Research data has grown to unprecedented sizes making local storage, efficient data analysis and long-term archiving a significant challenge. In this session we will introduce the stages of the research data lifecycle. We will discuss how data management plays a role at key stages of the data lifecycle. Finally, we will review tools and resources…
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data analysis
Introduction to Survival Analysis in R
Survival analysis models time-to-event outcomes. This workshop introduces usage of the survival package in R for some of the most commonly used survival methods. Topics include data setup, Kaplan-Meier estimates and curves, log-rank tests, fitting the Cox proportional hazards model, assessing the proportional hazards assumption, and modeling time-varying covariates. Experience in both survival analysis and…
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Boosting Python for High Performance Data Analytics (1) Interpreter War
While Python becomes the most popular programming language since 2019, data scientists often have a few common complaints about its slow speed and the limited capabilities of handling the big data scenarios. In this workshop series, we will present an extensive discussion on how to improve the performance of Python in data science by looking…
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Scientific Visualization with Paraview
Paraview is an open-source cross-platform program for interactive scientific visualization. Paraview can run as a stand-alone visualization tool, as well as in a client-server fashion for remote visualization. In this tutorial, we will explore the visualization pipeline and basic features in Paraview. We will show how to prepare data files from scratch. We will demonstrate…
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Retiring Statistical Significance: Interpreting and Reporting P – Values and Confidence Intervals Without Significance Testing
Please REGISTER in advance here. Workshop will be conducted in Zoom in PST time. Invites are sent out the day before the workshop. The misuse of null hypothesis significance testing (NHST) and p-value thresholds, together with selective reporting of statistically significant results, have produced an inundation of overstated conclusions and unreplicable results in scientific…
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Census Data Analysis and Mapping with Python
Please REGISTER in advance here. Workshop will be conducted in Zoom in PST time. Invites are sent out the day before the workshop. In this hands on workshop, you will be provided with a Jupyter Notebook workspace to import census data, explore, clean, and prepare the data for analysis using python. You will also learn…
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Jupyter Advanced Topics
This short class will illustrate several powerful tools and features that can enhance one’s experience with Jupyter notebooks. The interactive demonstrations will include a brief overview of plotting tools and magics, followed by demonstrations of how to make interactive widgets for interactive visualizations and dashboards and how to generate analysis pipelines and reports. Basic familiarity…
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Using SQL with Python for Data Analysis
SQL is a standard language designed to query and extract data from tables stored in a database. Python, on the other hand, has well-known libraries specially designed for data analysis and manipulation. This course will introduce attendees to the basics of SQL, relational database management systems, and options for integrating these with Python for data…
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