This face to face course is run by the Researcher Academy
The 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.
Target Audience: Early stage postgraduate research students and early career researchers
This course is for you if you have little or no previous experience of quantitative research methods (i.e. methods involving numbers and basic statistics) but feel that there is potential to apply such methods to your research. The course covers different types of quantitative methods including calculation of summary statistics, an introduction to correlation and regression analysis, hypothesis testing and calculating p-values.
This course will be useful if:
You need to apply these methods in your own discipline
You want to assess whether there is potential to use quantitative methods
You need to interpret the output from other quantitative research
Description
This is a two-day introductory course, and does not assume any previous experience of quantitative research methods.
The aim of the course is an introduction to statistics as a whole, but will focus on several common topics of interest to many disciplines. The course does not aim to teach students how to use particular statistical packages, though there will be some examples of implementing statistical methods in R.
The focus is on understanding the topics; applications are shown by simple examples calculated by hand. Although 'by hand' calculations are not common practice in research, their purpose here is for students to gain an insight into how to obtain statistical results and to appreciate the meaning and implications of their output from statistics software.
The course includes the following topics
A description of different types of quantitative data
Strength sand weaknesses of quantitative data
Discussions on data integrity
Describing data graphically
Calculating summary statistics
Measures of correlation
Conducting hypothesis testing
Calculating and interpreting p-values
Introduction to regression analysis
Aims: The aim of the course is to provide a brief introduction to the principles of quantitative research methods.
Objectives:
By the end of the course, you will:
Be able to distinguish between different types of quantitative data
Be able to provide basic numerical summaries of data
Be able to perform hypothesis tests and report p-values
Process: A two-day course involving discussion and practical exercises.
Course Materials:
You can self-enrol to access the course resources in Moodle by following this link: https://moodle.nottingham.ac.uk/course/view.php?id=140161
Here you will find all the course information for both the online and face to face versions of this course which complement each other, including the slides, pre-recorded tutor videos, 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 R codes used in the class are also available on the course page. Solutions to exercises can also be checked after completion of the course.
If you cannot access the course page, please email ra-training@nottingham.ac.uk.
Please note, attendances for courses will be recorded. There are no training points associated with courses run by the Researcher Academy.
Course Accessibility
The following table shows a summary of what is needed to participate in the course.
If you feel you will experience any difficulties participating, please let us know via the ‘special requirements’ tab, providing as much information as possible. The special requirements tab can be completed when you book your place. Alternatively, you can contact us directly at ra-training@nottingham.ac.uk.
Print off pre-requisite paperwork/ resources & bring them to the course (optional) | |
Bring your own laptop/ PC to the course (optional) | |
Access seminar room on campus | |
Attend the course at the specified date and time | |
Watch and listen to the course tutor(s) and/or other attendees | |
Follow presentation slides during the course |
Booking Conditions
Latecomer policy
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 ra-training@nottingham.ac.uk. 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. The 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.
Please note, if this course is being held in the Engineering Science & Learning Centre access is by swipe card.
Pre-requisites
There are no pre-requisities but participants are strongly encouraged to look at 'Statistics - an intuitive introduction' before attending to familiarise themselves with common statistical techniques, terms and calculations.
Students must self-enrol in Moodle to access course resources used during the course by following this link: https://moodle.nottingham.ac.uk/course/view.php?id=121093
Prior to joining this face to face course students should read through the introductory section covering why we study statistics.
In addition, students are strongly advised to familiarise themselves with the Student Workbook, which is also available on the course’s Moodle Page.
You must bring a copy (printed or electronic) of the GSTQME Formulae Sheet to the course.
Please ensure that you bring a calculator with you on the day.
Researchers from the Faculty of Engineering should book onto Quantitative Methods for Engineers
Location | Start Date | All Dates | Times | Places Available | Book |
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