Public University of Navarre



CastellanoEuskara | Academic year: 2015/2016 | Previous academic years:  2019/2020  |  2018/2019  |  2017/2018  |  2016/2017 
Bachelor's degree in Innovation on Food Processes and Products at the Universidad Pública de Navarra
Course code: 502203 Subject title: STATISTICS
Credits: 6 Type of subject: Basic Year: 1 Period: 2º S
Department: Statistics and Operative Research
Lecturers
FERNANDEZ MILITINO, ANA

Partes de este texto:

 

Module/Subject matter

Statistics

Up

Descriptors

Descriptive statistics, probability, statistical inference, statistical models

Up

General proficiencies

CT6: Ability of self-learning

CT7: Ability of solving new problems and decision-making capability

Up

Specific proficiencies

CG2: Adequate knowledge of the physical problems, technologies, equipment, and water and energy supply systems, the limits imposed by budgetary factors and building regulations, the relationships between installations and/or buildings with farms, agro-food industries and spaces related to gardening and landscaping with their social and environmental surroundings, as well as the need to relate those surroundings from that environment with human needs and environmental protection.
CE1: Ability to solve mathematical problems that may arise in engineering. Aptitude for applying knowledge towards: linear algebra, geometry, differential geometry, differential and integral calculus, differential equations and partial derivatives, numerical methods and numerical algorithmic methods, statistics, and optimization.

Up

Learning outcomes

To carry out statistical analysis of data to summarize a report in an efficient and accurate way

To know a statistical package for working with data bases and simulation of random experiments

To Model problems of random properties using probabilities, conditional probabilities and independent events

To recognize the main discrete and continuous probability distributions, and the main rules of probabilities

To know basic statistical models used in design of experiments,  assessment   and environmental problems

Up

Methodology

Methodology - Activity

Attendance

 Self-study

A-1 Theoretical clases

44

 

A-2 Computer Labs

14

 

A-3 Debates, group work, etc

1

 

A-4 Monitoring proofs

8

 

A-5 Lecture

 

 

A-6 Self-study

 

 75

A-7 Exam, evalutaion proofs

4

 

A-8 Tutorial

4

 

...

 

 

Total

75

75

Up

Relationship between formative activities and proficiencies

Proficiency

Activities

CT6-CT7

A-1, A-2, A-3

CG8

A-1, A-2, A-4, A-6, A-7

CE1

A-1, A-2, A-3, A-4, A-6,A-7

 

Up

Languages

Spanish, English and Euskera

Up

Evaluation

 

 

 

 Learning Outcomes

Competences

Evaluation Activity

Weight

 Second chance

1.       To carry out statistical analysis of data to summarize a report in an efficient and accurate way

2.       To know a statistical package for working with data bases and simulation of random experiments

3.       To Model problems of random properties using probabilities, conditional probabilities and independent events

4.       To recognize the main discrete and continuous probability distributions, and the main rules of probabilities

5.      To know basic statistical models used in design of experiments,  assessment   and environmental problems

CT6

CT7

CG2

CE1

Theoretical and computer evaluation proof

At least, 5 points of 10 will be necessary for passing the exam

50%

Yes

1.- To carry out statistical analysis of data to summarize a report in an efficient and accurate  

CT6

CT7

CG2

CE1

Individual Monitoring Proofs

40%

No

5.- To know basic statistical models used in design of experiments,  assessment   and environmental problems

 

 CT6

CT7

CG2

CE1

Active Participation

10%

No

 

 

Up

Contents

Descriptive Statistics

 

  • Exploring Data

 

Probabilidad

  • Sampling space and events
  • Condicional probability, the law of total probability, Bayes theorem and independent events
  • Probability density function and cummulative density function. Median, mode, percentiles and moments
  • Discrete random variables: Uniform, binomial and Poisson. Continuos random variables: Uniform, exponential, gamma and normal
  • Joint, marginal and conditional distributions of discrete and continuous random variables

 

Inferencial Statistics

 

  • Itroduction to sampling distributions. Parameters and estimators.
  • Chi-square distribution and t-Student
  • Sampling distribution of the mean, of the difference of means, proportion, difference of proportions
  • F Distribution
  • Sampling distribution of the variance and of the ratio of variances
  • Point Estimation and properties. Mean squared error
  • Confidence intervals introduction. Confidence intervals of means, difference of means, proportions, difference of proportions, variances and ratio of variances
  • Hypothesis testing. Type I and type II errors. P-value and power of a test.  Hyphotesis testing for means, proportions and variances

 Statistical Modelling

 

  • Analysis of variance and Regression

 

 

Up

Agenda

 

Week 1: Descriptive Statistics

Weeks 2-5: Probability 

Weeks 6-14: Inferencial Statistics

Week 15: Analysis of variance and Regression

 

 

Up

Bibliography

Acceda a la bibliografía que su profesor ha solicitado a la Biblioteca.


Basic

 

Ugarte, M. D., Militino, A. F., Arnholt, A. T. (2008). Probability and Statistics with R.  CRC Press/Chapman and Hall.

 

Supplementary

 

Devore, J. (2005) Applied statistics for engineers and scientists. Thomson

Montgomery, D.C. (2002). Probabilidad y Estadística aplicadas a la ingeniería. Limusa-Wiley

 

 

Up

Location

UPNA aulario

Up