# Data Analysis and Visualisation | My Assignment Tutor

UNIVERSITY OF WALES: TRINITY SAINT DAVIDPRIFYSGOL CYMRU: Y DRINDOD DEWI SANTBSc Cloud ComputingLondon CampusData Analysis and VisualisationACCB4002 Module CodeACCB4002TitleData Analysis and VisualisationDate09/09/2020Level4Credits20Pre-RequisitesNone AIM(S) To develop the knowledge and skills required to perform basic statistical analysis ofexperimental data.  To introduce students to a wide variety of techniques used to display different typesof data effectively. The student will learn to design data presentations for both staticand interactive displays, both individual and team scenarios.LEARNING OUTCOMESUpon the successful completion of this module, the student should be able to: Select and apply appropriate statistical methods for the analysis of well-definedproblems. Demonstrate an ability to present nominal, ordinal, categorical and network data informs that enable the easy understanding of the data  Demonstrate an ability to rearrange data in order to extract hidden information Apply colour, position, size, shape and icons to encode information creatively andeffectively to solve well-defined problems in information visualisation. INDICATIVE CONTENT Frequency distributions, descriptive statistics, the normal curve, percentiles andstandard scores, hypothesis development, confidence limits  Correlation coefficients, the t test, chi-square test Software for statistical analysis and data visualisation Different types of data; nominal, ordinal, categorical, network data; univariate,bivariate, trivariate, hypervariate data  Appropriate display methods for differing data types; graphs, tables, icons. Histograms, boxplots, scatterplots, barcharts, parallel coordinate plots, maps Rearranging data to extract meaning from it; introducing distortion to provide clarity Identifying problems with visualisationsStudy Time AllocationThe study time for the module is divided as follows: Activity typeHoursPercentageScheduled learning4824%Independent learning15276%Placement learning00%TOTAL200100% ASSESSMENTAssessment Component 1 ☐Written exam☒Coursework☐Practical Mode of assessmentVolumeWeightingReport2000 words50% Assessment Component 2 ☐Written exam☒Coursework☐Practical Mode of assessmentVolumeWeightingReport2000 words50% Assessment Summary Activity typePercentageWritten exam0%Coursework100%Practical0%TOTAL100% INDICATIVE READING LIST Module CodeACCB4002Module TitleData Analysis and VisualisationClassificationReading List entryElectronic*EssentialKranzler, J.H. (2017) Statistics for the Terrified, Rowman &Littlefield.☒EssentialFew, S. (2012), Show Me The Numbers, Analytics Press,Burlingame, CA.☒FurtherSchmuller, J. (2016), Statistical Analysis With Excel ForDummies (4th Ed.), John Wiley and Sons☒FurtherMacInnes, J. (2018), Little Quick Fix: Know Your Numbers,Sage,☒FurtherSpiegel, M.R (2014) Shaum’s Outline of Statistics, fifth ed.,McGraw Hill Education Limited☒FurtherGonick, L & Smith, W. (2000) Cartoon Guide to Statistics,William Morrow Paperbacks☒FurtherSpence, R. (2014), Information Visualization: An IntroductionPrentice Hall☐FurtherTufte, E. (2001) The Visual Display of QuantitativeInformation (2nd Ed.) Graphics Press USA☐ FurtherTufte, E. (1997), Visual Explanations, Images and Quantities,Evidence and Narrative. Graphics Press☐FurtherTufte, E. (1990) Envisioning Information, Graphics Press USA☐

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