Location:

Main Campus

Session:

2025 Trimestre d'hiver | Winter Term

Faculty:

Faculté des sciences sociales / Faculty of Social Sciences

Unit:

School of International Development and Global Studies_PT

Course Title:

Quantitative Reasoning for International Development

Course Code:

DVM 3170

Section:

A00

Course Description:

DVM 3170 Quantitative Reasoning for International Development (3 units)

Introduction to the use of data and basic statistical analysis in international development. Overview of data, data sources and basic quantitative measures of development: ratios, percentages, index numbers (e.g. human development index and its variants); available measures of national income, inequality, poverty; and basic demographic, health, educational and environmental indicators. Introduction to descriptive statistics, basic inferential statistics, and basic data visualization techniques (mainly using Excel).

Course Component: Lecture

Posting limited to:

Professeur à temps-partiel étudiant / Student Part-Time Professor

Date Posted:

October 31, 2024

Applications must be received BEFORE:

December 01, 2024

Expected Enrolment:

74

Approval date:

October 31, 2024

Number of credits:

3

Work Hours:

39

Course type:

C

Posting type:

Régulier / Regular

Language of instruction:

Anglais | English

Competence in second language:

Passive

Course Schedule:

Lundi | Monday 8:30-10:00 Jeudi | Thursday 10:00-11:30 -

Requirements:

Ph.D. completed or in progress, or equivalent experience in the field of social sciences and International Development; publications and works that demonstrate an understanding of basic statistical analysis techniques in Excel, as well as familiarity with different data sources in development (both national level and survey data) and debates over different approaches to measuring national income, poverty, inequality and other dimensions of development.  More advanced capabilities in statistical coding or analysis (such as familiarity with GIS or open source software such as R or Python) are an advantage and may be applied to help develop specific examples (e.g. around data visualization methods). Evidence of teaching experience and/or publications demonstrating the of these tools and competencies is an asset.

Additional Information and/or Comments:

An acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience. If you are invited to continue the selection process, please notify us of any adaptive measures you might require. Information you send us will be handled respectfully and in complete confidence. Employees are required under provincial law to successfully complete all mandatory legislated training. The list of training may be modified by provincial law.

The hiring process will be governed by the current APTPUO collective agreements; you can click here for the main unit, here for the OLBI unit, or here for the Toronto/Windsor unit to find out more.

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