Statistics Joint Major (SAJ1)

If you are interested in doing an Internship as part of Stage 4, you must indicate your interest now (in Stage 3).
See full details www.ucd.ie/science/careers/internships/students/

Curricular information is subject to change

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The 21st Century has given us the Data Society. All aspects of society are now producing large quantities of data and all areas of society from corporations, to government, to sport, to entertainment are increasingly making data driven decisions. Statistics is the science of data and the aim of our programmes are to equip our graduates with the necessary statistics and data analytics skills to make an impact and excel in the modern data oriented society. Our graduates are already in high demand with a 100% employment level in the year following graduation. Indeed the demand has been growing substantially over the last 5 years and we are contacted continually by employers seeking qualified statistics graduates. We offer the only complete undergraduate and postgraduate programme in Statistics on the island of Ireland and we are recognised internationally as a centre of excellence in Statistics. This programme is aimed at students who wish to gain a deep understanding of the concepts of modern statistics and a mastery of the associated skills and technologies. Our students will become autonomous inquisitive learners capable of formulating and creatively solving relevant problems in the language of statistics. Our graduates will be in demand by employers and academic research institutes for their ability to use the tools they have learned to explain, describe and predict. We aim to provide a teaching and learning environment that develops confidence and independence through a wide variety of interactive formats, both inside and outside the classroom, including lectures, tutorials, webwork, blackboard and computer assisted labs.



 


1 - Demonstrate an indepth understanding of statistics
2 - Use the language of logic to reason correctly and make deductions
3 - Approach problems in an analytical, precise and rigorous way
4 - Explore and manipulate abstract concepts
5 - Apply statistical reasoning and techniques to formulate and solve problems
6 - Model real world problems in a statistical framework
7 - Confidently analyze and draw information from large quantities of data
8 - Analyze and interpret data, find patterns and draw conclusions
9 - Use the power of modern technology to augment statistical problem solving
10 - Work independently and as part of a team
11 - Carry out research into a specific topic, including a survey and synthesis of the known literature
12 - Give oral presentations of technical statistical material at a level appropriate for the audience
13 - Prepare a written report on technical statistical content in clear and precise language
Approved Additional Standards for Continuation in undergraduate degree programmes in Science (all majors):

Students who return failing grades in a semester amounting to 15 credits, or more, will be identified under the UCD Continuation and Readmission Policy. Students whose rate of progression and performance over two academic sessions (2 years) is deemed unacceptable will be referred to the Academic Council Committee on Student Conduct and Capacity for exclusion from the programme.

As Stages 3 and 4 have the most dynamic components of the programme, and the material studied previously may no longer be relevant, a student who has been away from the programme for a significant period should be required to register again to Stage 3. The upper limit for completion of Stages 3 and 4 should be six years, if they choose to do 120 credits with 20 in each year.
Stage 3

Students take 5 core modules. Students take 25 credits in each of their two majors. Additional modules may be taken from the Option list below or alternatively, students can select 10 credits from elective modules to complete Stage 3.
If you are interested in doing an Internship as part of Stage 4, you must indicate your interest now (in Stage 3). See full details www.ucd.ie/science/careers/internships/students/

Stage 4

Students take at least 30 credits of modules in Statistics. Students take 4 core modules and 2 option modules.

Module ID Module Title Trimester Credits
Stage 3 Core Modules
     
STAT30010 Time Series Autumn

5

STAT30090 Models - Stochastic Models Autumn

5

STAT40110 Design of Experiments Autumn

5

STAT30250 Advanced Predictive Analytics Spring

5

STAT30270 Statistical Machine Learning Spring

5

Stage 3 Core Modules
     
Stage 3 Options - A)MIN0OF:
If not previously taken in Stage 2, students must take MATH20300 in Stage 3.
     
MATH20300 Linear Algebra 2 for the Mathematical Sciences Autumn

5

Stage 3 Options - A)MIN0OF:
If not previously taken in Stage 2, students must take MATH20300 in Stage 3.
     
Stage 3 Options - B)MIN0OF:
Students may take additional Option modules from the list below to complete Stage 3.
     
ACM30190 Dynamical Systems Autumn

5

MATH20130 Fundamentals of Actuarial and Financial Mathematics I Autumn

5

MATH30090 Metric Spaces Autumn

5

STAT40620 Data Programming with R Autumn

5

ACM30100 Maths of machine Learning Spring

5

Stage 3 Options - B)MIN0OF:
Students may take additional Option modules from the list below to complete Stage 3.
     
Stage 4 Core Modules
     
STAT30080 Models - Survival Models Autumn

5

STAT40400 Monte Carlo Inference Autumn

5

STAT40150 Multivariate Analysis Spring

5

STAT40510 Applied Statistical Modelling Spring

5

Stage 4 Core Modules
     
Stage 4 Options - MIN 2 OF:
Students should select 2 modules from the list below.
     
MATH30030 Advanced Linear Algebra Autumn

5

SCI30080 Professional Placement-Science Autumn

5

STAT40020 Actuarial Statistics I Autumn

5

STAT40110 Design of Experiments Autumn

5

STAT40620 Data Programming with R Autumn

5

STAT40800 Data Prog with Python (online) Autumn

5

STAT40880 Research Project I Autumn and Spring (separate)

5

MATH20180 Foundations for Financial Mathematics Spring

5

STAT40070 Actuarial Statistics II Spring

5

STAT40120 Categorical Data Analysis Spring

5

STAT40970 Machine Learning & AI (online) Spring

5

STAT41010 Stat Network Analysis Spring

5


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