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Short Course on Medical Statistics

Do you understand the meaning of the P-value? Do you know when to apply non-parametric tests and which test? Do you know what confounders are and how you adjust for them by stratification? Do you understand conditional probability and Bayes theorem?

These short courses will help you gain confidence to understand such concepts. Some background knowledge of basic mathematics is assumed. If you want to find out if you have the necessary skills, try this diagnostic quiz. You should be able to answer all questions confidently.

Target audience:

  • Clinical Scientists and trainee Clinical Scientists
  • Doctors
  • Nurses
  • Healthcare Scientists
  • Allied Health ProfessionalsPhD students
  • Clinical Psychologists
  • Medical Researchers

Aims of the courses:

To understand how statistical analysis and decision theory can be applied in medicine. You will learn how to analyse data and correctly interpret statistical findings in scientific publications. The course is backed up by a number of examples from the medical literature with practical demonstrations and exercises on how to carry out analysis. Some basic prior knowledge is assumed such as “Normal Distribution”, “mean”, “median”, “histogram”, etc.

CPD/CME:

These courses satisfy the requirements for HCPC CPD schemes.

All participants receive a full set of lecture notes and a certificate of attendance.

The first day is a refresher course covering the following topics:

  • Hypothesis testing
  • Type I and type II errors
  • Power calculations
  • Non-parametric tests
  • Analysis of variance
  • Probability Theory
  • ROC analysis
  • Correlation and regression
  • Relative risks and odds ratio

The second day is an intermediate course covering the following topics:

  • Robust statistics
  • Bayesian inference
  • Logistic regression analysis
  • Survival analysis
  • Making sense of statistics
  • Clinical decision making
  • Critical appraisal

The course is backed up by a number of examples from the medical literature with practical demonstrations and exercises.

Some background knowledge of basic mathematics is assumed. If you want to find out if this course is suitable for you, try this pre-course quiz. You should be able to answer all questions confidently.

10:00 – 10:05           Welcome

10:05 – 10:20           Data exploration: types of data; Normally distributed and skewed data; Numerical summaries; Plots

10:20 – 10:45           Hypothesis testing: null and alternative hypotheses; student’s 1 and 2-sample t-test; type I and type II errors; interpreting the P value; significance test for proportions

10:45 – 11:15           Power calculations: determining the sample size

11:15 – 11:30           Exercise

11:30 – 11:45           Break

11:45 – 12:15           Non-parametric tests: sign test; Wilcoxon signed rank test; Mann-Whitney test; chi-squared goodness-of-fit test

12:15 – 12:45           Analysis of variance: 1-way and 2-way ANOVA; factorial experiments

12:45 – 13:00           Exercise

13:00 – 14:00           Break

14:00 – 14:30           ROC analysis: definitions; confusion matrix; ROC curve; examples

14:30 – 15:00           Probability theory: events; conditional probability; prior and posterior distributions; Bayes Theorem; linear regression; relative risk and odds ratio

15:00 – 15:30           Exercise

15:30 – 15:45           Break

14:30 – 15:00           Correlation and regression: Pearson correlation; Spearman rank correlation; linear regression; relative risk and odds ratio

16:00 – 16:15           Summary

9:00 – 9:30                                     Registration

9:30 – 10:00                                   Robust Statistics: outliers; influential data points; leverage; residuals 

10:00 – 10:30                                Bayesian inference: conditional probability; marginalisation; posterior distributions

10:30 – 10:45                                Exercise 

10:45 – 11:00                                Break

11:00 – 11:30                                Logistic regression: log-odds; goodness-of-fit; model checking, outcome prediction

11:30 – 12:00                                Survival analysis: Kaplan-Meier; univariate and multivariate analysis; Cox regression  

12:00 – 12:15                                Exercise 

12:15 – 13:00                                Break 

13:00 – 13:30                                Making sense of statistics: correct interpretation of p-values; checking assumptions; Bonferroni correction 

13:30 – 14:00                                Clinical decision making: confidence intervals; clinical significance; number needed to treat; loss function; cost-benefit analysis

14:00 – 14:15                                Exercise 

14:15 – 14:30                                Break  

14:30 – 15:00                                Critical appraisal: study designs; sources of bias; example from medical literature; which tests to use; how to present data

15:00 – 15:30                                Summary: Homework

This course will be delivered online using a platform such as Teams, Zoom or Skype. Full details will be announced nearer the time. Supporting material including a full set of lecture notes will be uploaded about a week in advance and a link will be posted to all participants.

Delivery of the course includes a mixture of lectures, demos, exercises and Q&A sessions.

Contact us for more details.

2 day course: £230 +VAT.  Please note that NHS organisations are exempt from VAT.

Included in the fees are full set of lecture notes, access to interactive teaching and supporting material such as demo websites and example data, and CPD certificates

Click here to download an application form

Contact us for more details.

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We are keen to find out how useful delegates find these courses and how they have applied them in their place of work. If you attend the courses and write an article in a professional journal, let us know and you will be entitled to a 2 for 1 voucher to pass on to your colleagues on the next available courses.

Comments from previous course participants:

  • I certainly came away with more confidence in how to analyse data myself and how to understand figures quoted in papers
  • Worked examples were most useful to consolidate knowledge
  • Exercises really helped
  • Covered the right topics at a good speed
  • A very well organised course
  • A great course for someone like me with a stats phobia!
  • I enjoyed the course. It has given me a good background in statistics in medicine
  • Most useful part was being able to reflect on content delivered through exercises 
  • Exceeded expectation: clarity and breadth of content
  • I really appreciated the clear and straight forward teaching

Full review 1 - IPEM Newsletter 2009

Full review 2 - IPEM Scope 20,4 2011

Further information:

For further information including availability, please contact:

Prof. Azzam Taktak or Mrs. Lynsey Holmes

Tel: +44 (0)151 706 4202

Fax: +44 (0)151 706 5803

CD1909/02, Page 2 of 2 (July 2021)