Registry
Module Specifications
Archived Version 2022 - 2023
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Description This course introduces the use of the R environment for the implementation of data management, data exploration, basic data analysis and automation of procedures. | |||||||||||||||||||||||||||||||||||||
Learning Outcomes 1. Analyse a problem and write its solution in the R programming language 2. Read and modify R programming code 3. Demonstrate an understanding of programming constructs and concepts in the R programming language 4. Write programmes using advanced data types (Vectors, Lists, DataFrames) in the R programming language 5. Demonstrate the ability to import, clean and manipulate datasets in R 6. Apply basic data analysis and visualisation to a given dataset in R | |||||||||||||||||||||||||||||||||||||
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 Introductory TopicsIntroduction to R Programming. R development environment. R Console, Rstudio . Problem solving techniques: Problem analysis and problem solving. Algorithm design. Control structures - sequencing, selection and iteration. Introduction to the Basic Data Types of R: Numerics, Character , Logicals, Arithmetic calculations. Operator precedence. Mathematical and statistical functions. Control structures - If and if/else; While loops; For loops Arrays: Advanced data types: Lists, Dataframes, Matrices, Vectors, Factors and their operations. Modularity: Use of functions Passing arguments between functions. Data analysis: Importing data and reading data in R. Statistical Graphics, gplot | |||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||
Programme or List of Programmes | |||||||||||||||||||||||||||||||||||||
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