Statistics

This is the first half of a semester-long class which introduces elementary statistical approaches in social science. The course covers basics of statistical inference and programming skills that can be used to answer questions in real world social phenomena, policy analysis, and academic research. Students derive and explain key measures of elementary statistical analysis. They conduct elementary statistical analysis using a programming language and collect datasets and conduct research using skills introduced. Assessment: class participation, exam.

This course offers students an introduction to object-oriented and procedural programming, using Python. Most models and examples are taken from Economics, Management, and Finance. The course discusses topics including primitive types and class types; recursion and functions such as procedures and fruitful functions; basic statements such as assignment, if-statements, loops, blocks, and function calls; objects and classes including subclasses, inheritance, and overriding; sequences and dictionaries; testing and debugging; program development, stepwise refinement (top-down design), and object-oriented design; databases; examples of full featured applications; and programming style considerations. The course consists of lectures, exercises, case studies, and individual and group assignments. The course requires students to have completed an introductory course on programming as a prerequisite.