Researcher Academy courses are very popular and the majority are run in both semesters to give you the opportunity to attend at a time of the year that suits you. Semester 1 courses will be available for booking from the second week of October and Semester 2 courses from the second week of February.
Target audience: Postgraduate research students from the Faculty of Engineering. Science Postgraduate research students working collaboratively with Engineering may attend.
Process: Practical Workshop
Course Description:This is a 2-day introductory course,similar to the general ‘Introduction to Quantitative Research Methods’ but pitched at a higher level. The aim of the course is to understand the statistical concepts covered through the aid of exercises and examples. No particular software package is covered but the methods described can be easily implemented in any stats package or Matlab.
The first day of the course is intended to introduce students to basic statistical concepts, such as random variables,probability and distributions. The second day of the course will involve practical applications of hypothesis testing techniques and interpretation of results from regression analysis.
The course includes the following topics:
1) Random variables and statistical distributions.
2) Discussions of data integrity and factors influencing experiment design.
3) Describing data graphically for a general audience
4) Summarising data numerically. The concepts of bias and efficiency for estimators is introduced.
5) Hypothesis testing of various kinds
6) Estimation of sample size
7) Fitting statistical distributions to data
9) Hypothesis testing for the presence of a trend in data sets
Here you will find all the course information for GSTQME/GSTRM4, including the slides, workbook and formulae sheet.
You do not need to bring a copy of the workbook, as this is intended to be used as a reference having completed the course. You need to bring a printed copy or have access to the electronic version of the formulae sheet, as this will often be used for exercises during the course.
The R codes used in the class are also available on the course page. The lecture slides and solutions to exercises will be made available on the course page after completion of the course.
The aim of the course is to provide a brief introduction to quantitative research methods so that the attendee is able to go away and read more advanced text books and implement the analysis methods on a computer.
By the end of the course you will have a thorough understanding of quantitative methods and how they can be applied to your research. You will be able to
1) Perform hypothesis tests on sample data
2) Summarise data graphically and numerically
3) Understand terms used in more advanced texts
4) Perform further study independently
Introduction to SPSS is an online course designed to teach you the basics of IBM® SPSS® Statistics.
'Virtual Statistical tutor', an online learning tool for those who are familiar with the basics of data collection and analysis and require more information about statistical methods.
Additionally, help is available from the Methods and Data Institute (MDI): PGRs engaged in empirical research for their PhD thesis can call on the MDI for advice on their choice and use of methods and data. A drop-in session especially for PGRs is available every Tuesday from 2-5pm - appointments must be made for this by emailing email@example.com
Researchers should plan to arrive prior to the advertised course start time. Except for exceptional reasons, there will be no admittance to a Researcher Academy or Faculty Training Programme (FTP) course 15 minutes after the advertised course start time.
Importance of booking commitment
When booking on to a Researcher Academy short course you are entering into a commitment to attend. If you find that you are no longer available to attend you MUST cancel your place (on the system if more than three days before the course) or if at short notice by emailing firstname.lastname@example.org. This will ensure that your place can be offered to another researcher on the waiting list. Failure to cancel a place results in other researchers missing out on places through the waiting list process.
It is unacceptable for researchers to just not attend when booked onto a course. Researcher Academy maintains records of those who repeatedly do not attend courses they have booked. This may affect future eligibility to book onto further Researcher Academy courses and will affect considerations for Researcher Academy funded opportunities.
Students should have some experience with using calculus, particularly integration by parts. In addition, knowledge of the rules associated with logarithms is assumed. If students wish to familiarise themselves, or revise, common statistical terms and techniques, they are strongly encouraged to look at 'Statistics- an intuitive introduction' before attending.
In addition, students are strongly advised to familiarise themselves with the Student Workbook, which is available on the course’s Moodle Page (see how to gain access to this page below).Students who feel that this course is too advanced for them are advised to first take the course Introduction to Quantitative Research.