Practical session at a 'Lung Function Testing in the Workplace - Introductory Level' course

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Introductory Medical Statistics - two day course

Category: statistical

17 November, 2020

Registration is not yet open. 

NB: we are hoping to go ahead as planned, but we’ll consider an online version, at a reduced cost, should the COVID-19 situation prevent a face-to-face course.

Please contact Magda Wheatley on m.wheatley@imperial.ac.uk with any queries. 

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  • Online registration will be by card only - this is our preference ...
  • We encourage people to pay by card where possible. If a customer would like to receive an invoice from the College and pay through this route, a purchase order number must be provided to Imperial College.  Course details will only be sent upon payment being received by the College. This process might be a lot longer and normally takes up to several weeks.  Therefore, payment by card is much quicker and easier if you would like to avoid delay.
  • Imperial College staff can pay by internal transfer if they wish.

Registration fees (VAT-exempt), for face-to-face version: 

  • MSc/PhD students:  £220 - proof of student status may be required prior to registration
  • Academic/NHS:  £350
  • Corporate/other:  £450

50 delegates maximum.  Places are expected to go quickly; the course will close when full. 

Fees will include handout, lunch and other refreshments, plus tea/coffee. 

Venue (map can be viewed here; photos on page 2) -

National Heart and Lung Institute

Education Centre, Paul Wood Lecture Theatre

Guy Scadding Building

Dovehouse Street

London SW3 6LY

Please note:

  • All places are first-come, first-served

Course description:

Two-day course designed to introduce anyone who uses statistics in their work or research to:

- Basic epidemiological concepts (study designs; bias and confounding; measures of risk)

- Descriptive statistics for quantitative, ordinal and qualitative data (mean, median and mode; standard deviation, percentiles and frequency distribution)

- Estimating parameters in the population (confidence intervals)

- Testing an hypothesis (p-values; types of errors – false positive and false negative results)

- Main statistical tests (parametric vs. non-parametric; paired vs. unpaired) for quantitative, ordinal and qualitative outcomes

- Correlation vs. simple linear regression to test relationships between two quantitative variables (differences in aims and links between the two approaches; simple linear regression vs. ANOVA)

- Simple logistic regression for binary outcomes

- Multiple linear and logistic regression analyses to address confounding

- Power and sample size calculations

- Basic concepts of survival analyses

The course alternates classical lectures with two practical sessions on application of the methods presented (individual work, followed by classroom demonstration and discussion), and a final discussion of concepts covered on the course, using some real-world examples. 

Suitable for - Doctors, nurses, clinical research fellows and postgraduate students

Accreditation by the Royal College of Physicians to be sought
 

Feedback (November 2019) -

"Absolutely great course!  All speakers were good and helpful."

"All presentations excellent. Very good speakers; concepts explained very clearly."

"Enjoyed the course a lot.  Very well prepared and presented."

"Excellent course – I will recommend to colleagues."

"Handout materials all very comprehensive and easy to understand. The booklet will be a very useful reference."

"The handout is arranged in a well-organised order. It is easy to follow the chapters taught."

"The practical was a great way of reinforcing concepts from the lectures! Really liked this/found it helpful!"

"Very helpful study days – thank you."

 

Images (November 2019):

  • Main photo: Elaine Fuertes presents 'Hypothesis testing: Quantitative outcomes'.
  • James Potts introduces the first of his two practical Data Analysis sessions; Alex Adamson presents 'Power and sample size'; Winston Banya presents 'Basic concepts of survival analysis'; the paper critique session in progess.

Credits: Diana van der Plaat