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2017
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Data Science: Statistical Programming with R

Organizing institution
Utrecht University, Faculty of Social and Behavioural Sciences (UU)
Course code
S24
Course fee (incl. housing)
€ 800
Level
Master level

R is rapidly becoming the standard platform for data analysis, and is able to perform an enormous range of statistical procedures not available in other statistical programs, such as SPSS. This course offers an elaborate introduction into statistical programming in R. Students learn to operate R, make high quality graphics, fit, assess and interpret a variety of statistical models and do basic statistical programming. The statistical programming in this course covers plotting, regression models for linear, dichotomous, ordinal and multivariate data, multilevel data, repeated measures, and basic bootstrapping and Monte Carlo simulation techniques.

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NOTE: this course is fully booked! New applicants will be placed on a waiting list.

R is rapidly becoming the standard platform for data analysis and has a number of advantages over other statistical software packages. A wide community of users contribute to R, enabling it to cover an enormous amount of statistical procedures, including many that are not covered in any other statistical program. Furthermore, it is highly flexible for programming purposes, for example when manipulating data or creating professional plots. However, R lacks standard menus, as in SPSS for example, from which to choose what statistical test to perform or which graph to create. As a consequence, R is more challenging to master. Therefore, this course offers an elaborate introduction into statistical programming in R. Students learn to operate R, make plots, fit, assess and interpret a variety of statistical models and do basic statistical programming. The topics in this course include regression models for linear, dichotomous, ordinal and multivariate data, and some basic bootstrapping and Monte Carlo simulation techniques.

The course deals with the following topics:
1. An introduction to the R environment.
2. Basic programming skills: data generation, manipulation, summaries and plotting.
3. Fitting linear models: regression and ANOVA.
4. Fitting generalized linear models (GLM): logistic and ordinal regression.
5. Fitting multivariate models: PCA, MANOVA, discriminant analysis and Repeated Measures.
6. Bootstrapping and Monte Carlo simulation.

Prerequisites:
Participants are requested to bring their own laptop for lab meetings.

This course is part of three courses in the Summer School Data Science specialization taught by UU’s department of Methodology & Statistics. Please see here [link] for more information about the full specialization. This course can also be taken separately.

Summer School Data Science specialization:
Data Science: Statistical Programming with R (S24)
Data Science: Multiple Imputation in Practice (S28)
Data Science: Data Analysis and Visualization (S31)

Upon completing all three courses in the specialization, students can obtain a certificate. Each course may also be taken separately.

Tags: statistical programming, r, graphics, multivariate data analysis, analyzing data, data manipulation, data generation, linear models, generalized linear models, repeated measures

» Download the day-to-day programme (PDF)

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COURSE LEADER

Gerko Vink

LECTURERS

Gerko Vink, Jolien Cremers

TARGET GROUP

Applied researchers and (master) students who already use statistical software and would like to learn to use, or improve their usage of the flexible R-environment. Understanding of basic statistical procedures such as t-tests, (M)AN(C)OVA, and regression is required.

Participants from a variety of fields, including sociology, psychology, education, human development, marketing, business, biology, medicine, political science, and communication sciences, will benefit from the course.

After registration we will ask you to briefly describe your statistical programming experience (none required) as well as your expectations from this course.

A maximum of 60 participants will be allowed in this course.

COURSE AIM

The course teaches students the necessary skills to understand how R works, and how to use R for a variety of statistical analysis of data in the behavioural and social sciences.

The skills addressed in this practical are:
• working with the R environment.
• using R-functions for data generation, manipulation and summaries.
• making high-quality plots.
• fitting and interpreting a variety of statistical models.
• Programming of simple bootstraps and Monte Carlo simulations.

STUDY LOAD

Five full days.

FEE

• € 800 - Course + course materials + housing
• € 600 - Course + course materials

Tuition for PhD candidates from the Faculty of Social and Behavioural Sciences will be funded by the Graduate School of Social and Behavioural Sciences.

NOTE: this course is fully booked! New applicants will be placed on a waiting list.

DISCOUNTS AND COMBINATIONS
» Overview of all available discounts

SCHOLARSHIPS

Utrecht Summer School does not offer scholarships for this course.

MORE INFORMATION

Marianne Geelhoed
E-mail: ms.graduate.program@uu.nl

» Contact Utrecht Summer School

REGISTRATION

Deadline for registration: 31 July 2017

Application closed