Registry
Module Specifications
Archived Version 2021 - 2022
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Description The main objective of this module is to develop the student's understanding and practical skills of basic statistical methods for Business Analytics. The lectures and tutorials will also develop student's ability to interpret the result provided a statistical model and to evaluate its performance. Students will be initially exposed to introductory statistical concepts and then to more advanced techniques. The course will be delivered with a practical approach and will cover the following topics: Basic statistical concepts, Statistical Analysis using R and SPSS, Linear Regression, and Logistic Regression. | |||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Understand the importance of statistical analysis in current business environment and how organisations can make use of it. 2. Understand the characteristics of different types of data and the differences between structured and unstructured data. 3. Identify and apply appropriate statistical techniques for gathering valuable business insights. 4. Interpret statistical output to drive business decisions. 5. Effectively present the output of statistical analyses. 6. Evaluate the fit-for-purpose of a statistical model and its analytical and predictive performance. 7. Implement statistical analysis and generate statistical reports. | |||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and
Learning Activities Statistical analysis for business purposes.Why is important to perform to statistical analysis? When and how do managers adopt it?Business Analysis Planning and MonitoringOrganise and coordinate the efforts of business analysts and stakeholders, and identify business analysis performance improvements.Elicitation and CollaborationStakeholders engagement and communication in the context of business analytics projects.Requirements Analysis and Design DefinitionOrganise, specify and model requirements and designs, validate and verify information, and identify solution options that meet business needs.Basic statistical conceptsA refresher of basic statistical concepts that will be useful in the rest of the course such as: data types, sampling, descriptive statistics, hypotheses testing, and confidence intervals.Statistical Analysis using R and SPSSR interface, import/export of data, vectors, variables attributes, basic data manipulation, and basic commands for univariate and multivariate analysis.Linear RegressionUnivariate and multivariate analysis, OLS estimation, model evaluation, heteroscedasticity, multicollinearity, and other factors that might bias the results.Logistic RegressionLogit and Probit models, basic assumptions, applicability, and maximum likelihood estimation. | |||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources 27515, Software, 0, R and R Studio, | |||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||
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