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Standard Score - Definition of the Standard Score (Z-Score)

Posted in Masters Programmes.


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This Masters programme aims to train postgraduate students in computational, mathematical and statistical methods to solve data-driven problems. The programme will create opportunities for students in the Computer Science, Statistics, Physics, Electrical Engineering or related fields to gain an interdisciplinary perspective on the emerging fields of Data Science. Students will register with their Home Institution but will attend coursework at Wits University in Johannesburg, Gauteng, in the first year.

On completion of the coursework modules, students will move back to their Home Institutions for their second year of study. Applicants require a minimum of 65 percent in their NQF level 8 qualification and fulfill any additional institutional application requirements of the institution through which they are applying, and must be co-approved by the Consortium. Applicants will also be required to complete a number of pre-requisite on-line courses and complete an assessment on these.

The Masters programme extends over eighteen months of full-time study. The programme comprises compulsory and elective modules. Cross-disciplinary data-driven projects are offered both within the University and from a wide range of industry partners. A candidate must undertake modules to the value of credits and must successfully complete the following courses to obtain a Master of Science by Coursework and Research Report in the field of e-Science.

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Graduates of the programme can find data-oriented roles within academic institutions, technology, healthcare companies and the finance sector. Data scientist positions involve a wide range of responsibilities; such as conducting exploratory data analysis, applying statistical methodologies, deriving business insights from data, partnering with company executives, product and engineering teams to solve problems, identify trends and opportunities, inform, influence, support, and execute product decisions and launches.

Students are advised to apply as early as possible due to competition for places. Posted in Masters Programmes This Masters programme aims to train postgraduate students in computational, mathematical and statistical methods to solve data-driven problems. Degree Information The Masters programme extends over eighteen months of full-time study.

Statistics coursework - GCSE Maths - Marked by lightresicur.tk

Graphical display of data. Discrete and continuous time processes with an emphasis on Markov, Gaussian and renewal processes.

Martingales and further limit theorems. Advanced topics in statistics and data analysis with emphasis on applications. Diagnostics and residuals in linear models, introduction to generalized linear models, graphical methods, additional topics such as random effects models, designed experiments, model selection, analysis of censored data, introduced as needed in the context of case studies.

Statistical theory and its applications at an advanced mathematical level. Topics include probability and distribution theory as it specifically pertains to the statistical analysis of data.


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Linear models and the geometry of data, least squares and the connection to conditional expectation. The basic concept of inference and the likelihood function. Material Covered: Statistical models and distributions; fundamentals of inference: estimation, hypothesis testing, and significance levels; likelihood functions and likelihood-based inference; prior distributions and Bayesian inference.

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About the Data Analytics Master's Degree

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