Syllabus

Titel
4769 Statistics for Economics and Social Sciences with R
LV-Leiter/innen
Annalisa Cadonna, Ph.D.
Kontakt
  • LV-Typ
    PI
  • Semesterstunden
    2
  • Unterrichtssprache
    Englisch
Anmeldung
11.02.2019 bis 18.02.2019
Anmeldung über LPIS
Hinweise zur LV
Planpunkt(e) Bachelor
Termine
Wochentag Datum Uhrzeit Raum
Dienstag 05.03.2019 13:00 - 15:00 TC.-1.61
Dienstag 12.03.2019 13:00 - 15:00 LC.-1.038
Dienstag 19.03.2019 13:00 - 15:00 TC.-1.61
Dienstag 26.03.2019 13:00 - 15:00 LC.-1.038
Dienstag 02.04.2019 14:00 - 16:00 D2.-1.019 Workstation-Raum
Dienstag 09.04.2019 13:00 - 15:00 LC.-1.038
Dienstag 30.04.2019 13:00 - 15:00 LC.-1.038
Dienstag 07.05.2019 12:00 - 14:00 D2.-1.019 Workstation-Raum
Dienstag 14.05.2019 12:00 - 14:00 TC.-1.61
Dienstag 21.05.2019 13:00 - 15:00 LC.-1.038
Dienstag 28.05.2019 13:00 - 15:00 LC.-1.038
Dienstag 04.06.2019 13:00 - 15:00 LC.-1.038
Dienstag 18.06.2019 13:00 - 15:00 D2.-1.019 Workstation-Raum

Inhalte der LV

 

  • Introduction to R
  • Descriptive statistics and graphs:
  1. Measures of center(average, median, ...)
  2. Measures ofdispersion (variance, standard deviation, ...)
  3. Histogram, density plot
  4. Bar plot, spineplot, mosaic plot
  5. Box plot
  6. Scatterplot
  7. Association (correlation,Pearson & Spearman)

 

  • Statistical inference:
  1. Chi-squared tests
  2. Confidenceintervals
  3. Odds Ratios
  4. (Binary) logistic regression
  5. Dummyvariabels for categorial 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)

 

Lernergebnisse (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.

Regelung zur Anwesenheit

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

Lehr-/Lerndesign

    The course is held weekly. The subject is presented by the lecturer in theoretical units and illustrated with data sets. The performance of the students is assessed through various exercises and a test (see Assesment).

      Leistung(en) für eine Beurteilung

      • No more than 2 absences.
      • Quizzes: 5 best out 6  (10 points total, 2 points per quiz)
      • Homework: 10 exercises (50 points, each exercise is worth 5 points).
      • Multiple choice final exam  (20 points).
      • Of the 80 total points, at least 70% must be achieved for a positive score.
      • Active participation in the computer exercises (8 bonus points for cooperation possible).

      Erreichbarkeit des/der Vortragenden

      annalisa.cadonna@wu.ac.at

      Zuletzt bearbeitet: 13.02.2019



      Zurück