Module Specifications.
Current Academic Year 2024 - 2025
All Module information is indicative, and this portal is an interim interface pending the full upgrade of Coursebuilder and subsequent integration to the new DCU Student Information System (DCU Key).
As such, this is a point in time view of data which will be refreshed periodically. Some fields/data may not yet be available pending the completion of the full Coursebuilder upgrade and integration project. We will post status updates as they become available. Thank you for your patience and understanding.
Date posted: September 2024
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Coursework Only |
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Description Data Collection, Analysis and Reporting for Business | |||||||||||||||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Differentiate between different types of data sources / measurement types 2. Use descriptive statistical and data visualisation techniques to summarise a business data set 3. Explain the nature of sample error and calculate this error for a number of sample parameters 4. Choose the appropriate statistical techniques for testing a variety of statistical hypotheses 5. Interpret statistical output and effectively present the results of this output 6. Provide an overview of the role if statistics in an increasingly data driven business world | |||||||||||||||||||||||||||||||||||||||||||||||||
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
1. Introduction to Data AnalysisRole of Data Analysis in Business, Role of Technology in Data Analysis, Big Data and Data Analytics2. Data Collection / MeasurementData Collection, Questionnaire Design, Reliability and Validity, Data Cleaning and Missing Data, Measurement Types, Data Types,3. Descriptive StatisticsFrequency Distributions, Measures of Central Tendency, Measures of Dispersion, Crosstabs and Correlation, Presentation, Graphical Tools and Data Vsiualsation4. ProbabilityProbability Laws, Empirical and A Priori Probabilities, Probability Distributions; Binomial and Poisson Distributions, Normal Probability Distribution5. Statistical Estimation/Sampling ErrorSampling Error, Sampling Distributions, Central Limit Theorem, Confidence Intervals for means and proportions, Selecting appropriate sample size6. Hypothesis Testing / Statistical TestsWhat is a Statistical Test? General approach to statistical tests, Statistical Significance, Summary of Statistical Tests for Difference7. Regression / Forecasting / Predictive AnalyticsMultivariate Analysis, Linear Regression. Over view of Forecasting Techniques; Time Series, Predictive Analytics | |||||||||||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||||||||||||||