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© 2010 – 2016 eoda GmbHMartin Schneider
I have to teach R
Experiences in the teaching of R
eRum 2016
Martin Schneider
Data Scientist
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
About eoda
Interdisciplinary Team
Statisticians | Engineers | Economists | Sociologist | …
Based in Kassel - Germany
Data Science Consulting, Training, Support,
Software and Analytic Services with a focus on R
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Teaching R since
2013
Motivation and Qualification
Number of courses
0025
Course Participants
0125I
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Motivation and Qualification
Teaching R since
2010
Number of courses
0150
Course Participants
1000WE
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
BusinessAcademics
Wide differing Background
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
Business
Wide differing Priorities
We want to do everything perfect, every
prerequisite for analysis has to be met.
Academics
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
BusinessAcademics
Wide differing Priorities
How much money can we save?
We want to see results
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
? Excel
Wide differing preknowledge in Analytic Tools
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
Wide differing Statistical Background
NONECOOL
NONE
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
Wide differing Statistical Background
A LOT
COOL
A LOT
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
Wide differing Statistical Background
SOME
Dangerous
half knowledge
SOME
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
Wide differing Personal Goals
I want to start with
statistical analysis
I‘m already using SPSS
but I heard a lot of R so I
wanted to take a look
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
For who?
BusinessAcademics
Wide differing Personal Goals?
I want to start with
statistical analysis
I‘m already using SPSS
but I heard a lot of R so I
wanted to take a look
I‘m already using Excel and
everything is working fine
but my boss said…
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Package updates
Recurring Problems
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Recurring Problems
diverse classes
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Recurring Problems
In R there are usually lots of different ways
to solve a problem
We did this already this way, why
are we doing it another way?
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Recurring Problems
Steep learning curve
What does this Error Message
mean? I‘m having problems
solving this exercise.
This is in SPSS much easier
I will never
under-
stand R
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Recurring Problems
Technical hurdles
I´m missing the permission
to install packages
I have to use external
software
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Writing code
in front
Excersises
Usual Course
Small Part of Presentation
Presentation
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Usual Course
Writing code in front
cars <- read.csv(file = "Data/carsMO.csv", stringsAsFactors = FALSE)
select(cars, Manufacturer, Modell, contains("sales", ignore.case = TRUE))
select(cars, Manufacturer, Modell, Sales:Sales_grouped)
mutate(cars, weight_to_hp = HP/Weight) %>%
filter(weight_to_hp > mean(weight_to_hp, na.rm = TRUE)) %>%
arrange(desc(weight_to_hp))%>%
select(Modell, weight_to_hp)
abs_loss_data <- cars %>%
mutate(absolute_loss = Purchase_price - Resaleprice) %>%
arrange(desc(absolute_loss)) %>%
select(Modell, contains("price"), absolute_loss) %>%
filter(!is.na(absolute_loss))
Slowdown
when writing
code
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Usual Course
Excercises
Don‘t make it
to difficult
Now that you know, what a list is
please load this dataset, apply a
cluster analysis on it and create
an appealing report
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Usual Course
Excercises
Don‘t make it
to easy
Now that you know how to
extract the first element from a
list, please extract the second
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Example Data
Iris
NYC Taxi Data
MT Cars
Usual Course
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
Wishfull Thinking
workshop element attached to the course
smaller chunks of training sessions
© 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de
@eodaGmbH
@eodaGmbH eodaGmbH
blog.eoda.de
eoda GmbH
Universitätsplatz 12
34127 Kassel - Germany
www.eoda.de/en
info@eoda.de
+49 561 202724-40
The Data Science Specialists.

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Aargh! I have to teach R (Experiences in the teaching of R)

  • 1. © 2010 – 2016 eoda GmbHMartin Schneider I have to teach R Experiences in the teaching of R eRum 2016 Martin Schneider Data Scientist
  • 2. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de About eoda Interdisciplinary Team Statisticians | Engineers | Economists | Sociologist | … Based in Kassel - Germany Data Science Consulting, Training, Support, Software and Analytic Services with a focus on R
  • 3. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Teaching R since 2013 Motivation and Qualification Number of courses 0025 Course Participants 0125I
  • 4. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Motivation and Qualification Teaching R since 2010 Number of courses 0150 Course Participants 1000WE
  • 5. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? BusinessAcademics Wide differing Background
  • 6. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? Business Wide differing Priorities We want to do everything perfect, every prerequisite for analysis has to be met. Academics
  • 7. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? BusinessAcademics Wide differing Priorities How much money can we save? We want to see results
  • 8. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? ? Excel Wide differing preknowledge in Analytic Tools
  • 9. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? Wide differing Statistical Background NONECOOL NONE
  • 10. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? Wide differing Statistical Background A LOT COOL A LOT
  • 11. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? Wide differing Statistical Background SOME Dangerous half knowledge SOME
  • 12. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? Wide differing Personal Goals I want to start with statistical analysis I‘m already using SPSS but I heard a lot of R so I wanted to take a look
  • 13. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de For who? BusinessAcademics Wide differing Personal Goals? I want to start with statistical analysis I‘m already using SPSS but I heard a lot of R so I wanted to take a look I‘m already using Excel and everything is working fine but my boss said…
  • 14. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Package updates Recurring Problems
  • 15. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Recurring Problems diverse classes
  • 16. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Recurring Problems In R there are usually lots of different ways to solve a problem We did this already this way, why are we doing it another way?
  • 17. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Recurring Problems Steep learning curve What does this Error Message mean? I‘m having problems solving this exercise. This is in SPSS much easier I will never under- stand R
  • 18. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Recurring Problems Technical hurdles I´m missing the permission to install packages I have to use external software
  • 19. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Writing code in front Excersises Usual Course Small Part of Presentation Presentation
  • 20. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Usual Course Writing code in front cars <- read.csv(file = "Data/carsMO.csv", stringsAsFactors = FALSE) select(cars, Manufacturer, Modell, contains("sales", ignore.case = TRUE)) select(cars, Manufacturer, Modell, Sales:Sales_grouped) mutate(cars, weight_to_hp = HP/Weight) %>% filter(weight_to_hp > mean(weight_to_hp, na.rm = TRUE)) %>% arrange(desc(weight_to_hp))%>% select(Modell, weight_to_hp) abs_loss_data <- cars %>% mutate(absolute_loss = Purchase_price - Resaleprice) %>% arrange(desc(absolute_loss)) %>% select(Modell, contains("price"), absolute_loss) %>% filter(!is.na(absolute_loss)) Slowdown when writing code
  • 21. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Usual Course Excercises Don‘t make it to difficult Now that you know, what a list is please load this dataset, apply a cluster analysis on it and create an appealing report
  • 22. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Usual Course Excercises Don‘t make it to easy Now that you know how to extract the first element from a list, please extract the second
  • 23. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Example Data Iris NYC Taxi Data MT Cars Usual Course
  • 24. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de Wishfull Thinking workshop element attached to the course smaller chunks of training sessions
  • 25. © 2010 – 2016 eoda GmbHMartin Schneider www.eoda.de @eodaGmbH @eodaGmbH eodaGmbH blog.eoda.de eoda GmbH Universitätsplatz 12 34127 Kassel - Germany www.eoda.de/en info@eoda.de +49 561 202724-40 The Data Science Specialists.