform, Exponential, Normal
- Central Limit Theorem
- Two-dimensional continuous random variables

Relation between Activities and Contents

1 2 3 4
Class participation        
Tests        
Exam on Units 1&2        
Exam on Unit 3&4        

Methodology

Lectures and participatory sessions:

Lectures: Faculty will combine theoretical explanations with exercises. Lecture classes will include tests. Students' marks on these will be taken into account to determine their overall marks for the subject.

Participatory sessions: Some of these classes will focus on preliminary concepts, while others will be dedicated to resolve more advanced problems as defined by faculty. These exercises are to be completed by the students and might be handed in at the end of class.

ASSESSMENT

ASSESSMENT BREAKDOWN

Description %
Class participation 10
Tests 25
Exam on Units 1&2 30
Exam on Unit 3&4 35

Assessment criteria

Students' final marks will be based on the following activities and their respective percentages:
10% - Class participation
25% - Tests
30% - Exam on Units 1&2
35% - Exam on Units 3&4

For students that have to retake the course and can only sit the final exam, 100% of the mark for the course will be the mark they obtain on the final exam which covers all the course material. For the remaining students, students' marks for the different course components are required to obtain the final mark for the course.

Students that earn below a 5 on the final average will have to resit on an extraordinary exam on all units of the course, with a weight of 65%. The rest will be the continuous evaluation with the same weights than in the ordinary sitting (10% class participation and 25% tests).

For students to be able to assess their own learning and progress, they will receive feedback from faculty throughout the course. This feedback will be given in different ways depending on the evaluation activity (corrected tests and exams and feedback in the participatory sessions).

According to ESADE internal regulations for the Law School students must attend at least 80% of the sessions to seat in the first attempt exam, minum attendance to have the right to do the resit exam is 50%

Bibliography

Short bibliography:

Newbold, P., Carlson, W.L. & Thorne, B. (2013). Estadística para administración y economía. Ed. Pearson - Prentice Hall

This book may be considered the course textbook. Throughout the course, reference will be made to different chapters in this text both with regard to theoretical issues and to complete the assignments.

Timetable and sections

Group Teacher Department
Year 3 Jordi Montserrat Adell Operaciones, Innovación y Data Sciences

Timetable Year 3

From 2022/9/7 to 2022/10/5:
Each Friday from 8:30 to 10:30. (Except: 2022/9/16, 2022/9/23 and 2022/9/30)
Each Wednesday from 8:00 to 10:30.

From 2022/9/9 to 2022/9/19:
Each Monday from 15:15 to 17:15. (Except: 2022/9/12)
Each Friday from 11:00 to 13:00. (Except: 2022/9/16)

From 2022/9/30 to 2022/10/28:
Each Thursday from 17:00 to 18:30. (Except: 2022/10/6, 2022/10/20 and 2022/10/27)
Each Friday from 8:30 to 10:30.

From 2022/10/19 to 2022/11/16:
Each Wednesday from 8:00 to 10:30.
Each Friday from 18:00 to 20:30. (Except: 2022/10/21, 2022/11/4 and 2022/11/11)

From 2022/11/3 to 2022/11/23:
Each Friday from 8:30 to 10:30. (Except: 2022/11/4)
Each Wednesday from 9:00 to 10:30. (Except: 2022/11/9 and 2022/11/16)
Each Thursday from 17:00 to 19:00. (Except: 2022/11/10 and 2022/11/17)

Friday2022/11/25:
From 16:45 to 19:00.
From 8:00 to 10:15.
From 10:15 to 10:45.

Thursday 2023/2/9 from 14:45 to 18:00.