Teaching plan for the course unit

 

 

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General information

 

Course unit name: Programming and Applications

Course unit code: 568957

Academic year: 2018-2019

Coordinator: Luis Ortiz Gracia

Department: Department of Econometrics, Statistics and Applied Economics

Credits: 2,5

Single program: S

 

 

Estimated learning time

Total number of hours 62,5

 

Face-to-face and/or online activities

22,5

 

-  Lecture with practical component

Face-to-face

 

13,5

 

-  Practical exercises

Face-to-face

 

9

Supervised project

20

Independent learning

20

 

 

Competences to be gained during study

 

— Capacity to carry out actuarial and financial calculations using specific software.

 

 

 

 

Learning objectives

 

Referring to knowledge

— Identify the basic structure of an SAS program. Know the main types of files that the program works with.

— Learn some of the advanced statistical procedures.

 

Referring to abilities, skills

— Apply statistical models and techniques using commercial and open-access statistical software.

— Identify the advantages and disadvantages of the main software packages.

 

 

Teaching blocks

 

1. Introduction to SAS

1.1. Introduction to the SAS environment

1.2. Structure of SAS programs: DATA and PROC

1.3. SAS datasets and libraries

1.4. Import and export of data

2. Programming in the DATA phase

2.1. Specific treatment of variables; Functions

2.2. Handling of observations

2.3. Diagnosis and fixing of errors

3. Combining SAS datasets

3.1. Fusion of sets of SAS data

3.2. Updating of sets of SAS data

4. Basic procedures in SAS

4.1. Introduction to the PROC phase

4.2. Statistical and graphical procedures

5. Matrix language in SAS

5.1. IML procedure and applications

5.2. Matrices and IML functions

5.3. Programming with IML

6. Case studies with SAS

6.1. PROC GLM

6.2. Logit, Poisson and negative binomial models

6.3. Multinomial generalised logit model

6.4. Conditional logit model

7. Advanced data analysis with Excel

7.1. Advanced filters

7.2. Dynamic tables

7.3. Macros in Visual Basic

7.4. Graphics

 

 

Teaching methods and general organization

 

The teaching method is based on two types of activities that are carried out in computer rooms:

a) Theory classes, in which the basic concepts of each of the units are presented.

b) Practical classes, in which the aim is for each student to learn to analyse and solve the exercises that are set, in accordance with the knowledge gained in the theoretical classes. Although these practical classes are not directed, the teaching staff provide support and help to clarify any aspects that were not necessarily explained in the theory classes.

Students should also work on additional practical exercises outside of class, to gain enough confidence to work independently. The practical classes are used as a means of assessment.

 

 

Official assessment of learning outcomes

 

Students complete two continuous assessment tests, worth 50% of the final grade each. The first mid-semester exam takes place once the first half of the teaching blocks has been taught, and the second, once all blocks have been taught. The final grade for continuous assessment is the mean between the two tests.

 

Examination-based assessment

— Final examination on the date established by the Coordination Committee. This is worth 100% of the grade.

— Students who do not pass the subject have the right to repeat assessment.

 

 

Reading and study resources

Consulteu la disponibilitat a CERCABIB

Book

Cody, R.(2007) Learning SAS by Example: A Programmer’s Guide. Cary NC:SAS, Institute inc.

Catāleg UB  Enllaç

Delwiche, Lora D. y Sugan J. Salughter (2008). The Little SAS book: A primer, 4 ed Cary NC:SAS, Institute inc.

Catāleg UB  Enllaç

Etheridge, D. (2010) Microsoft Excel Data Analysis. Ed.Wiley

Catāleg UB  Enllaç

Kleinman, K. i Horton, N.J. (2010) Using SAS for Data Management, Statistical Analysis, and Graphics. Champan and Hall. London, New York.

Catāleg UB  Enllaç

Kleinman, K. i Horton, N.J. (2010) SAS and R: Data Management, Statistical Analysis and Graphics. Champan and Hall. London, New York.

Catāleg UB  Enllaç

Littell, R.C., et al. (2006) SAS for Mixed Models. Cary NC:SAS, Institute inc.

Catāleg UB  Enllaç