## STATISTICS

### Course

Code: 965

Degree: Bachelor's in Agro-Food and Agro-Environmental Engineering

School of Engineering of Orihuela

Year: Year 1 of Bachelor's in Agro-Food and Agro-Environmental Engineering

Semester: Spring

Type: Core

Language: Spanish

ECTS credits: 6 Lecture: 3 Laboratory: 3 | Hours: 150 Directed: 60 Shared: 30 Autonomous: 60 |

Subject matter: Mathematics

Module: Core

Department: Statistics, Mathematics and Informatics

Course instructors are responsible for the course content descriptions in English.

### Description

### Faculty

Name | Coordinator | Lecture | Laboratory |
---|---|---|---|

RAMON ESCOLANO, NURIA | ■ | ■ | ■ |

### Professional interest

### Competencies and learning outcomes

#### General competencies

- Capacity to use tools for resolving problems within the field.
- Capacity for evaluating, optimizing, and comparing criteria in decision making.
- Capacity to write, represent, analyze, and interpret technical documentation and data relevant to engineering and architecture.
- Ability to communicate and convey knowledge in expert and non-expert environments.
- Capacity to update knowledge independently and with a constant willingness to do so.
- Knowledge of basic, scientific, and technological matters that enable continuous learning, as well as a capacity to adapt to new situations and changing environments.
- Ability to solve problems with creativity, initiative, methodology, and critical thinking.
- Leadership, communication, and transmission of knowledge, skills, and abilities in social fields of action.
- Ability to search for and use the rules and regulations relative to the field of action.
- Ability to develop activities, assuming a social, ethical, and environmental commitment in tune with the reality of the human and natural environments.
- Capacity to work on multidisciplinary and multicultural teams.

#### Specific competencies

- Skills for resolving mathematical problems that arise in engineering. Aptitude for applying knowledge towards linear algebra, geometry, differential geometry, differential and integral calculus, differential equations and partial derivatives, numerical and numerical algorithmic methods, statistics, and optimization.

#### Objectives (Learning outcomes)

- 01Differentiate between descriptive statistics and Statistical Inference and determine the usefulness of both disciplines in the Agrifood and Agroambiental area
- 02Analyze and interpret data banks through graphical and numerical descriptors
- 03Students will be able to apply the basic concepts of probability calculus to measure the certainty (or uncertainty) of certain events occurring in the Agrifood and Agroambiental area
- 04Identify models of probability distributions in Agrifood and Agroambiental field problems and be able to perform probability calculations on these models
- 05Knowing the basic principles of Inferenca Statistics (sample, parameter, confidence intervals, hypothesis testing , etc. )
- 06Inference to make decisions on parameters of one or more populations in the Agrifood and Agroambiental area
- 07Formulate and solve linear programming problems that allow simple optimization of resources in the Agrifood and Agroambiental area
- 08Skillfully handle software which will allow the objectives described in the subject

### Contents

#### Teaching units

#### Association between objectives and units

Objective/Unit | U1 | U2 | U3 | U4 | U5 | U6 |
---|---|---|---|---|---|---|

01 | ||||||

02 | ||||||

03 | ||||||

04 | ||||||

05 | ||||||

06 | ||||||

07 | ||||||

08 |

#### Schedule

Week | Teaching units | Directed hours | Shared hours | Autonomous hours | Total hours |
---|---|---|---|---|---|

1 | U1 | 4 | 1 | 2 | 7 |

2 | U1,U2 | 4 | 1 | 2 | 7 |

3 | U1,U2 | 4 | 2 | 4 | 10 |

4 | U2 | 4 | 2 | 4 | 10 |

5 | U2 | 4 | 2 | 4 | 10 |

6 | U2 | 4 | 2 | 4 | 10 |

7 | U2,U3 | 4 | 2 | 4 | 10 |

8 | U3 | 4 | 2 | 4 | 10 |

9 | U3 | 4 | 2 | 4 | 10 |

10 | U3 | 4 | 2 | 4 | 10 |

11 | U3 | 4 | 2 | 4 | 10 |

12 | U3,U4 | 4 | 2 | 4 | 10 |

13 | U4 | 4 | 2 | 4 | 10 |

14 | U4 | 4 | 2 | 4 | 10 |

15 | U1,U2,U3,U4 | 4 | 4 | 8 | 16 |

#### Basic bibliography

- Ferrandis Ballester, Eduardo / Borrás Rocher, Fernando / Segura Heras, José Vicente. "Cuadernos de Bioestadística". Alicante Editorial Club Universitario 1996-1997.
- Borrás Rocher, Fernando. "Cuadernos de bioestadística". Alicante Universidad de Alicante, Secretariado de Publicaciones 1994.
- Moore, David S. Comas, Jordi trad. "Estadística aplicada básica". Barcelona Antoni Bosch 2005.
- Pérez López, César 1955-. "Estadística aplicada a través de excel". Madrid Prentice Hall D.L. 2002.
- Mendenhall,William. Sincich, Terry. "Probabilidad y estadística para ingeniería y ciencias". México [etc.] Prentice-Hall Hispanoamericana 1997.
- Mathur, Kamlesh Ph. D. Solow, Daniel. "Investigación de las operaciones el arte de la toma de decisiones". México [etc.] Prentice Hall cop. 1996.
- Bazaraa, M. S. Jarvis, John J. / Sherali, Hanif D. 1952-. "Programación lineal y flujo en redes". Mexico Limusa 1998.

#### Complementary bibliography

- Walpole, Ronald E. Myers, Raymond H. aut. / Myers, Sharon L. aut. "Probabilidad y estadística para ingenieros". México Prentice Hall 1999.
- Montgomery, Douglas C. Runger, George C. "Probabilidad y estadística aplicadas a la ingeniería ". México McGraw-Hill 1996.
- Grimmett, Geoffrey. Stirzaker, David. "One thousand exeercises in probability". Oxford Oxford University Press 2001.

#### Links

#### Software

- Microsoft Office 2010

### Methodology and grading

#### Methodology

**Case studies:**Learning through the analysis of actual or simulated cases in order to interpret and resolve them by employing various alternative solution procedures.**Cooperative learning:**Develop active learning through cooperative working strategies among students and promote shared responsibility to reach group goals.**Lecture:**Pass on knowledge and activate cognitive processes in students, encouraging their participation.**Problem-based learning:**Develop active learning strategies through problem solving that promote thinking, experimentation, and decision making in the student.**Project-based learning:**Realization of a project to solve a problem, applying acquired learning and promoting abilities related to planning, design, performing activities, and reaching conclusions.**Solving exercises and problems:**Exercise, test, and apply previous knowledge through routine repetition.

#### Grading

June The Final mark will be the sum of the score obtained in the part of continuous evaluation and Final exam: follows each of the parties;

1) continuous assessment: 25% of the global note.

a) Test exam(10% of the global note) . The examination will have multiple questions with four answer choices. The wrong answers penalize a well at a rate of four bad subtraction. (The test as well as the date of the same (April/May) will be specified with at least one month in advance .

b) A Final practice (10%). The student body must deliver at the end of may a practice that can be made individually or by couples.

c) assistance and participation in class (5% of the global note)

2) theoretical and practical exam: 75% of the global note. Exam of problems develop with questions about concepts and theoretical and practical methods of the subject.

To pass the subject you must obtain at least 3.5 (out of 7.5) in the FINAL EXAMSeptember and december continuous assessment note is not saved for the September and December. The exam will be the 100% of the final grade .

#### Correction criteria

The note of each section will be specified in the exam

#### Additional requirements

The allowed forms and a calculator must be taken to the exam