Academic literature on the topic 'Statistical visualisation'
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Journal articles on the topic "Statistical visualisation"
SUTHERLAND, SINCLAIR, and JIM RIDGWAY. "INTERACTIVE VISUALISATIONS AND STATISTICAL LITERACY." STATISTICS EDUCATION RESEARCH JOURNAL 16, no. 1 (May 31, 2017): 26–30. http://dx.doi.org/10.52041/serj.v16i1.210.
Full textCuthbert, Carol E., and Noel J. Pearse. "Strategic Data Pattern Visualisation." Journal of Systemics, Cybernetics and Informatics 20, no. 1 (January 2022): 122–41. http://dx.doi.org/10.54808/jsci.20.01.122.
Full textKhormi, Sameer Ali, Areeb Alshoshan, and Abdulrahman Binrsheed. "THE IMPACT OF USING LOGO PROGRAMMING LANGUAGE ON THE DEVELOPMENT OF SPATIAL VISUALISATION ABILITY AMONG ELEMENTARY SCHOOL STUDENTS." International Journal of Research -GRANTHAALAYAH 9, no. 3 (March 26, 2021): 118–27. http://dx.doi.org/10.29121/granthaalayah.v9.i3.2021.3771.
Full textBreddels, M. A. "Interactive (statistical) visualisation and exploration of a billion objects with vaex." Proceedings of the International Astronomical Union 12, S325 (October 2016): 299–304. http://dx.doi.org/10.1017/s1743921316012795.
Full textLodha, Suresh, Prabath Gunawardane, Erin Middleton, and Ben Crow. "Understanding relationships between global health indicators via visualisation and statistical analysis." Journal of International Development 21, no. 8 (November 2009): 1152–66. http://dx.doi.org/10.1002/jid.1652.
Full textAndruszkiewicz, Anna, and Jolanta Korycka-Skorupa. "The cartographic visualisation of spatial data. An example of nature protection areas in the Podlaskie Voivodship (north-eastern Poland)." Polish Cartographical Review 52, no. 3 (September 1, 2020): 108–23. http://dx.doi.org/10.2478/pcr-2020-0009.
Full textGRANT, ROBERT. "STATISTICAL LITERACY IN THE DATA SCIENCE WORKPLACE." STATISTICS EDUCATION RESEARCH JOURNAL 16, no. 1 (May 31, 2017): 17–21. http://dx.doi.org/10.52041/serj.v16i1.207.
Full textFORBES, SHARLEEN, JEANETTE CHAPMAN, JOHN HARRAWAY, DOUG STIRLING, and CHRIS WILD. "USE OF DATA VISUALISATION IN THE TEACHING OF STATISTICS: A NEW ZEALAND PERSPECTIVE." STATISTICS EDUCATION RESEARCH JOURNAL 13, no. 2 (November 28, 2014): 187–201. http://dx.doi.org/10.52041/serj.v13i2.290.
Full textSweatman, Winston LeMay, James McGree, Corrie Jacobien Carstens, Kylie J. Foster, Shen Liu, Nicholas Tierney, Eloise Tredenick, and Ayham Zaitouny. "Visualisation and statistical modelling techniques for the management of inventory stock levels." ANZIAM Journal 57 (August 28, 2016): 130. http://dx.doi.org/10.21914/anziamj.v57i0.10225.
Full textKról, Karol. "MAP CHARTS: VISUALISATION OF STATISTICAL DATA ON A BACKGROUND MAP – CASE STUDY." Geomatics, Landmanagement and Landscape 4 (2020): 171–81. http://dx.doi.org/10.15576/gll/2019.4.171.
Full textDissertations / Theses on the topic "Statistical visualisation"
Albazzaz, Hamza. "Multivariate statistical batch process control and data visualisation based on independent component analysis." Thesis, University of Leeds, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.432293.
Full textTORTI, FRANCESCA. "Advances in the forward search: methodological and applied contributions." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2010. http://hdl.handle.net/10281/7791.
Full textKobakian, Stephanie Rose. "New algorithms for effectively visualising Australian spatio-temporal disease data." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/203908/1/Stephanie_Kobakian_Thesis.pdf.
Full textAlfadda, Dalal Abdulaziz. "How Does a ‘Model of Graphics’ Approach and Peer Tutoring Lead to Deep Understanding of Data Visualisation?" Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/27203.
Full textLaurent, Anabelle. "The analysis of data from on-farm research network : Statistical approaches to test the efficacy of management practices and data visualization." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASB022.
Full textAn on-farm research network is an organization of farmers that conducts agronomic experiments under local conditions. There is growing interest in on-farm research networks because they provide the infrastructure needed to test new products and management practices in farmers’ fields. Often, the results are usually presented as individual reports (i.e., a report summarizing the outcome for one trial), but this provides limited information difficult to generalize and does not allow presenting, in a synthetic way, all the results collected from the different trials. Moreover, there is an unexplored potential in detecting yield response variability patterns for better decision making. The overall objective of this thesis is to demonstrate the importance of identifying appropriate statistical methods for analyzing and visualizing on-farm research network data. Specifically, I focused on analyzing the on-farm research networks managed by the Iowa Soybean Association, and an adaptation was made with a French case-study. A data-analytics framework was developed to analyze multiple trials that use a common protocol and identify the conditions where an imposed treatment may or may not be effective. This framework used a random-effect model through a Bayesian approach and returned yield response estimates at the network and trial levels. The framework was implemented through a web-application for 51 different management practices on corn and soybean. The web-application includes dynamic data visualization features to enhance communication and information sharing, and is accessible to a broad audience to improve accessibility to on-farm research insights. A random-effects statistical model was used to compute prediction intervals describing a range of plausible yield response for a new (out-of-sample) trial, and compute the probability that the tested management practice will be ineffective in a new field. Depending on the level of between-trial variability, the prediction intervals were 2.2–12.1 times larger than confidence intervals for the estimated mean yield responses (i.e., at the network level) for all tested management practices. Using prediction intervals and the probability of ineffective treatment will prevent farmers from over-optimistic expectations that a significant effect at the network level will lead with high certainty to a yield gain on their farms. The data-analytic framework was adapted to a French on-farm research network focusing on the efficacy of biocontrol agent products against Botrytis cinerea, potassium bicarbonate and Aureobasidium pullulans, on organic vine. The results favored potassium bicarbonate as its efficacy on incidence at the network level is higher for diseased intensities between 0% and 10% than for Aureobasidium pullulans. For both biocontrol agents, the efficacy on incidence for a new trial is highly uncertain for intensity levels higher than 15%. Finally, this research investigated the impact of experimental plot scale (i.e., small-plot scale and field scale) on the effect of management practice on crop yield and identified the cause of potential discrepancies to inform on-farm decision-making better and adapt the extrapolation of the results. Taken together, this research represents the first major effort in consolidating results from on-farm research network and provides insight to make better farming management decisions
Phaweni, Thembani. "Classification and visualisation of text documents using networks." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29534.
Full textByström, Gustaf. "User centred prototyping iPhone visualisation of XMS Penvision statistics." Thesis, Linköpings universitet, Institutionen för teknik och naturvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-94736.
Full textXMS Penvision tillhandahåller idag en plattform till sina kunder för skapande av pappersformulär med den speciella teknik som detta kräver och hanteringen av tillhörande digitala pennor. Plattformen sträcker sig över flera olika operativsystem men har ännu inte tagit steget över till iPhone. XMS Penvisions ambition är att genomföra detta och vill då börja med att visa statistisk administrativ information gällande deras plattform. Syftet med detta examensarbete är att lyfta fram behov och önskemål från XMS Penvisions kunder med hjälp av användarcentrerade metoder och skapa en prototyp över ett administrativt gränssnitt för iPhone. Användbarhetsmål, prototyping, heuristisk utvärdering och användningstest är några av de metoder som under arbetet tillämpades och rapporten beskriver dessa metoder, dels genom teori men också genom diskussion kring tillämpandet. Slutresultatet är en prototyp implementerad på iPhone. Prototypen använder sig av data direkt hämtad från XMS Penvsions system och användarnas åsikter finns dokumenterade.
Burke, Tommy. "Evaluation of visualisations of geographically weighted regression, with perceptual stability." Thesis, University of St Andrews, 2016. http://hdl.handle.net/10023/15680.
Full textGood, Norman Markus. "Methods for estimating the component biomass of a single tree and a stand of trees using variable probability sampling techniques." Thesis, Queensland University of Technology, 2001. https://eprints.qut.edu.au/37097/1/37097_Good_2001.pdf.
Full textKrusche, Stefan. "Visualisierung und Analyse multivariater Daten in der gartenbaulichen Beratung -Methodik, Einsatz und Vergleich datenanalytischer Verfahren." Doctoral thesis, Humboldt-Universität zu Berlin, Landwirtschaftlich-Gärtnerische Fakultät, 1999. http://dx.doi.org/10.18452/14463.
Full textIn order to interpret large data sets in the context of consultancy and extension in horticulture, this thesis attempts to find ways to visually explore horticultural multivariate data, in order to obtain a concise description and summary of the information available in the data and moreover develop possibilities to interactively analyse survey data. The thesis is part of an exploratory data analysis which analyses data without making specific model assumptions, is predominantly descriptive, analyses data step by step in a highly interactive setting, and makes full use of all kinds of graphical displays. The methods used comprise various dimensionality reduction techniques (principal components analysis, correspondence analysis, multidimensional scaling), biplots, the multivariate analysis of grouped data (procrustes rotation and groupwise principal components), graphical models, CART, and line diagrams of formal concept analysis. In addition, further graphical methods are used, like e.g. trellis displays. Data from an on-site investigation of the production process of Cyclamen in 20 nurseries and from the microeconomics indicators of 297 growers in Germany (so called Kennzahlen) from the years 1992 to 1994 are used to demonstrate the analytical capabilities of the methods used. The data present a perfect example of unperfect data, and therefore represent the majority of the data sets that horticultural consultancy has to work with. Thus, it becomes clear, that despite the variety of results, which helps to enhance the understanding of the data at hand, not only the complexity of the processes observed, but also the low data quality make it fairly difficult to arrive at clear cut conclusions. The most helpful tools in the graphical data analysis are biplots, hierarchical line diagrams and trellis displays. Finding an empirical grouping of objects is best solved by classification and regression trees, which provide both, the data segmentation, and an intuitively appealing visualisation and explanation of the derived groups. In order to understand multivariate relationships better, discrete graphical models are well suited. The procedures to carry out a number of the methods which cannot be found in general statistics packages are provided in the form of Genstat codes.
Books on the topic "Statistical visualisation"
Visualization and verbalization of data. Boca Raton: CRC Press, Taylor & Francis Group, 2014.
Find full textFarebrother, R. W. Visualizing statistical models and concepts. New York: Marcel Dekker, 2002.
Find full textSAS Institute. Discovering JMP 11. [Place of publication not identified]: SAS Institute, 2013.
Find full textR: Data analysis and visualization : a course in five modules. Birmingham [United Kingdom]: Packt, 2016.
Find full textImpact of Visual Simulations in Statistics: The Role of Interactive Visualizations in Improving Statistical Knowledge. Springer, 2014.
Find full textO'Donoghue, Peter, Ambikesh Jayal, Allistair McRobert, and Giles Oatley. Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance. Taylor & Francis Group, 2018.
Find full textO'Donoghue, Peter, Ambikesh Jayal, Allistair McRobert, and Giles Oatley. Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance. Taylor & Francis Group, 2018.
Find full textO'Donoghue, Peter, Ambikesh Jayal, Allistair McRobert, and Giles Oatley. Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance. Taylor & Francis Group, 2018.
Find full textData Analytics for business Edition. Data Analytics : for Statisticians Biologists Scientific Research Surveys : Collect Data with Statistical Tables to Fill for Data /analysis *Average Variance Standard Deviation*: Data Visualisation and Statistical Inference Time Series Data Analysis Tracker. Independently Published, 2020.
Find full textData Analytics for Business : Collect Data Tool with Statistical Tables to Fill for Data Analytics / Analysis *Average Variance Standard Deviation*: Data Visualisation and Statistical Inference Time Series Data Analysis Tracker a Manual for Polls Surveys. Independently Published, 2020.
Find full textBook chapters on the topic "Statistical visualisation"
Aitkin, Murray. "Data visualisation." In Introduction to Statistical Modelling and Inference, 111–16. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003216025-9.
Full textRogel-Salazar, Jesús. "Alluring Arguments and Ugly Facts – Statistical Modelling and Hypothesis Testing." In Statistics and Data Visualisation with Python, 267–382. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003160359-6.
Full textVidmar, Gaj. "Pixelisation-Based Statistical Visualisation for Categorical Datasets with Spreadsheet Software." In Pixelization Paradigm, 48–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71027-1_5.
Full textGower, John C. "Visualisation." In Geometry Driven Statistics, 282–87. Chichester, UK: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118866641.ch14.
Full textAsche, Hartmut, Carolin Kucharczyk, and Marion Simon. "Geodata Discovery Assistant: A Software Module for Rule-Based Cartographic Visualisation and Analysis of Statistical Mass Data." In Computational Science and Its Applications -- ICCSA 2015, 566–75. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21470-2_41.
Full textBrezina, Vaclav, and Aina Casaponsa. "Statistics and data visualisation." In Introducing Linguistics, 426–46. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003045571-28.
Full textYoung, Joanna, and Jan Wessnitzer. "Descriptive Statistics, Graphs, and Visualisation." In Human–Computer Interaction Series, 37–56. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26633-6_3.
Full textRogel-Salazar, Jesús. "The Measure of All Things – Statistics." In Statistics and Data Visualisation with Python, 141–78. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003160359-4.
Full textRogel-Salazar, Jesús. "Delightful Details – Data Visualisation." In Statistics and Data Visualisation with Python, 383–416. Boca Raton: Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003160359-7.
Full textShardt, Yuri A. W. "Introduction to Statistics and Data Visualisation." In Statistics for Chemical and Process Engineers, 1–30. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21509-9_1.
Full textConference papers on the topic "Statistical visualisation"
Vadakkoot, Raveendran, and Achuth Raghavendra. "Improved image visualisation through statistical techniques." In 2009 4th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2009. http://dx.doi.org/10.1109/iciea.2009.5138631.
Full textKapelner, Adam, Peter P. Lee, and Susan Holmes. "An Interactive Statistical Image Segmentation and Visualization System." In International Conference on Medical Information Visualisation - BioMedical Visualisation (MediVis 2007). IEEE, 2007. http://dx.doi.org/10.1109/medivis.2007.5.
Full textRidgway, Jim, James Nicholson, Pedro Campos, and Sónia Teixeira. "Tools for visualizing data: a review." In Teaching Statistics in a Data Rich World. International Association for Statistical Education, 2018. http://dx.doi.org/10.52041/srap.17201.
Full textRusu, Adrian, Doru Stoica, Edward Burns, Benjamin Hample, Kevin McGarry, and Robert Russell. "Dynamic Visualizations for Soccer Statistical Analysis." In 2010 14th International Conference Information Visualisation (IV). IEEE, 2010. http://dx.doi.org/10.1109/iv.2010.39.
Full textPatel, Vijay, Henri Brouquet, Bryan Shaughnessy, and Julian Thomas. "An Investigation of Statistical Visualisation Techniques for Thermal Applications." In 40th International Conference on Environmental Systems. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-6086.
Full textButters, T. D., T. J. Sharpe, S. Guttel, and J. L. Shapiro. "Statistical cluster analysis and visualisation for alarm management configuration." In Asset Management Conference 2014. Institution of Engineering and Technology, 2014. http://dx.doi.org/10.1049/cp.2014.1027.
Full textBrebric, Marina, Mihaela Vranic, and Damir Pintar. "Streamlining visualisation of geographical data through statistical programming tools." In 2018 First International Colloquium on Smart Grid Metrology (SmaGriMet). IEEE, 2018. http://dx.doi.org/10.23919/smagrimet.2018.8369853.
Full textUnger, Andrea, Phillip Muigg, Helmut Doleisch, and Heidrun Schumann. "Visualizing Statistical Properties of Smoothly Brushed Data Subsets." In 2008 12th International Conference Information Visualisation (IV). IEEE, 2008. http://dx.doi.org/10.1109/iv.2008.29.
Full textNor, Muhammed Haziq Muhammed, Choong-Yeun Liong, and Hariharan Gunasekaran. "Visualisation and prediction of user ratings on video games using web analytics." In The 5TH ISM INTERNATIONAL STATISTICAL CONFERENCE 2021 (ISM-V): Statistics in the Spotlight: Navigating the New Norm. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0128976.
Full textHenderson, Hatold. "Visualizing data with dynamic graphics in excel." In Statistics Education and the Communication of Statistics. International Association for Statistical Education, 2005. http://dx.doi.org/10.52041/srap.05204.
Full textReports on the topic "Statistical visualisation"
McCarthy, Noel, Eileen Taylor, Martin Maiden, Alison Cody, Melissa Jansen van Rensburg, Margaret Varga, Sophie Hedges, et al. Enhanced molecular-based (MLST/whole genome) surveillance and source attribution of Campylobacter infections in the UK. Food Standards Agency, July 2021. http://dx.doi.org/10.46756/sci.fsa.ksj135.
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