Registry
Module Specifications
Current Academic Year 2012 - 2013
Please note that this information is subject to change.
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| Description | |||||||||||||||||||||||||||||||||||||||||||||
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This module aims to provide students with a grounding in quantitative and statistical methods to enable information assessment and analysis of relevant data. This, in order to inform better business decisions. This will include reviewing knowledge of how to properly present and describe information, of how to use sample information to draw conclusions about target populations, to obtain reliable forecasts, and to improve processes. Topics covered will include probability theory, relevant special statistical distributions, theory of statistical estimation, statistical testing for one , two, many samples, decision making under risk and uncertainty, and linear programming principles and examples. | |||||||||||||||||||||||||||||||||||||||||||||
| Learning Outcomes | |||||||||||||||||||||||||||||||||||||||||||||
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1. Calculate simple probabilities using probability theory. 2. Analyse decision making under risk and uncertainty 3. Identify and apply appropriate special distributions for use in a variety of novel scenarios. 4. Construct the basic statistical point and interval estimates. 5. Explain the importance of the Central Limit Theorem in the construction of statistical estimates 6. Test statistical hypotheses concerning means, proportions and variances for one, two or multiple samples 7. Apply correlation and regression analysis techniques to two variable samples 8. Develop forecasts using basic time-series analysis methods 9. Apply basic Linear Programming principles | |||||||||||||||||||||||||||||||||||||||||||||
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 | |||||||||||||||||||||||||||||||||||||||||||||
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Review Basic Probability. Axioms, additive, multiplicative rules, marginal, conditional , joint probabilities, Bayes Rule. Random variables. Expectation, variances. Decision-making under uncertainty and risk. Profit, Loss, Maximin and alternative strategies, value of information, risk assessment and sensitivity. Discrete, continuous distributions. Binomial, Poisson, Normal and derived sampling distributions. Point and Confidence Interval Estimation. Means and proportions. Statistical Hypotheses in Business and Finance. Tests for means, proportions for one,two, many samples, tests for variances. Linear Regression/correlation. regression vs correlation objectives; outline of multiple linera regression. Time Series Analysis. Relaxation of regression assumptions, model forms and forecasts, including smoothing. Linear Programming. principles and examples in Business and Finance. | |||||||||||||||||||||||||||||||||||||||||||||
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| Indicative Reading List | |||||||||||||||||||||||||||||||||||||||||||||
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| Other Resources | |||||||||||||||||||||||||||||||||||||||||||||
| None | |||||||||||||||||||||||||||||||||||||||||||||
| Example exercise sheets will be provided and occasionally web resources may be indicated (optional) | |||||||||||||||||||||||||||||||||||||||||||||
| Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||||||||||
| AF | BA in Accounting & Finance | ||||||||||||||||||||||||||||||||||||||||||||
| Timetable this semester: Timetable for CA250 | |||||||||||||||||||||||||||||||||||||||||||||
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