Date and Time

The dates and times vary each year. The class locations also change from year to year. For the most current and updated information, please consult UC timetable (this link is valid for 2018). 
For the year 2018, these are the dates and times (9 AM - 3 PM):
Block I, Day I: 28th February, Wednesday, Wheki 103
Block 1, Day 2: 1st March, Thursday,  Wheki 101
Block II, Day 1: 28th March, Wednesday, Jack Mann 101
Block II, Day 2: 29th March, Thursday, Wheki 101
Block III, Day 1: 9th May, Wednesday, Wheki 106
Block III, Day 2: 10th May, Thursday, Wheki 101
The official course page is at http://learn.canterbury.ac.nz/course/view.php?id=2908, and you should consult the official page. This website provides you with the course content, and assessment policy. a copy of this syllabus is also kept at the official page. The course materials are also maintained at the course's Github repository so that you can use the materials even after the course is over. These are maintained at the following site: https://arinbasu.github.io/health460/
As the course is hosted on a github site, you can obtain all course materials if you can fork the site. We will go over these issues of technology on the first day of the course. 

Description of the course

We will organise this course in three blocks of two days per block. In the first block, we will learn how to read literature critically. At the end of this block you will write a research proposal following the guidelines and the lessons you will learn in the first two days.
In the second block, you will learn data science in R. You will learn where to look for data, how to read data into R, how to preprocess data using dplyr, how to visualise data using ggplot2, what is meant by modellling and what tools you can use to model data. If you are already familiar with R statistical software, great. If you are not, there will be enough scope for you to learn in the class. You will need to bring a computer with you (do not use a tablet or an ipad or your phone: they will not work). The format of the class will be such that I will work on the screen at the same time as you will work on your computers. This method of teaching is referred to as live coding. I will also give you unfinished examples from time to time in the class to complete. This is referred to as "faded examples". Using these various tools, you will gain mastery in taking a data set and working through the data set to clean it to a point where you can analyse it.
Then in the third block, you will learn how to write a research paper or a report. Here we will cover details of how to write a paper; finally, we will complete this course with a lecture from our research person where to find for funds to conduct your study. 
In this course, our emphasis will be on finding research and reports related to environmental health. We will study air pollution, water pollution, soil pollution, climate change, but also social environmental issues. You can bring your own topic of inquiry you are working on and you are not only welcome to do so, you are encouraged to talk about your own topic. If you are considering to write your own research proposal for your Master thesis, this is a class where you can develop it pretty much (the same goes for your doctoral thesis proposal development). 

Assessment Summary Table