Data Analysis in R
Beschrijving
Something for you: the VU Graduate Winter School!
VU Graduate Winter School offers interactive one-week courses for Master students, PhD candidates and professionals from 11-15 January 2021. Our courses are small-scale and full time, you are given access to exclusive content and you will be personally guided by the lecturer(s) to maximize your learning.
Why should you join?
-Equip
yourself with a new set of key skills
-Become an expert in a particular field
-Broaden your professional network and expand your CV
Your stepping stone. Join us online!
Course will take place online from 10-14 January 2022. Full time attendance is required.
With the increasing use of statistical languages like R in data analysis, now is the time to get to grips with them!
In this course, we’ll start out with the data structures present in R (vectors, matrices, lists, data frames) and how to perform simple operations with them. Then, we’ll learn how to import the data in R and how to save the output of your analyses. We’ll also go over logical operations and key elements to navigate through datasets.
Once the students have familiarised themselves with these basic concepts, we will move on to more advanced programming concepts such as understanding and writin…
Veelgestelde vragen
Er zijn nog geen veelgestelde vragen over dit product. Als je een vraag hebt, neem dan contact op met onze klantenservice.
Something for you: the VU Graduate Winter School!
VU Graduate Winter School offers interactive one-week courses for Master students, PhD candidates and professionals from 11-15 January 2021. Our courses are small-scale and full time, you are given access to exclusive content and you will be personally guided by the lecturer(s) to maximize your learning.
Why should you join?
-Equip
yourself with a new set of key skills
-Become an expert in a particular field
-Broaden your professional network and expand your CV
Your stepping stone. Join us online!
Course will take place online from 10-14 January 2022. Full time attendance is required.
With the increasing use of statistical languages like R in data
analysis, now is the time to get to grips with them!
In this course, we’ll start out with the data structures present in
R (vectors, matrices, lists, data frames) and how to perform simple
operations with them. Then, we’ll learn how to import the data in R
and how to save the output of your analyses. We’ll also go over
logical operations and key elements to navigate through
datasets.
Once the students have familiarised themselves with these basic
concepts, we will move on to more advanced programming concepts
such as understanding and writing functions, string operations, and
list operations.
Besides these technical skills, students will learn how to compute
descriptive statistics and how to produce a visual representation
of data in R. For example, we will touch upon the linear regression
model, which is a widely used model with two primary purposes:
modelling relationships among the data and predicting future
observations. After that, we’ll expand the linear model to the
generalised linear framework in order to analyse non-normally
distributed variables. All the statistical theory will be covered
first, and then we’ll see practical examples of R in action so that
students can learn the methods through first-hand application.
Each day will consist of lectures with examples and exercises,
which the students can use as opportunities to apply what they have
learned. The focus of the exercises and end-of-course assignment is
the coding in R and how to apply and interpret generalised linear
regression models.
Who should join?
Open to Bachelor and Master’s students, PhD candidates, and
professionals from all disciplines.
Students and professionals with a basic knowledge of statistics (an
undergraduate course is a prerequisite) who are interested in
learning the basics and some more advanced skills of R and applying
them to solve their data analysis problems.
Final year Bachelor, Master’s students, PhD candidates, and
professionals are welcome to apply.
If you have doubts about your eligibility for the course, please
contact us via graduatewinterschool@vu.nl.
Learning objectives
Students will develop their programming skills in R and
statistically evaluate quantitative data sources, conduct various
statistical tests, and analyse data using generalised linear
frameworks.
Upon completion of the course, students will be familiar with the
various popular R packages, have the tools to write their own
functions, and know how to use attractive plots to present their
data.
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