Statistical Analysis with R

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This is a two day workshop (March 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity.

  • How to Obtain R
  • Help Tools
  • Importing / Exporting Data
  • Data Management
  • Descriptive and Exploratory Statistics
  • Common Statistical Analyses (t-test, Regression Modeling, ANOVA, etc.)
  • Graphics
  • Creating Functions

 

Statistical Analysis with R

By |

This is a two day workshop (March 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity.

  • How to Obtain R
  • Help Tools
  • Importing / Exporting Data
  • Data Management
  • Descriptive and Exploratory Statistics
  • Common Statistical Analyses (t-test, Regression Modeling, ANOVA, etc.)
  • Graphics
  • Creating Functions

 

The 2nd Annual Data for Public Good Symposium

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Do you have experience in working alongside community partners in data analysis or program evaluation? Do you want to connect with others who are using their skills for public good? National efforts from organizations such as DataKind, Data Science for Social Good, and Statistics without Borders have been expanding in recent years as more individuals recognize their potential to impact social change.  Great things can happen when individuals are empowered to dedicate time, resources, and knowledge to the pursuit of public good. Whether we work in the foreground or the background, we can all contribute to improving the lives of those around us.

Statistics in the Community (STATCOM), in collaboration with the Center for Education Design, Evaluation, and Research (CEDER) and the Community Technical Assistance Collaborative (CTAC), invite you to attend the 2nd Annual Data for Public Good Symposium hosted by the Michigan Institute for Data Science (MIDAS). The symposium will take place on Tuesday, February 19, 2019 and will showcase the many research efforts and community-based partnerships at U-M that focus on improving humanity by using data for public good. If you are interested in attending, please register here.

Schedule:
10:00 – 10:30: Registration and Networking
10:30 – 11:30: Presentations

  • Partners for Preschool: The Added Value of Learning Activities at Home During the Preschool Year, Amanda Ketner, School of Education
  • University-Community Partnership to Support Ambitious STEM Teaching: Leveraging University of Michigan expertise in education, research, and evaluation to support innovative, interactive teaching across the S.E. Michigan region and beyond, C. S. Hearn, Center for Education Design, Evaluation, and Research (CEDER)
  • Open Data Flint, Stage II, Kaneesha Wallace, MICHR
  • Research-Practice Partnerships at the Youth Policy Lab, A Foster, ISR Youth Policy Lab and School of Education
  • The LOOP Estimator: Adjusting for Covariates in Randomized Experiments, Edward Wu, Statistics

11:30 – 01:00: Lunch/Poster Session
01:00 – 02:00: Presentations

  • Barrier Busters: Unconditional Cash Transfers as a Strategy to Promote Economic Self-Sufficiency, Elise Gahan, School of Public Health
  • Implementing Trauma-Informed Care at University Libraries, Monte-Angel Richardson, School of Social Work
  • Why did the global crude oil price start to rise again after 2016?, Shin Heuk Kang, Economics
  • Poverty and economic hardship in Michigan communities: Data from the Michigan Public Policy Survey (MPPS), Natalie Fitzpatrick, Center for Local, State, and Urban Policy
  • Understanding Networks of Influence on U.S. Congressional Members’ Public Personae on Twitter, Angela Schopke, Chris Bredernitz, Caroline Hodge, School of Information

02:00 – 02:30: UM Student Organization Presentations
02:30 – 04:30: Workshop Debrief & Closing

About the Organizers: STATCOM is a community outreach organization offering the expertise of statistics graduate students – free of charge – to nonprofit governmental and community organizations. CTAC is a community-university partnership convened to serve a universal need identified by community partners around data and evaluation. CEDER is a School of Education center devoted exclusively to offering high-quality designs, evaluations, and research on teaching, learning, leadership, and policy at multiple levels of education. This symposium is part of our effort to bring together university organizations that promote similar ideals and individuals whose research provides a service for the greater good.

Questions: Please contact salernos@umich.edu.

 

 

 

 

 

Statistical Analysis with R

By |

This is a two day workshop (February 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity.

  • How to Obtain R
  • Help Tools
  • Importing / Exporting Data
  • Data Management
  • Descriptive and Exploratory Statistics
  • Common Statistical Analyses (t-test, Regression Modeling, ANOVA, etc.)
  • Graphics
  • Creating Functions

 

Statistical Analysis with R

By |

This is a two day workshop (February 4 and 5) in R which  is a free and open source environment for data analysis and statistical computing.  While R contains many built-in statistical procedures, a powerful feature of R is the facility for users to extend these procedures to suit their own needs.  Excellent graphing capability is another reason R is gaining wide popularity.

  • How to Obtain R
  • Help Tools
  • Importing / Exporting Data
  • Data Management
  • Descriptive and Exploratory Statistics
  • Common Statistical Analyses (t-test, Regression Modeling, ANOVA, etc.)
  • Graphics
  • Creating Functions

 

Statistics: A Review

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A one-day, intensive review of common statistical methods of design, measurement analysis and presentation of scientific investigations.  The workshop is designed for any scholar engaged in quantitative research. Statistics: A Review discusses answers to the following questions:

  • What should we measure?
  • What are the main design types; what are the comparative advantages of each?
  • How are the sample sizes determined?
  • What are the appropriate inference procedures?
  • What do standard error, p-value and confidence level mean?
  • What are some dangers we need to avoid?
  • How should we display our results?
  • What are the statistical software options?

 

Biostatistics Seminar: Kenneth Lange, Professor of Biomathematics, Human Genetics and Statistics, UCLA: “Next Generation Statistical Genetics”

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This talk will discuss how modern data mining techniques can be imported into statistical genetics. Most relevant models now invoke high-dimensional optimization. Penalization and set projection give sparsity. Separation of variables gives parallelization. Time permitting, these ideas will be illustrated by several examples: estimation of ethnic ancestry, genotype imputation via matrix completion, conversion of imputed genotypes into haplotypes, matrix completion discriminant analysis, estimation in the linear mixed model, iterative hard thresholding in GWAS, and sparse principal components analysis.

MIDAS Seminar: Susan Murphy, U-M professor of Statistics and Psychiatry, on “Learning Treatment Policies in Mobile Health” — Jan. 8

By | Educational, Events

As part of the MIDAS Seminar Series, U-M Professor of Statistics and Psychiatry Susan Murphy will present a talk titled “Learning Treatment Policies in Mobile Health.”

Time/Date: 4 p.m., Friday, Jan. 8, 2016

Location: Forum Hall, Palmer Commons, 100 Washtenaw Ave.

Abstract: We describe a sequence of steps that facilitate effective learning of treatment policies in mobile health. These include a clinical trial with associated sample size calculator and data analytic methods. An off-policy Actor-Critic algorithm is developed for learning a treatment policy from this clinical trial data.

Bio: Susan Murphy is the H.E. Robbins Distinguished University Professor of Statistics & Professor of Psychiatry and a Research Professor at the Institute for Social Research. Her research focuses on improving sequential, individualized, decision making in health, in particular on clinical trial design and data analysis to inform the development of mobile health treatment policies.  Susan is a Fellow of the Institute of Mathematical Statistics, a Fellow of the College on Problems in Drug Dependence, a former editor of the Annals of Statistics, a member of the US National Academy of Medicine and a 2013 MacArthur Fellow.

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