Syllabus

Title
0624 Statistics for Economics and Social Sciences with R
Instructors
PD Dr. Thomas Rusch, Bakk.
Contact details
thomas.rusch@wu.ac.at
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/15/22 to 09/21/22
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Statistics for Economics and Social Sciences
Dates
Day Date Time Room
Thursday 10/06/22 04:00 PM - 06:30 PM LC.-1.038
Thursday 10/13/22 04:00 PM - 06:30 PM LC.-1.038
Thursday 10/20/22 04:00 PM - 06:30 PM LC.-1.038
Thursday 10/27/22 04:00 PM - 06:30 PM LC.-1.038
Thursday 11/03/22 04:00 PM - 06:30 PM LC.-1.038
Thursday 11/10/22 04:00 PM - 06:30 PM LC.-1.038
Thursday 11/17/22 04:00 PM - 06:30 PM LC.2.064 PC Raum
Thursday 11/24/22 04:00 PM - 06:30 PM LC.-1.038
Thursday 12/01/22 04:00 PM - 06:30 PM TC.-1.61
Thursday 12/15/22 04:00 PM - 06:30 PM TC.-1.61

On this page:

to top
Contents

 

  • Introduction to R
  • Descriptive statistics and visualizations:
  1. Measures of location (average, median, ...)
  2. Measures of dispersion (variance, standard deviation, ...)
  3. Histogram, density plot
  4. Bar plot, spine plot, mosaic plot
  5. Box plot
  6. Scatter plot
  7. Association (correlation, Pearson & Spearman)

 

  • Statistical inference:
  1. Chi-squared tests
  2. Confidence intervals
  3. Odds ratios
  4. (Binary) logistic regression
  5. Dummy variables for categorical predictors
  6. (Univariate) simple and multiple linear regression
  7. T-test and simple analysis of variance
  8. Mann-Whitney U-Test and Kruskal-Wallis H test
  9. Analysis of variance (ANOVA)

 

to top
Learning outcomes
In this course, you will learn basic statistical techniques widely used in economics and socio-economics. You will get acquainted with the statistical software package R. You will learn via practical examples how to carry out statistical analysis using the software R.
to top
Attendance requirements

For this course, attendance is mandatory. Students must not miss more than a maximum of 20% of course time (regardless of whether excused or not excused).

to top
Teaching/learning method(s)

    Presence units take place weekly. Prior to each unit, students work through each week's topics in advance by self-studying with the literature and readings provided, supported with screencasts on the usage of R for the week's topics. In presence units, the week's topics will be revisited in a quiz structure, open questions about the material will be discussed and the practical application using the statistical software package R is practiced based on exercises. There will be homework assignments, which need to be submitted online. A final exam will take place as an online exam after the last unit.

      to top
      Assessment
      • Active participation (including presentation) during the practical exercises (a maximum 8 bonus points can be obtained).
      • Homework (in groups): 10 exercises (50 points, each exercise is worth 5 points).
      • Quizzes with a total of 12 points. A maximum of 10 points will be scored.
      • Final exam (20 points).
      • Of the 80 total points, at least 70% must be achieved for a positive grade.
      • Grading key: 4 – (56 – 61 p.), 3 – (62 – 67 p.), 2 – (68 – 73 p.), 1 – (74+ p.)
      to top
      Availability of lecturer(s)

      thomas.rusch@wu.ac.at

      Last edited: 2022-07-14



      Back