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7 event found

Keywords: Statistical Methods 

  • Fundamentals of Statistics: Online

    16 - 20 January 2023

    Fundamentals of Statistics: Online https://dresa.org.au/events/fundamentals-of-statistics-online In this course you will obtain a solid foundation in basic statistical concepts and procedures to progress with some confidence into more advanced topics. This is an introductory unit in statistical methods with the emphasis on statistical techniques applicable to the social sciences, although these introductory techniques are also appropriate to the health sciences. Key examples from journal articles will be presented to illustrate the use and reporting of the statistical techniques covered in this unit. Our approach to learning will be largely non-mathematical, concentrating on concepts rather than mathematical theory. Participants familiar with the use of a statistical software package, but lacking statistical training should also start with this course. SOFTWARE The course will be using the free and open-source software jamovi. The software jamovi can be downloaded from https://www.jamovi.org.download.html While jamovi is built on top of the R statistical language, it has a look and feel very similar to IBM SPSS Statistics and in many ways is easier to use. Depending on student preferences, there will be an opportunity to use IBM SPSS Statistics v28. Instructions will be provided for both packages and students can choose either jamovi or IBM Statistics v28. 2023-01-16 10:00:00 UTC 2023-01-20 16:30:00 UTC ACSPRI online, Australia online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all Fundamentals of StatisticsStatistical MethodsJamoviquantitativeStatistics
  • Fundamentals of Structural Equation Modelling: Online

    16 - 20 January 2023

    Fundamentals of Structural Equation Modelling: Online https://dresa.org.au/events/fundamentals-of-structural-equation-modelling-online Structural equation modelling—or structural equations with latent variables—is a very general statistical model and widely used method. For example, SEM is used in fundamental disciplines such as the social, economic and psychological sciences, the biological sciences, and applied disciplines such as education, health and marketing. SEM has become popular for several reasons, apart from its generality: (i) all SEM models can be represented visually, (ii) a standard notation helps researchers to communicate, and (iii) several software packages for estimating SEM models are readily available (e.g., AMOS, LISREL, Mplus, R). This course provides an overview of the fundamentals of SEM. As well as the statistical theory, an overview of the many applications and capabilities of SEM is given. The course is not particularly mathematical, but instead places emphasis on the fundamental concepts of SEM and how it is used by applied researchers. General aims of the course are for students to develop a readiness for using SEM software and to develop the requisite knowledge for applying SEM methods and models in an intelligent way. Note that participants may be invited to briefly present their own research on the last day of class. This exercise, along with the formal lecture material, might help participants to chart a direction forward in their study and application of SEM. 2023-01-16 10:00:00 UTC 2023-01-20 17:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all SEMStructural equation modellingStatistical Methodsquantitative
  • Multi-level Analysis using Mplus: Online

    16 - 20 January 2023

    Multi-level Analysis using Mplus: Online https://dresa.org.au/events/multi-level-analysis-using-mplus-online This course is designed as an introduction to the concepts and techniques required to analyse data that is multi-level in nature. (That is, data that is derived from subjects who are nested within groups or data that involves repeated measures that are nested within subjects) In conventional regression analysis it is assumed that subjects are randomly selected and, therefore, all the variance in your dependent variables is due solely to variation amongst individuals. However, in most studies, subjects are clustered within a group and multiple groups are sampled. For example, in an education study, we may have students clustered within multiple classes; in a human resourcing study, we may have employees clustered within multiple work units or teams. In such sampling, although some of the variance in your dependent variables will be due to variation amongst individuals, some the variance in your dependent variables will also be due to variation amongst the groups themselves. In such cases, multilevel analysis (MLA) should be employed to account for the different levels of variation. Repeated measure designs should also be analysed using multilevel analysis because the repeated observations are nested within subjects. For example, in a marketing study, we may have repeated measures of consumers’ attitudes to a brand over the life of a marketing campaign; in an epidemiology study, we may have repeated measures of a health outcome over the life of a drug treatment regime. In such studies, although some of the variance in your dependent variables will be due to variation across the various time occasions, some the variance in your dependent variables will also be due to variation amongst individuals themselves. Again, in such cases, multilevel analysis (MLA) should be employed to account for the different levels of variation. 2023-01-16 10:00:00 UTC 2023-01-20 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all multilevel modellingSEMStatistical MethodsStatistics
  • Applied Statistical Procedures: Online

    6 - 10 February 2023

    Applied Statistical Procedures: Online https://dresa.org.au/events/applied-statistical-procedures-online This is an intermediate, applied course covering a range of the most commonly used statistical procedures. Research design, Experimental, Quasi-Experimental and Non-Experimental, will be covered so students can select the best design and statistical procedure for a research project, and to clarify exactly what claims can be made in relation to findings. It aims to provide participants with an ability to understand, run and interpret procedures. This course will further enhance your ability to understand research-based literature. The level falls between ‘Fundamentals of Statistics’, and the more detailed single procedure based courses. This course will provide a good foundation for progression to the more detailed courses in (Multiple) Regression, Factor Analysis, SEM and Latent Variables using Mplus. On completing this course you should be able to read and understand literature where these procedures are reported, select the appropriate statistical procedure for research, run the procedure, and report the results from an informed base of understanding. The course is taught from an applied prospective, with questions encouraged. The statistical package employed will be SPSS. No prior knowledge of SPSS is required. 2023-02-06 10:00:00 UTC 2023-02-10 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] workshop open_to_all StatisticsStatistical Methodsapplied statistics SPSS
  • Fundamentals of Multiple Regression: Online

    6 - 10 February 2023

    Fundamentals of Multiple Regression: Online https://dresa.org.au/events/fundamentals-of-multiple-regression-online The course is designed for those who have limited knowledge and experience with multivariate statistical techniques and are seeking the knowledge and skills to use multiple regression for research at a post-graduate level and/or to publish in professional research journals. Particular attention is given to the application of multiple regression to substantive problems in the social and behavioral sciences. (See Course Program below.) By the end of the course, you will understand the principles of multiple regression, and be able to conduct regression analyses, interpret the results, obtain regression diagnostics to test the underlying model assumptions and write-up the results for publication. The course notes provide instructions for using the major statistical packages (SPSS, SAS, Stata) for regression. Participants who are considering regression analysis of their own data are encouraged and there will be time for individual consultations. This course provides the foundations necessary for progression to ‘Applied Multiple Regression Analysis’, and to subsequent advanced-level courses in structural equation modelling and multi-level analysis. 2023-02-06 10:00:00 UTC 2023-02-10 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all Multiple RegressionquantitativeStatisticsStatistical Methodsapplied statistics
  • Data Analysis Using Stata: Online

    6 - 10 February 2023

    Data Analysis Using Stata: Online https://dresa.org.au/events/data-analysis-using-stata-online 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. 2023-02-06 10:00:00 UTC 2023-02-10 17:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all STATAapplied statisticsStatistical MethodsStatistics
  • Advanced Statistical Analysis Using R: Online

    6 - 10 February 2023

    Advanced Statistical Analysis Using R: Online https://dresa.org.au/events/advanced-statistical-analysis-using-r-online R is a free software environment for scientific and statistical computing and graphics that runs on all common computing platforms. An active and highly skilled developer community works on development and improvement. It has become an environment of choice for the implementation of new methodology. It is at the same time attracting wide attention from statistical application area specialists. The powerful and innovative graphics abilities available in R include the provision of well-designed publication-quality plots. The first day of this course will focus on the R software environment, the remaining days of this workshop will focus on learning advanced statistical methods with R. We will spend an almost equal amount of time in PowerPoint sessions and computer exercises. During the PowerPoint sessions the focus will be on the statistical methods with minimal discussion of computer software. During the computer exercise time you will be using R to apply the statistical methods taught in the lectures. At the start of each session of computer exercises Mark will perform the first exercise in each set on his own computer demonstrating to the class the use of the software and the statistical results obtained. 2023-02-06 10:00:00 UTC 2023-02-10 17:00:00 UTC ACSPRI Online Online ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all R statisticsStatistical MethodsStatisticsR statistical software
  • Fundamentals of Statistics: Online

    16 - 20 January 2023

    Fundamentals of Statistics: Online https://dresa.org.au/events/fundamentals-of-statistics-online In this course you will obtain a solid foundation in basic statistical concepts and procedures to progress with some confidence into more advanced topics. This is an introductory unit in statistical methods with the emphasis on statistical techniques applicable to the social sciences, although these introductory techniques are also appropriate to the health sciences. Key examples from journal articles will be presented to illustrate the use and reporting of the statistical techniques covered in this unit. Our approach to learning will be largely non-mathematical, concentrating on concepts rather than mathematical theory. Participants familiar with the use of a statistical software package, but lacking statistical training should also start with this course. SOFTWARE The course will be using the free and open-source software jamovi. The software jamovi can be downloaded from https://www.jamovi.org.download.html While jamovi is built on top of the R statistical language, it has a look and feel very similar to IBM SPSS Statistics and in many ways is easier to use. Depending on student preferences, there will be an opportunity to use IBM SPSS Statistics v28. Instructions will be provided for both packages and students can choose either jamovi or IBM Statistics v28. 2023-01-16 10:00:00 UTC 2023-01-20 16:30:00 UTC ACSPRI online, Australia online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all Fundamentals of StatisticsStatistical MethodsJamoviquantitativeStatistics
  • Fundamentals of Structural Equation Modelling: Online

    16 - 20 January 2023

    Fundamentals of Structural Equation Modelling: Online https://dresa.org.au/events/fundamentals-of-structural-equation-modelling-online Structural equation modelling—or structural equations with latent variables—is a very general statistical model and widely used method. For example, SEM is used in fundamental disciplines such as the social, economic and psychological sciences, the biological sciences, and applied disciplines such as education, health and marketing. SEM has become popular for several reasons, apart from its generality: (i) all SEM models can be represented visually, (ii) a standard notation helps researchers to communicate, and (iii) several software packages for estimating SEM models are readily available (e.g., AMOS, LISREL, Mplus, R). This course provides an overview of the fundamentals of SEM. As well as the statistical theory, an overview of the many applications and capabilities of SEM is given. The course is not particularly mathematical, but instead places emphasis on the fundamental concepts of SEM and how it is used by applied researchers. General aims of the course are for students to develop a readiness for using SEM software and to develop the requisite knowledge for applying SEM methods and models in an intelligent way. Note that participants may be invited to briefly present their own research on the last day of class. This exercise, along with the formal lecture material, might help participants to chart a direction forward in their study and application of SEM. 2023-01-16 10:00:00 UTC 2023-01-20 17:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all SEMStructural equation modellingStatistical Methodsquantitative
  • Multi-level Analysis using Mplus: Online

    16 - 20 January 2023

    Multi-level Analysis using Mplus: Online https://dresa.org.au/events/multi-level-analysis-using-mplus-online This course is designed as an introduction to the concepts and techniques required to analyse data that is multi-level in nature. (That is, data that is derived from subjects who are nested within groups or data that involves repeated measures that are nested within subjects) In conventional regression analysis it is assumed that subjects are randomly selected and, therefore, all the variance in your dependent variables is due solely to variation amongst individuals. However, in most studies, subjects are clustered within a group and multiple groups are sampled. For example, in an education study, we may have students clustered within multiple classes; in a human resourcing study, we may have employees clustered within multiple work units or teams. In such sampling, although some of the variance in your dependent variables will be due to variation amongst individuals, some the variance in your dependent variables will also be due to variation amongst the groups themselves. In such cases, multilevel analysis (MLA) should be employed to account for the different levels of variation. Repeated measure designs should also be analysed using multilevel analysis because the repeated observations are nested within subjects. For example, in a marketing study, we may have repeated measures of consumers’ attitudes to a brand over the life of a marketing campaign; in an epidemiology study, we may have repeated measures of a health outcome over the life of a drug treatment regime. In such studies, although some of the variance in your dependent variables will be due to variation across the various time occasions, some the variance in your dependent variables will also be due to variation amongst individuals themselves. Again, in such cases, multilevel analysis (MLA) should be employed to account for the different levels of variation. 2023-01-16 10:00:00 UTC 2023-01-20 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all multilevel modellingSEMStatistical MethodsStatistics
  • Applied Statistical Procedures: Online

    6 - 10 February 2023

    Applied Statistical Procedures: Online https://dresa.org.au/events/applied-statistical-procedures-online This is an intermediate, applied course covering a range of the most commonly used statistical procedures. Research design, Experimental, Quasi-Experimental and Non-Experimental, will be covered so students can select the best design and statistical procedure for a research project, and to clarify exactly what claims can be made in relation to findings. It aims to provide participants with an ability to understand, run and interpret procedures. This course will further enhance your ability to understand research-based literature. The level falls between ‘Fundamentals of Statistics’, and the more detailed single procedure based courses. This course will provide a good foundation for progression to the more detailed courses in (Multiple) Regression, Factor Analysis, SEM and Latent Variables using Mplus. On completing this course you should be able to read and understand literature where these procedures are reported, select the appropriate statistical procedure for research, run the procedure, and report the results from an informed base of understanding. The course is taught from an applied prospective, with questions encouraged. The statistical package employed will be SPSS. No prior knowledge of SPSS is required. 2023-02-06 10:00:00 UTC 2023-02-10 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] workshop open_to_all StatisticsStatistical Methodsapplied statistics SPSS
  • Fundamentals of Multiple Regression: Online

    6 - 10 February 2023

    Fundamentals of Multiple Regression: Online https://dresa.org.au/events/fundamentals-of-multiple-regression-online The course is designed for those who have limited knowledge and experience with multivariate statistical techniques and are seeking the knowledge and skills to use multiple regression for research at a post-graduate level and/or to publish in professional research journals. Particular attention is given to the application of multiple regression to substantive problems in the social and behavioral sciences. (See Course Program below.) By the end of the course, you will understand the principles of multiple regression, and be able to conduct regression analyses, interpret the results, obtain regression diagnostics to test the underlying model assumptions and write-up the results for publication. The course notes provide instructions for using the major statistical packages (SPSS, SAS, Stata) for regression. Participants who are considering regression analysis of their own data are encouraged and there will be time for individual consultations. This course provides the foundations necessary for progression to ‘Applied Multiple Regression Analysis’, and to subsequent advanced-level courses in structural equation modelling and multi-level analysis. 2023-02-06 10:00:00 UTC 2023-02-10 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all Multiple RegressionquantitativeStatisticsStatistical Methodsapplied statistics
  • Data Analysis Using Stata: Online

    6 - 10 February 2023

    Data Analysis Using Stata: Online https://dresa.org.au/events/data-analysis-using-stata-online 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. 2023-02-06 10:00:00 UTC 2023-02-10 17:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all STATAapplied statisticsStatistical MethodsStatistics
  • Advanced Statistical Analysis Using R: Online

    6 - 10 February 2023

    Advanced Statistical Analysis Using R: Online https://dresa.org.au/events/advanced-statistical-analysis-using-r-online R is a free software environment for scientific and statistical computing and graphics that runs on all common computing platforms. An active and highly skilled developer community works on development and improvement. It has become an environment of choice for the implementation of new methodology. It is at the same time attracting wide attention from statistical application area specialists. The powerful and innovative graphics abilities available in R include the provision of well-designed publication-quality plots. The first day of this course will focus on the R software environment, the remaining days of this workshop will focus on learning advanced statistical methods with R. We will spend an almost equal amount of time in PowerPoint sessions and computer exercises. During the PowerPoint sessions the focus will be on the statistical methods with minimal discussion of computer software. During the computer exercise time you will be using R to apply the statistical methods taught in the lectures. At the start of each session of computer exercises Mark will perform the first exercise in each set on his own computer demonstrating to the class the use of the software and the statistical results obtained. 2023-02-06 10:00:00 UTC 2023-02-10 17:00:00 UTC ACSPRI Online Online ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all R statisticsStatistical MethodsStatisticsR statistical software

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