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Data Analytics

Enhance productivity and help make more informed decisions, while using your Computer Science and Statistical analysis skills, through Data Analytics.

Data Analytics

Data Analytics is the combination of Computer Science and Statistics. With the massive amount of data that is collected today, we need to have the computing skills to manipulate and extract relevant data prior to performing statistical analyses, which enables us to make informed decisions in a world where variability is everywhere.

Data Analytics provides you with the skills and techniques for manipulating and administering large databases to extract useful information for statistical analyses.

As a Data Analytics graduate from the University of Waikato you will have the ability to use statistical techniques in a number of industries, from healthcare to travel to energy management.  Your skills will help companies to make better decisions as well as to verify and disprove existing theories.

Computing facilities at Waikato

The computing facilities at the University of Waikato are among the best in New Zealand.  Our senior computing laboratory has a network of PCs running Linux and Windows.  All students will have 24 hour access to labs equipped with the latest versions of specialist statistical software packages, including Minitab, R, Mathematica, Matlab and C++.

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Key information

Study Location:Hamilton
Faculty:

Career opportunities

  • Biometrics
  • Business Analyst
  • Data Analyst
  • Government Statistician
  • Industrial Statistician
  • Insurance and Finance
  • Market Researcher
  • Medical Statistician
  • Operational Researcher

Prescriptions for the GradCert(DataA) and GradDip(DataA)

A Graduate Certificate and Graduate Diploma are available to graduates who have not included Data Analytics at an advanced level in their first degree.

For further details, contact the Faculty of Computing and Mathematical Sciences Office.

100 Level

Code Paper Title Occurrence / Location
COMPX101Introduction to Computer Science19A (Hamilton), 19A (Online), 19B (Hamilton) & 19C (Zhejiang University City College, Hangzhou China)
This paper introduces computer programming in C# - the exciting challenge of creating software and designing artificial worlds within the computer. It also covers concepts such as the internals of the home computer, the history and future of computers, cyber security, computer gaming, databases, mobile computing and current researc...
CSMAX170Foundations in Computing and Mathematical Sciences19A (Hamilton) & 19B (Hamilton)
The objective of this paper is to provide students with the academic foundations for computing and mathematical sciences. The paper will cover the following areas: - Effective academic reasoning and communication - Information literacy and research skills - Academic integrity - Techniques and tools in the computing and mathematica...
STATS111Statistics for Science19B (Hamilton) & 19B (Tauranga)
This paper provides a first course in statistics for students in the Faculty of Science and Engineering. Microsoft Excel is used throughout. Topics include the collection and presentation of data, basic principles of experimental design, hypothesis testing, regression and the analysis of categorical data.
STATS121Introduction to Statistical Methods19A (Hamilton)
An introduction to statistical data collection and analysis. Topics include general principles for statistical problem solving; some practical examples of statistical inference; and the study of relationships between variables using regression analysis.

200 Level

Code Paper Title Occurrence / Location
COMPX223Database Practice and Experience19A (Hamilton)
This paper approaches the subject of databases from a practical perspective - how do I create a database and how do I retrieve/update data. Both aspects are heavily addressed in this paper. Database creation and querying, using SQL, will be introduced in lectures as you will master practical skills associated with a commercial Data...
CSMAX270Cultural Perspectives for Computing and Mathematical Sciences19B (Hamilton)
The paper provides students with an understanding of scientific and culture-specific perspectives on computing and mathematical science issues and the ability to apply these in diverse contexts.
STATS221Statistical Data Analysis19A (Hamilton)
This paper introduces students to the R programming language which is used to investigate a collection of real data sets. Analysis of variance, multiple regression, non parametric methods and time series are covered.
STATS226Bayesian Statistics19B (Hamilton)
This paper introduces statistical methods from a Bayesian perspective, which gives a coherent approach to the problem of revising beliefs given relevant data. It is particularly relevant for data analytics, statistics, mathematics and computer science.

300 Level

Code Paper Title Occurrence / Location
COMPX305Practical Data Mining19B (Hamilton) & 19B (Tauranga)
This paper introduces students to techniques for automatically finding and exploiting patterns in datasets, covering basic techniques applied in data analytics, data mining, machine learning, and big data. The well-known, locally-made Weka software will be used as the software environment for this paper.
STATS321Advanced Data Analysis19B (Hamilton)
This paper covers the use of statistical packages for data analysis and modelling. The emphasis is on observational rather than experimental data. The topics covered are regression modelling and its generalisations, and multivariate analysis.
STATS322Probability and Mathematical Statistics19A (Hamilton)
This paper introduces students to probability theory and the mathematical theory of statistics. It covers formally the theoretical foundations of probability, random variables, likelihood and estimation, statistics, and statistical inference.
STATS323Design and Analysis of Experiments and Surveys19A (Hamilton)
This paper outlines the principles and practicalities of designing and analysing experiments and surveys, with emphasis on the design.
STATS326Computational Bayesian Statistics19B (Hamilton)
Bayesian approach has the potential to model any complex real life problem. In practice, Bayesian methods are implemented using various computational algorithms. This paper introduces the basics of some of the most widely used computational methods, viz the ABC method and the MCMC methods.
STATS390Directed Study19A (Hamilton) & 19B (Hamilton)
Students carry out an independent research project on an approved topic under staff supervision.
STATS391Undergraduate Research Project19A (Hamilton), 19B (Hamilton), 19C (Hamilton) & 19Y (Hamilton)
Students carry out an independent research project on an approved topic under staff supervision.

500 Level

Code Paper Title Occurrence / Location
STATS501Quantitative Methods for Security and Crime Science19A (Hamilton)
This paper considers quantitative techniques that can be used to analyse crime data.
STATS502Advanced Quantitative Methods for Security and Crime Science19B (Hamilton)
This paper considers advanced quantitative techniques that can be used to identify and forecast crime event patterns.
STATS521Computational Statistics19A (Hamilton)
This paper covers maximum likelihood estimation, and the fitting of advanced regression models including non-linear models, mixture models and their generalisations. It will take a practical approach stressing the use of R packages and WinBugs or OpenBugs Bayesian software.
STATS522Statistical Inference19B (Hamilton)
Statistical inference will be considered from both the classical and Bayesian perspectives.
STATS525Topics in Statistics19C (Hamilton)
No description available.
STATS590Directed Study19C (Hamilton)
Students have the opportunity to pursue a topic of their own interest under the guidance of academic staff.
STATS591Dissertation19C (Hamilton)
A report on the findings of a theoretical or empirical investigation.
STATS592Dissertation19C (Hamilton)
A report on the findings of a theoretical or empirical investigation.
STATS593Statistics Thesis19C (Hamilton)
An externally examined piece of written work that reports on the findings of supervised research.
STATS594Statistics Thesis19C (Hamilton)
An externally examined piece of written work that reports on the findings of supervised research.

Claudia Wu University of Waikato Computer Science graduate Claudia Wu spends her days making sense of numbers, to ensure ANZ are lending responsibly.

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New to Waikato? The International Excellence Scholarship is worth up to $10,000.

CMS International Exchange Scholarship  Closed

For students who have completed at least one year of study in the Faculty of Computing & Mathematical Sciences (FCMS), applied for a University of Waikato exchange programme, and who will be enrolled full-time in FCMS in the year of tenure.

Looking for more scholarships?

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Documents


Contacts

Faculty of Computing & Mathematical Sciences

Phone: 0800 924 528 ext: 4322 or +64 7 838 4322
Email: cms@waikato.ac.nz
Website: cms.waikato.ac.nz
Facebook: facebook.com/WaikatoFCMS