Data Analytics for You - Data Analysis

Please send an email to Library.events@miami.edu or call 305-284-4026.

University of Miami Libraries

This series offered exclusively to University of Miami students, faculty, and staff who are undertaking research in any discipline.

<p><strong>Please note registration for each workshop will close an hour before each workshop. 
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Workshops will take place via Zoom. 
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<h3>Introduction to Python for Data Analysis with <a href="https://sp.library.miami.edu/subjects/staff/criopelle" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Cameron Riopelle</a></h3><p><strong>Tuesday, March 8, 2022 at 2 p.m. to 4 p.m. (EST)</strong></p><p>This workshop is an introduction to the programming language Python using the Jupyter environment. The basics of using Python for data analytis are covered, including using Jupyter, importing data, using popular libraries such as pandas and NumPy, data visualization, and saving/exporting.</p><p></p><h3>Introduction to Nvivo with <a href="https://sp.library.miami.edu/subjects/staff/criopelle" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Cameron Riopelle</a></h3><p><strong>Wednesday, March 9, 2022 at 2 p.m. to 4 p.m. (EST)</strong></p><p>This workshop is an introduction to using the software program NVivo to conduct qualitative research, including the NVivo environment, coding, analysis, visualization, and generating reports.</p><p></p><h3>Introduction to R for Data Analysis with <a href="https://sp.library.miami.edu/subjects/staff/jaq32" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Jorge Quintela</a></h3><p><strong>Thursday, March 10, 2022 at 2 p.m. to 4 p.m. (EST)</strong></p><p>Designed for new and intermediate R and R Studio users. It provides an introduction to the R software program, including its programming language, software environment, importing data, descriptive statistics, transforming variables, selecting and splitting data, exploratory tests, and visualization, common statistical methods in R such as means comparisons, ANOVA, linear regression, and basic visualization<strong>.</strong></p><p></p><h3>Intermediate R with <a href="https://sp.library.miami.edu/subjects/staff/criopelle" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Cameron Riopelle</a></h3><p><strong>Tuesday, March 29, 2022 at 2 p.m. to 4 p.m. (EST)</strong></p><p>Designed for intermediate R and R Studio users. It covers common statistical methods in R such as means comparisons, ANOVA, linear regression, and basic visualization.</p><h3></h3><h3>Introduction to SPSS for Data Analysis with <a href="https://sp.library.miami.edu/subjects/staff/jaq32" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Jorge Quintela</a></h3><p><strong>Thursday, March 31, 2022 at 2 p.m. to 4 p.m. (EST)</strong></p><p>Designed for new SPSS users. It provides an introduction to the SPSS software program, including its software environment, importing data, descriptive statistics, transforming variables, selecting and splitting data, and visualization.</p><p></p><h3>Intermediate SPSS with <a href="https://sp.library.miami.edu/subjects/staff/criopelle" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Cameron Riopelle</a></h3><p><strong>Monday, April 11, 2022 at 2 p.m. to 4 p.m. (EST)</strong></p><p>Designed for intermediate SPSS users. It covers common statistical methods in SPSS such as means comparisons, ANOVA, linear regression, and logistic regression models.</p><p></p><h3>Introduction to SAS Studio with <a href="https://sp.library.miami.edu/subjects/staff/criopelle" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Cameron Riopelle</a></h3><p><strong>Tuesday, April 19, 2022 at 1 p.m. to 3 p.m. (EST)</strong></p><p>Introduction to SAS Studio is an introduction to the SAS Studio environment for data analytics, including importing data, libraries, descriptive statistics, bivariate statistics, visualization, means comparison tests, and linear regression. </p><p></p><p></p>

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Data Analytics for You - Data Analysis

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