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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

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 Programming20A (Hamilton), 20A (Online), 20B (Hamilton), 20G (Hamilton) & 20X (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 Sciences20A (Hamilton), 20A (Tauranga) & 20B (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 mathematical sci...
STATS111Statistics for Science20B (Hamilton) & 20B (Tauranga)
An introductory paper in statistics that uses Microsoft Excel. 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 Methods20A (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 Experience20A (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 Sciences20B (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 Analysis20A (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 Statistics20B (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 Mining20B (Hamilton) & 20B (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 Analysis20B (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 Statistics20A (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 Surveys20A (Hamilton)
This paper outlines the principles and practicalities of designing and analysing experiments and surveys, with emphasis on the design.
STATS326Computational Bayesian Statistics20B (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 Study20A (Hamilton) & 20B (Hamilton)
Students carry out an independent research project on an approved topic under staff supervision.
STATS391Undergraduate Research Project20A (Hamilton), 20B (Hamilton), 20D (Hamilton) & 20X (Hamilton)
Students carry out an independent research project on an approved topic under staff supervision.
STATS397Work-Integrated Learning Directed Study20X (Hamilton)
Students carry out an independent work-related project on an approved topic under staff supervision.

500 Level

Code Paper Title Occurrence / Location
STATS505Optimization20B (Hamilton)
This paper teaches students a toolbox of optimization techniques. It covers traditional approaches, such as linear programming and Newton's method, and heuristic methods such as simulated annealing and evolutionary algorithms.
STATS511Computational Statistical Methods20A (Hamilton)
Computationally intensive statistical methods will be considered. This could include Bayesian methods, methods for high-dimensional data, Big Data, etc. The choice of methods taught will be decided by the lecturer/paper convenor in charge.
STATS520Dissertation20X (Hamilton)
A directed investigation and report on an approved project or study topic.
STATS522Statistical Inference20B (Hamilton)
Statistical inference will be considered from both the classical and Bayesian perspectives.
STATS525Topics in Statistics20A (Hamilton)
This paper will discuss advanced topics in statistics. The exact topics covered could change subject to the preference and research expertise of the academic staff. Students preferences may also be taken into account.
STATS590Directed Study20B (Hamilton)
Students have the opportunity to pursue a topic of their own interest under the guidance of academic staff.
STATS591Dissertation20X (Hamilton)
A report on the findings of a theoretical or empirical investigation.
STATS592Dissertation20X (Hamilton)
A report on the findings of a theoretical or empirical investigation.
STATS593Statistics Thesis20X (Hamilton)
An externally examined piece of written work that reports on the findings of supervised research.
STATS594Statistics Thesis20X (Hamilton)
An externally examined piece of written work that reports on the findings of supervised research.

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, applied for a University of Waikato exchange programme, and who will be enrolled full-time in FCMS in the year of tenure.

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Faculty of Computing & Mathematical Sciences

Phone: 0800 924 528 ext: 4322 or +64 7 838 4322