3 minute read

statistics

Next Article
NOTES

NOTES

Statistics (group 6 subject) CAO Code: MH101 | CAO Points 2021: 338

Minimum entry requirements: recommended minimum O3/H7 Leaving Certificate Mathematics. For full details about entry requirements see p. 42.

> Statistics deals with the collection, analysis and interpretation of data. > You will learn how to use statistical models and visualisation methods to unlock valuable information and hidden patterns in large volumes of data. > A degree in Statistics will provide you with tools to address problems of critical importance to humans such as climate change, developing cancer drugs or managing traffic flows.

Why choose this subject? > We offer Statistics as a Double Major subject which can be combined with most other academic subjects in the Bachelor of Arts degree.

This flexibility means you can combine your interest in aspects of society with knowledge of the statistical tools needed to understand data from those fields. > Data recording is happening at unprecedented levels on local, national and global scales. The ability to transform data into usable knowledge is a highly sought-after and desirable skill in today’s workforce, be it in business, science, health or social sciences. This subject will strongly enhance your employability.

Course structure

1st year

BA Bachelor of Arts – Statistics Double Major or as a Minor

> In year 1 of the BA Double Major programme, Statistics is taken with two or three other subjects. One of these subjects must be Mathematical

Studies or Mathematics (Pure) 2nd year

> Statistics is taken with one of your first year subjects. This subject can be, but does not have to be, Mathematical Studies or

Mathematics (Pure) > Optional 10 credit Elective in 2nd year (see p. 13 for details)

Erasmus/Study Abroad option after 2nd year

3rd year

> Statistics can be taken as a Double Major or as a Minor subject.

The second subject can be, but does not have to be, Mathematical

Studies or Mathematics (Pure).

For MH101 subject groups table go to p. 45

Possible topics

1st year

> Introduction to Data Science 1 > Introduction to Data Science 2 > Data Analysis > Design and Analysis of Experiments > R for Statistics and Data Science > Nonparametric Statistics > Calculus > Linear Algebra > Probability > Data Visualisation > Generalized Linear Models > Time Series > Bayesian Data Analysis

2nd year Final year

Statistics (group 6 subject) (continued)

Options after graduation?

> Graduates of a degree in Statistics are highly data literate and because of this are very much sought-after by employers. Critical thinking, being analytically focused and being adaptable to varying work environments are among the strong skills and traits of Statistics graduates that are attractive to employers. Graduates have a wide range of career options open to them, including employment in the civil service, industry and business, scientific research, medical research, environmental research, financial services and actuarial roles.

Postgraduate study options at Maynooth currently include:

> MSc (by research) or PhD in Statistics

Contact us

Maynooth University Department of Mathematics and Statistics, Logic House  + 353 1 708 3914

 mathsstats@mu.ie  www.maynoothuniversity.ie/mathematics-and-statistics @MU_MathsStats “ I work as a modelling analyst for one of Ireland’s largest betting shop chains. I analyse the customers who play on the Casino, Bingo, Games and Poker channels. Using different statistical methods, I try to identify groups of customers who have similar playing habits so that the marketing teams can engage with these customers with offers that best suit them. I also try to predict which customers are going to be valuable and which customers are going to eventually stop playing. This allows the marketing teams to focus their efforts on engaging with the right kind of customer. Mathematics is crucial in my job. Every day I use at least one nugget of knowledge that

I learned from the Statistics courses I sat for my undergraduate degree in Maynooth."

deNise, GrAduAte

You might also like

Computer Science p. 58 Data Science p. 192 Quantitative Finance p. 130

This article is from: