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

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Introductory Medical Statistics - one-day virtual course

Category: statistical

17 November, 2020

Registration is now closed. 

Applicants can be put on a waiting list on request.  

The programme is accessible further down this page.  

Contact Magda Wheatley for further information.

- Click here to join our courses and events mailing list

  • Online registration is by card only - this is our preference.  NB: 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 and students can pay by internal transfer; if so, you do not need to use the booking link.  Please just supply your details and a project/grant code.  Please contact Magda Wheatley about this.  

Registration fees (VAT-exempt): 

  • MSc/PhD students:  £110 - proof of student status may be required prior to registration
  • Academic/NHS:  £175
  • Corporate/other:  £225

 

* Please note that this course will NOT be recorded. *

 

Course description 

Designed to introduce anyone who uses statistics in their work or research to the following:

- Basic epidemiological concepts (hierarchy of evidence and differences in study designs; confounding in observational studies vs. RCTs
- Descriptive statistics for quantitative, ordinal and qualitative data (mean, median and mode; standard deviation, percentiles and frequency distribution)
- Inferential statistics: estimating parameters in the population (confidence intervals)
- Testing a hypothesis (p-values; choosing a test; types of errors – false positive and false negative results; multiple testing)
- Correlation vs. simple linear regression to test relationships between quantitative variables (differences in aims and links between the two approaches; simple linear regression vs. ANOVA)
- Multiple linear regression to adjust for confounding; Interpretation of findings; examples of the impact of confounding on estimates of interest
- Different measures of risk (binary outcomes): relative measures of risk (odds ratio, relative risk, hazard ratio); absolute measures of risk (risk difference, NNT/NNH)
- Simple and multiple logistic regression (binary outcomes): interpretation of findings; examples of the impact of confounding on the estimates of interest
- Power and sample size calculations: why we need them and what parameters we need to perform them ; examples of sample size and power calculations for continuous and binary outcomes

The course will conclude with a practical session: revision and discussion of concepts presented in the course using real examples. Feedback with answers to questions through online voting.

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

Accreditation by the Royal College of Physicians currently sought
 

Feedback from most recent (two-day, face-to-face) course, in 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."

 

Credit for main photo: Carlos Muza on Unsplash 

Images from our November 2019 course (credits: Diana van der Plaat): 

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.