Ceci n’est pas une %>%: Exploring Your Data with R

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R is an extremely powerful tool for data modeling, visualization, and general programming.  In many practical applications of statistics, the vast majority of time is spent preparing the data for eventual analysis. However, this also where many practitioners who use R often have relatively little training.  In recent years, a variety of packages have become available to make data wrangling, summarizing, generation and other common operations more straightforward, and easier to read for future use (e.g. via piping and clearer syntax).  In addition, some newer visualization packages work these approaches, allowing one to go quite seamlessly from raw data to interactive graphics.  This workshop will introduce participants to a handful of tools that can make their data exploration and analytical flow more streamlined and reproducible.

Statistical Analysis with R

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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 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

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

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

Engaging the Web with R

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Well known for its statistical capabilities, R can also be used for web-scraping, connecting with websites via APIs, html documents and presentations, interactive visualizations, dashboards, and even building entire, possibly interactive, websites.  This talk will provide an overview of web-based use of aàR. Conceptual introductions, package synopses, and small demonstrations will be presented.

Numerical computing in Python with Numpy

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Numpy is the powerful and widely-used array and linear algebra library for Python. We will cover the basics of array manipulation using Numpy, and cover selected more advanced topics including broadcasting and type conversion. The workshop assumes an intermediate level of Python programming, but no prior knowledge of numpy is required.

Basic Go programming with data (part 1)

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Go (golang.org) is an open-source programming language that can yield very high performance for large-scale data processing applications.  This workshop is an introduction to programming in Go with data.  Participants should have programming experience in some language, but prior exposure to Go is not expected.  We will cover writing a basic Go program, using the Go tools, Go data structures, and reading files.

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.

Statistical Analysis with R

By | | No Comments

This is a two day workshop (February 5 and 6) 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