• Training Room

    Stats for the Fearful
    Provider   Researcher Development Programme

    This course starts with a reminder of basic statistics and then introduces the principles behind statistical inference and hypothesis testing. The emphasis is on interpreting outputs from such analysis as might appear in academic journals.

Duration 1 full day

Course Type Webinar

Booking Status Waiting List

Is this course right for me?

Target Audience: Postgraduate Research Students

This is an introductory or refresher course with no computer based exercises. For those needing to undertake such analysis as a regular part of their research, this course could serve as a precursor to attending a more comprehensive lab-based class such as MM914.

The key course content includes the following:

This is an introductory or refresher course with no computer based exercises. For those needing to undertake such analysis as a regular part of their research, this course could serve as a precursor to attending a more comprehensive lab-based class such as MM914.

The key course content includes the following:

  • Data and data types
  • Graphs and charts and which to use
  • Summary statistics and frequency tables
  • Statistical inference: random sampling, the normal distribution, estimating means and proportions, confidence intervals
  • Hypothesis tests for comparing means and proportions for normal and non-normal continuous data (ie using parametric and non-parametric methods)
  • Hypothesis tests for categorical data (contingency tables and Chi-squared tests)
  • Introduction to Analysis of Variance for comparing means of more than two groups (ie one-way ANOVA).

By then end of the course, participants will:

  • Understand the correct usage of summary statistics and graphs
  • Understand the concepts behind statistical inference and hypothesis testing for some common situations
  • Gain confidence in interpreting the results of such analysis as often presented in academic journals


Delivered By: Ian Dwyer, Knowledge Exchange Director, Department of Mathematics and Statistics

Prerequisites

Basic statistical knowledge is assumed (eg calculating means, reading graphs). No knowledge of more advance concepts is required, though some exposure to hypothesis testing would be an advantage. Example outputs are provided from Minitab, but no knowledge of Minitab is necessary. Cancellation Policy

If you are unable to attend a course please cancel your place as soon as possible, with at least 3 working days notice via the online booking system http://bookings.strath.ac.uk/mybookings.asp.

Full details of booking conditions can be found at the link below.

Useful Links

Find out about the opportunities available to you as an early career researcher:

PG Certificate in Researcher Professional Development

All postgraduate research students are eligible to access the Researcher Development Programme workshops. This workshop can contribute towards the PG Certificate in Researcher Professional Development (PG Cert RPD).

You can find credit and class information in the Researcher Development Programme Handbook and in NEPTUNE (Engineering, HaSS) or SPIDER (Science).

Please check with your department or Supervisor to confirm if you are enrolled on the PG Cert RPD and how many credits you are expected to achieve if you are unsure.