# Module Overview

### Mathematical Laboratory

This module allows the learner to use the computer effectively for areas of other modules. It covers Microsoft Excel which is widely used in the workplace. It also uses various mathematical software such as R (a language for statistical computing and graphics) and Latex (a document preparation system for high-quality typesetting)

MATH 1809

##### ECTS Credits

10

*Curricular information is subject to change

Excel (10 weeks) To include: Entering and formatting text & numbers ; Adjusting column heights and row widths  and applying borders & shading ; Insert rows & columns: Select multiple rows & columns
Understanding relative and absolute referencing ; Construction of simple formulae
Use of AutoSum Calculate Sum; Maximum; Minimum, Average ; Using the Insert function
Use of IF statement; Creating and formatting charts.
Conditional formatting.

LaTex (5 weeks) Introduction to LaTex and using it to write equations; typesetting advantages and disadvantages.

R (9 weeks)

Introduction to R – a sample R session: invoking the R system and modes of operation (interactive, batch). Integrated Development

Environments for R (e.g. Rstudio). The source() command. Extending

R: installing additional packages.

Simple commands in R including left-to-right and right-to-left assignments. Accessing help locally and online. R classes and objects: vectors, lists, arrays, matrices, tables and data frames. Creating each type of object and rules for allowing/disallowing mixed classes within an object. Accessing elements of each object type. Object attributes. Special values: NA, NULL, NaN. Inf etc. R programming using logical operators (e.g. ==, !, |, &) and control flow structures (e.g. if, for, while, else, []).

Reading external data sets into data frames from comma and general delimited files and data stored in a Excel spreadsheets. The colnames and rownames attributes. Rules for mixed classes in columns and class coercion. Ordering and forming subsets of vectors, lists and data frames. Attaching and detaching data frames, search paths and with() function.

Basic summary statistics: numeric summaries including measures of location and dispersion. Calculating summary statistics by groups (factors). Factors and factor levels. Tables and cross-tabulations with two or more factors.

Functions in R: inbuilt and user defined. User defined functions with one two or more named arguments. Local and global assignments and function returns. Loading user defined functions automatically at start up.

Plotting: Plots in R. The default plotting device and calling multiple devices. Standard plots such as scatterplots, histograms, bar charts, pie charts. Specifying colours and other plot attributes. Adding lines (including the least squares line) and text to a plot. Curve sketching and adding curves to plots. Adding legends with colour, character and line keys. Customising axes. Outputting plots to other devices, e.g. pdf, jpg, pgn devices. Introduction to data visualisation using R. Plotting in 3 dimensions (e.g. the rgl package).

Introduction to R dynamic reporting (e.g. sweave, knitr, Markdown)

Module Content & Assessment
Assessment Breakdown %
Other Assessment(s)100