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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

 

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

 

Introduction to Survey Design: Data Collection, Questionnaire Design and Response Processes

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This lecture-format workshop will present an overview of available modes and methods of survey data collection as well as an introduction to the survey response process and implications for questionnaire design.  Participants will gain an appreciation of the tradeoffs inherent in survey design decisions and how design can affect data quality and survey errors. Topics will include: Survey errors, in particular measurement, coverage, and nonresponse error; what to consider when selecting a data collection method for a particular research question; Measurement (response) error and how to reduce it through question wording/format and questionnaire structure; the role of the interviewer and interviewer effects.

  • Survey errors, in particular measurement, coverage, and nonresponse error.
  • What to consider when selecting a data collection method for a particular research question.
  • Measurement (response) error and how to reduce it through question wording/format and questionnaire structure.
  • The role of the interviewer and interviewer effects.

Registration

To register for CSCAR workshops, call the CSCAR front desk at (734) 764-7828, or come to the office in person with payment (cash, check or a UM department shortcode):

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440
Email: cscar@umich.edu

ADDRESS

Consulting for Statistics, Computing and Analytics Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

Statistical Analysis with R

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This is a two day workshop (May 21 & 22) 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

Registration

To register for CSCAR Workshops, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM department shortcode:

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440

ADDRESS

Center for Statistical Consultation and Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

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?

Registration

To register for CSCAR Workshops, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM department shortcode:

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440

ADDRESS

Consulting for Statistics, Computing and Analytics Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

Statistical Analysis with R

By | | No Comments

This is a two day workshop 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

Registration

To register for CSCAR Workshops, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM department shortcode:

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440

ADDRESS

Center for Statistical Consultation and Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

Structural Equation Modeling II: Latent Variables

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This workshop will help participants develop skills in understanding and conducting latent variable models, and specifically from the perspective of structural equation modeling. After a conceptual overview, a broad view of matrix factorization techniques will be provided along with specific examples (e.g. PCA, ‘factor analysis’).  In addition, measurement error issues, reliability, and scale development will be discussed (e.g. ‘confirmatory’ factor analysis). Prerequisites: One should have a firm understanding of basic regression. R will be the program of choice, but nothing beyond very basic skill is assumed.  While this workshop can serve as a standalone session, it is required for SEM III: Structural Equation Modeling.

Registration

To register for CSCAR Workshops, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM department shortcode:

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440

ADDRESS

Consulting for Statistics, Computing and Analytics Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

Structural Equation Modeling I: Graphical Models

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This workshop will help participants develop skills in understanding graphical models, and specifically from the perspective of structural equation modeling (SEM). After a general overview of concepts, regression approaches with observed variables will be demonstrated (path analysis), as well as mediation models in particular.  Alternative approaches and non-SEM settings will also be discussed. Prerequisites: One should have a firm understanding of basic regression estimation techniques.  R will be the program of choice, but nothing beyond very basic skill is assumed.

Registration

To register for CSCAR Workshops, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM department shortcode:

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440

ADDRESS

Consulting for Statistics, Computing and Analytics Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

Basic Go programming with data (part 2)

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This workshop continues our discussion of using the Go language for data processing.  We will introduce concurrent programming in Go, discuss data serialization, and talk through several case studies.