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* RSS - Programming in RRSS - Programming in R


Location: 12 Errol Street London EC1Y 8LX CPD: 12 hours Level: Intermediate Course Outline The course is a two day intensive course on programming principles in R. On completion of the course participants will gain experience in a range of programming techniques for the R programming language. Users will be able to write their own functions and scripts for undertaking bespoke data analysis tasks. Consideration of memory allocation, code profiling and leveraging parallel computation will also be explored to guide participants in the principles of efficient R programming. Learning Outcomes By attending the course participants will gain experience in writing their own functions and scripts for data analysis in the R programming language. They will improve on their data manipulation skills. Further, attendees will also gain an understanding of how to make code more efficient and to extend their workflow to leverage the power of parallel computing. Topics Covered Data manipulation and aggregation using dplyr Control flow: conditional expressions, functional composition, for loops The 'apply' family of functions Efficient data structures Code Profiling Avoiding loops Parallel computing Target Audience This course is idea for anyone who would like to extend their basic familiarity with using R, and using R to write their own bespoke functions or optimizing their code.

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* RSS - Programming in RRSS - Programming in R


Location: 12 Errol Street London EC1Y 8LX CPD: 12 hours Level: Intermediate Course Outline The course is a two day intensive course on programming principles in R. On completion of the course participants will gain experience in a range of programming techniques for the R programming language. Users will be able to write their own functions and scripts for undertaking bespoke data analysis tasks. Consideration of memory allocation, code profiling and leveraging parallel computation will also be explored to guide participants in the principles of efficient R programming. Learning Outcomes By attending the course participants will gain experience in writing their own functions and scripts for data analysis in the R programming language. They will improve on their data manipulation skills. Further, attendees will also gain an understanding of how to make code more efficient and to extend their workflow to leverage the power of parallel computing. Topics Covered Data manipulation and aggregation using dplyr Control flow: conditional expressions, functional composition, for loops The 'apply' family of functions Efficient data structures Code Profiling Avoiding loops Parallel computing Target Audience This course is idea for anyone who would like to extend their basic familiarity with using R, and using R to write their own bespoke functions or optimizing their code.

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* Women in Statistics ConferenceWomen in Statistics Conference


The American Statistical Association invites you to join us at the 2019 Women in Statistics and Data Science Conference in Bellevue, Washington. Professionals and students from academia, industry, and the government working in statistics and data science will gather and find unique opportunities to grow their influence, community, and knowledge. Whether you are a student, early-career professional, or experienced statistician or data scientist, this conference will deliver new knowledge and connections in an intimate and comfortable setting.

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* Women in Statistics ConferenceWomen in Statistics Conference


The American Statistical Association invites you to join us at the 2019 Women in Statistics and Data Science Conference in Bellevue, Washington. Professionals and students from academia, industry, and the government working in statistics and data science will gather and find unique opportunities to grow their influence, community, and knowledge. Whether you are a student, early-career professional, or experienced statistician or data scientist, this conference will deliver new knowledge and connections in an intimate and comfortable setting.

* Joint Working GroupJoint Working Group


The working group has the aim to promote the development and application of biostatistical procedures in the fields of multiple testing and group adaptive designs.

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* Women in Statistics ConferenceWomen in Statistics Conference


The American Statistical Association invites you to join us at the 2019 Women in Statistics and Data Science Conference in Bellevue, Washington. Professionals and students from academia, industry, and the government working in statistics and data science will gather and find unique opportunities to grow their influence, community, and knowledge. Whether you are a student, early-career professional, or experienced statistician or data scientist, this conference will deliver new knowledge and connections in an intimate and comfortable setting.

* Joint Working GroupJoint Working Group


The working group has the aim to promote the development and application of biostatistical procedures in the fields of multiple testing and group adaptive designs.

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* RSS - New Fellow EventRSS - New Fellow Event

Time: 2019-09-16T18:30:00+00:000000000030201909



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* October IBS Journal ClubOctober IBS Journal Club


The International Biometric Society (IBS) Journal Club is an initiative, designed by the Education Committee to help members and others network and discuss recent papers published in IBS journals.

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* RSS - Discussion Paper MeetingRSS - Discussion Paper Meeting


Wednesday 16 October 2019, 05:00pm Location - Royal Statistical Society, 12 Errol Street London EC1Y 8LX Speaker: Paromita Dubey and Hans-Georg Müller(University of California at Davis, USA) Functional data analysis provides a popular toolbox of functional models for the analysis of samples of random functions that are real valued. In recent years, samples of time-varying object data such as time-varying networks that are not in a vector space have been increasingly collected. These data can be viewed as elements of a general metric space that lacks local or global linear structure and therefore common approaches that have been used with great success for the analysis of functional data, such as functional principal component analysis, cannot be applied. We propose metric covariance, a novel association measure for paired object data lying in a metric space (?, d) that we use to define a metric autocovariance function for a sample of random ?-valued curves, where ? generally will not have a vector space or manifold structure. The proposed metric autocovariance function is non-negative definite when the squared semimetric d2 is of negative type. Then the eigenfunctions of the linear operator with the autocovariance function as kernel can be used as building blocks for an object functional principal component analysis for ?-valued functional data, including time-varying probability distributions, covariance matrices and time dynamic networks. Analogues of functional principal components for time-varying objects are obtained by applying Fréchet means and projections of distance functions of the random object trajectories in the directions of the eigenfunctions, leading to real-valued Fréchet scores. Using the notion of generalized Fréchet integrals, we construct object functional principal components that lie in the metric space ?. We establish asymptotic consistency of the sample-based estimators for the corresponding population targets under mild metric entropy conditions on ? and continuity of the ?-valued random curves. These concepts are illustrated with samples of time-varying probability distributions for human mortality, time-varying covariance matrices derived from trading patterns and time-varying networks that arise from New York taxi trips.

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* Lambrecht Summer School 2019Lambrecht Summer School 2019



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* Lambrecht Summer School 2019Lambrecht Summer School 2019



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* Lambrecht Summer School 2019Lambrecht Summer School 2019



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* Lambrecht Summer School 2019Lambrecht Summer School 2019



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* CPD105 - PROPENSITY SCORECPD105 - PROPENSITY SCORE


SSA and ACEMS are proud to present the following 1-day workshop with Liz Stuart to be held on 21 October 2019 in Sydney: Propensity score methods for estimating causal effects in non-experimental studies: The why, what, and how

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* Intro to Machine Learning in RIntro to Machine Learning in R


This is a two day course covering the application of machine-learning methodology to real-world analytics problems. The course outlines the stages involved in a machine learning analysis, and walks through how to perform them using the R programming language and the caret library. Participants will be provided with exercises to complete in R so as to gain hands-on experience in using the methods presented. The individual stages of: problem formulation, data preparation, feature engineering, model selection and model refinement will be walked through in detail giving participants a solid process to follow for any machine-learning analysis. This includes methods for evaluating machine-learning models in terms of a performance metric as well as assessing bias and variance. Delegates are expect to bring a laptop with the R software installed.

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* Intro to Machine Learning in RIntro to Machine Learning in R


This is a two day course covering the application of machine-learning methodology to real-world analytics problems. The course outlines the stages involved in a machine learning analysis, and walks through how to perform them using the R programming language and the caret library. Participants will be provided with exercises to complete in R so as to gain hands-on experience in using the methods presented. The individual stages of: problem formulation, data preparation, feature engineering, model selection and model refinement will be walked through in detail giving participants a solid process to follow for any machine-learning analysis. This includes methods for evaluating machine-learning models in terms of a performance metric as well as assessing bias and variance. Delegates are expect to bring a laptop with the R software installed.

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* RSS - Data & Basic StatisticsRSS - Data & Basic Statistics


Location: Birkbeck, University of London Course Outline This practical, two-day workshop will present an overview of the manipulations of data that are often required prior to statistical analysis. Topics will include dealing with outliers, combining data from different sources, calculating annual average growth rates, weighting and smoothing data and constructing indexes. It also covers basic statistical methods used in describing data such as measures of central tendency and dispersion, correlation and the use of dummy variables in regression analysis. Topics Covered Day One - Data Manipulation Morning - Common problems in using data This session will begin with a discussion of data as samples from populations, observing data and detecting outliers, and issues that arise in merging data different sources. It will then discuss methods to summarise data, both cross sectionally and through time. Estimating growth rates involves an introduction to the use of logarithmic and exponential functions. The session will end by presenting methods to construct indexes, including Laspeyres, Paasche, Fisher and Tornqvist indexes. Afternoon – Exercises on data manipulation using Excel This will involve exercises on each of the topics covered in the morning session. The tutor will give an overview of how the exercises should be tackled. Participants will then be asked to do these at their own pace, with the tutor assisting when required. Full answers to the exercises will be given at the end of the session. Day Two - Statistical Inference Morning – Methods for statistical inference This session will introduce the ideas of sampling distribution, the normal and t distributions, a decision framework for testing hypotheses, correlation and the method of ordinary least squares regressions. Afternoon – Exercises on statistical inference using STATA In this session the participants will do some exercises by replicating the commands used by the tutor and some additional exercises on their own. The tutor will feedback on answers during the session. Delegate Feedback • Excellent examples used throughout. • Tutors were extremely knowledgeable and friendly.

* IBS- DR Academy meets IndustryIBS- DR Academy meets Industry


Connect – Collaborate – Create The aim of this workshop is to provide a meeting ground for academic researchers, statisticians in the pharmaceutical industry, as well as BSc, MSc and PhD students with an interest in statistical research. Free admission!

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* RSS - Data & Basic StatisticsRSS - Data & Basic Statistics


Location: Birkbeck, University of London Course Outline This practical, two-day workshop will present an overview of the manipulations of data that are often required prior to statistical analysis. Topics will include dealing with outliers, combining data from different sources, calculating annual average growth rates, weighting and smoothing data and constructing indexes. It also covers basic statistical methods used in describing data such as measures of central tendency and dispersion, correlation and the use of dummy variables in regression analysis. Topics Covered Day One - Data Manipulation Morning - Common problems in using data This session will begin with a discussion of data as samples from populations, observing data and detecting outliers, and issues that arise in merging data different sources. It will then discuss methods to summarise data, both cross sectionally and through time. Estimating growth rates involves an introduction to the use of logarithmic and exponential functions. The session will end by presenting methods to construct indexes, including Laspeyres, Paasche, Fisher and Tornqvist indexes. Afternoon – Exercises on data manipulation using Excel This will involve exercises on each of the topics covered in the morning session. The tutor will give an overview of how the exercises should be tackled. Participants will then be asked to do these at their own pace, with the tutor assisting when required. Full answers to the exercises will be given at the end of the session. Day Two - Statistical Inference Morning – Methods for statistical inference This session will introduce the ideas of sampling distribution, the normal and t distributions, a decision framework for testing hypotheses, correlation and the method of ordinary least squares regressions. Afternoon – Exercises on statistical inference using STATA In this session the participants will do some exercises by replicating the commands used by the tutor and some additional exercises on their own. The tutor will feedback on answers during the session. Delegate Feedback • Excellent examples used throughout. • Tutors were extremely knowledgeable and friendly.

* IBS- DR Academy meets IndustryIBS- DR Academy meets Industry


Connect – Collaborate – Create The aim of this workshop is to provide a meeting ground for academic researchers, statisticians in the pharmaceutical industry, as well as BSc, MSc and PhD students with an interest in statistical research. Free admission!

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