Informatics 1 - Data and Analysis (U04326)

? Credit Points : 10 ? SCQF Level : 8 ? Acronym : INF-1-INF1-DA

An introduction to collecting, representing and interpreting data across the range of informatics. Students will learn the different perspectives from which data is used, the different terminology used when referring to them and a number of representation and manipulation methods. The course will present a small number of running, illustrative examples from the perspectives of hypothesis testing and query formation and answering.

Entry Requirements

? Pre-requisites : Prior attendance at the following courses is essential: Informatics 1 - Computation & Logic [U04323] Informatics 1 - Functional Programming [U04324]

? Co-requisites : Informatics 1 - Object-Oriented Programming [U04325] is a strict co-requisite.

Subject Areas

Home subject area

Informatics, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : 1st year

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 2 hour(s) per week for 10 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
13/01/2009	11:10	12:00	Lecture Theatre 3, Appleton Tower	Central

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	14:00	14:50	Central
Lecture	Thursday	11:10	12:00	Central

Summary of Intended Learning Outcomes

1.Demonstrate knowledge of the terminology and paradigms used in different areas of informatics for collecting, representing and interpreting data, by being able to apply them to sample problems.
2.Demonstrate understanding of different types of data (for example, structured/semistructured/unstructured, quantitative/qualitative). 3.Demonstrate proficiency of the entity/relationship model by being able to specify appropriate representations and queries for simple examples.
4.Show awareness of the importance of logic for the representation of data by being able to design simple logical representation of a given data set.
5.Present data in a variety of forms (textual, graphical, quantitative), across a range of data types.
6.Show awareness of the distinction between object data and meta-data, by being able to apply it to a number of applications across informatics (e.g., databases, corpora).
7.Demonstrate knowledge of the basic algorithms for interpreting and processing data, by being able to demonstrate how these algorithms work for simple data sets.