SISS - EMbeDS-education/ComputingDataAnalysisModeling20232024 GitHub Wiki

This is the home page of the course SISS: Statistical Inference for the Social Sciences.

Please use the right-sidebar to navigate the pages of interest.

Instructors:

Language: Italian

Duration: 20h, TBD, Fall, 2023.

Description: This course will provide a review of the basic elements of statistical inference as applied to realistic problems and real data -- integrating the presentation of statistical theory with practice in data processing and analysis using the STATA Software. An introduction to the R software will be also provided. The content will include topics selected from the following areas:

  • Planning a quantitative research study & descriptive statistics
  • Point estimates, confidence intervals and hypothesis testing
  • Linear regression
  • Introduction to the Generalized Linear Model with binary outcome

Compared to traditional courses on Statistics, this course will provide a practically oriented approach to learning with a focus on interpretation of statistical results.

Materials: Statistics / David Freedman Robert Pisani (et Al.), a copy is available at the Sant’Anna library.
Lohr, S. L. (2021). Sampling: design and analysis. Chapman and Hall/CRC.
Slides and other support materials for this course will be made available through this repository; see links in the right-sidebar.

Attendance: We expect lectures and Practicum sessions to be held in presence. Room: Via Maffi, Aula L'EMbeDS.

Prerequisites: A working knowledge of probability and descriptive statistics.

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