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2 events found
Keywords: STATA or Predictive Analytics
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Data Analysis Using Stata: Online
20 - 24 January 2025
Data Analysis Using Stata: Online https://www.acspri.org.au/summer-program-2025/data-analysis-using-stata-online https://dresa.org.au/events/data-analysis-using-stata-online-8f70c6bb-483c-445b-a08f-56082b7de9b2 Stata is a comprehensive integrated package for data management, analysis and graphics. Stata has a comprehensive GUI interface. Sample datasets will be provided, but you are encouraged to bring some of your own data for analysis in Excel or ASCII format. Teaching and practice will be closed integrated. Private consultations will be allocated during the course as needed. The course is suitable for beginners to the Stata package and will be presented in a way that introduces survey research. It is also appropriate to those familiar with Stata as it extends the capabilities of more experienced researchers. 2025-01-20 10:00:00 UTC 2025-01-24 17:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au ph: +61 3 8376 6496 [] [] 12 workshop open_to_all STATAapplied statisticsStatistical MethodsStatistics -
Predictive Analytics for Data Science: Linear and Non-Linear Modelling
28 - 29 March 2025
Predictive Analytics for Data Science: Linear and Non-Linear Modelling https://www.acspri.org.au/master-class-march-2025-predictive-analytics-data-science-online https://dresa.org.au/events/predictive-analytics-for-data-science-linear-and-non-linear-modelling-e8d89bd0-1e2e-44ba-b3bf-5f3094a2130f This masterclass is an introduction to linear and non-linear predictive models. It will provide an interactive step-by-step guide to running these models and key diagnostics using the R software platform. Regression modelling is a foundation in data science and a must for anyone wanting to venture into this space. Understanding when and how to use linear and non-linear regression models in everyday research is an essential skill for any analyst. Linear and non-linear regression models are commonly used to quantify the relationship between two or more variables by predicting a key outcome of interest. These models are used as effective and powerful tools to control for the potential confounding effect of extraneous variables and/or developing highly predictive models. Linear regression relates to continuous outcomes and is a fundamental regression technique in data science. Logistic regression is used when the outcome of interest is categorical and a fundamental classification technique in data science. When there is no theoretical or mechanistic model to suggest a particular functional form to describe the relationship between two or more variables of interest, Generalized Additive Models (GAMs) can used as they fit a nonparametric curve to the data without requiring pre-defining any particular mathematical model to describe the nonlinearity. Gaining a sound understanding of all these models is essential to understand when it is appropriate to use these techniques. 2025-03-28 09:30:00 UTC 2025-03-29 17:00:00 UTC ACSPRI online, Australia online Australia ACSPRI info@acspri.org.au [] researchersPhD studentsHDR students 12 workshop open_to_all Predictive modelsPredictive AnalyticsData Sciencesocial data science
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Data Analysis Using Stata: Online
20 - 24 January 2025
Data Analysis Using Stata: Online https://www.acspri.org.au/summer-program-2025/data-analysis-using-stata-online https://dresa.org.au/events/data-analysis-using-stata-online-8f70c6bb-483c-445b-a08f-56082b7de9b2 Stata is a comprehensive integrated package for data management, analysis and graphics. Stata has a comprehensive GUI interface. Sample datasets will be provided, but you are encouraged to bring some of your own data for analysis in Excel or ASCII format. Teaching and practice will be closed integrated. Private consultations will be allocated during the course as needed. The course is suitable for beginners to the Stata package and will be presented in a way that introduces survey research. It is also appropriate to those familiar with Stata as it extends the capabilities of more experienced researchers. 2025-01-20 10:00:00 UTC 2025-01-24 17:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au ph: +61 3 8376 6496 [] [] 12 workshop open_to_all STATAapplied statisticsStatistical MethodsStatistics -
Predictive Analytics for Data Science: Linear and Non-Linear Modelling
28 - 29 March 2025
Predictive Analytics for Data Science: Linear and Non-Linear Modelling https://www.acspri.org.au/master-class-march-2025-predictive-analytics-data-science-online https://dresa.org.au/events/predictive-analytics-for-data-science-linear-and-non-linear-modelling-e8d89bd0-1e2e-44ba-b3bf-5f3094a2130f This masterclass is an introduction to linear and non-linear predictive models. It will provide an interactive step-by-step guide to running these models and key diagnostics using the R software platform. Regression modelling is a foundation in data science and a must for anyone wanting to venture into this space. Understanding when and how to use linear and non-linear regression models in everyday research is an essential skill for any analyst. Linear and non-linear regression models are commonly used to quantify the relationship between two or more variables by predicting a key outcome of interest. These models are used as effective and powerful tools to control for the potential confounding effect of extraneous variables and/or developing highly predictive models. Linear regression relates to continuous outcomes and is a fundamental regression technique in data science. Logistic regression is used when the outcome of interest is categorical and a fundamental classification technique in data science. When there is no theoretical or mechanistic model to suggest a particular functional form to describe the relationship between two or more variables of interest, Generalized Additive Models (GAMs) can used as they fit a nonparametric curve to the data without requiring pre-defining any particular mathematical model to describe the nonlinearity. Gaining a sound understanding of all these models is essential to understand when it is appropriate to use these techniques. 2025-03-28 09:30:00 UTC 2025-03-29 17:00:00 UTC ACSPRI online, Australia online Australia ACSPRI info@acspri.org.au [] researchersPhD studentsHDR students 12 workshop open_to_all Predictive modelsPredictive AnalyticsData Sciencesocial data science
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