Syllabus

Title
4629 Statistics for Economics and Social Sciences with R
Instructors
Assoz.Prof PD Dr. Bettina Grün
Contact details
bettina.gruen@wu.ac.at
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/16/21 to 02/22/21
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Statistics for Economics and Social Sciences
Dates
Day Date Time Room
Wednesday 03/03/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 03/10/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 03/17/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 03/24/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 04/07/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 04/14/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 04/21/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 04/28/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 05/05/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 05/12/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 05/19/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 05/26/21 02:00 PM - 04:00 PM Online-Einheit
Wednesday 06/02/21 02:00 PM - 04:00 PM Online-Einheit

On this page:

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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)

 

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Learning outcomes
In this course, you will learn basic statistical techniques widely used in econometrics and economics. All presented methods are illustrated with practical examples to provide you with the tools to carry out statistical analysis using the software R.
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Attendance requirements

For this course participation is obligatory. Students are allowed to miss a maximum of 20% (no matter if excused or not excused).

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Teaching/learning method(s)

    The course takes place via Rotation Mode. The students are divided into 2 groups. Each group only comes to the campus / attends the online units for half of the course dates. The relevant dates for the respective group will be announced.

    The theoretical basics and the application using the statistical software package R are repeated or worked out in advance by the students in self-study using the literature and videos provided. In the presence units the content is discussed and practical exercises are performed.

    The homework exercises are submitted online. The final exam takes place online in the last unit for both groups simultaneously.

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      Assessment
      • Active participation in the computer exercises in the presence units (8 bonus points for participation possible).
      • Homework: 10 exercises (50 points, each exercise is worth 5 points).
      • Quizzes in the presence units 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.
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      Availability of lecturer(s)

      bettina.gruen@wu.ac.at

      Last edited: 2021-01-29



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