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Introductory Medical Statistics - two day course
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 firstname.lastname@example.org 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
London SW3 6LY
- All places are first-come, first-served
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