Essex Summer Research Course at Waseda University

Location
WASEDA University
Tokyo
Japan
Date
End Date

Waseda University is a large, private university with a main campus located in Shinjuku, Tokyo, Japan. First established in 1882 as the Tōkyō Senmon Gakkō or Tōkyō College by Ōkuma Shigenobu, the school obtained university accreditation and was formally renamed as Waseda University in 1902. The university consists of 13 undergraduate schools and 23 graduate schools. Waseda is one of a select group of top 13 universities assigned additional funding under the Japanese Ministry of Education, Culture, Sports, Science and Technology’s “Top Global Universities” Project.

Waseda consistently ranks among the most academically selective and well-regarded universities in Japanese university rankings.

Courses
Course 1: Maximum Likelihood Estimation (22 hours)

Instructor: Dr Daina Chiba

Schedule: 6 – 20 September, 2017

Time: 1:00 PM – 2:30 PM (Mon, Wed, Fri), 1:00 PM – 4:15 PM (Tue, Thu), 10:40 AM – 12:00 PM (20 Sep)

Location: Waseda campus, Waseda University, Japan

Tuition Fees: £300

To apply: Please complete the following online Application form choosing ‘0A’ from the course selection drop down menu. Application deadline 4 August.

 

Course 2: Multilevel Analysis (22 hours)

Instructor: Dr Lucas Leeman

Schedule: 13 – 20 September, 2017

Time: 10:40 AM – 4:15 PM (13, 15 Sep), 10:40 AM – 2:30 PM (14, 16, 18, 19 Sep), 10:40 AM – 12:00 PM (20 Sep)

Location: Waseda campus, Waseda University, Japan

Tuition Fees: £300

To apply: Please complete the following online Application form choosing ‘0B’ from the course selection drop down menu. Application deadline 4 August.

Please Note:
• Students need to make lodging and travel arrangements on their own;
• Waseda cannot sponsor student visa.

Prerequisites
The course should be taken subsequent to a course on linear regression using OLS. Knowledge of basic calculus will be useful — though not strictly essential. No matrix algebra will be required. That said, statistical models are mathematical models and so we will use a lot of basic algebra and mathematical notation in order to formalize our theoretical intuitions into mathematical (statistical) models. Students should be ready to consume and produce models presented in this way