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.
- Clinical Scientists and trainee Clinical Scientists
- 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.
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.
Provisional Timetable Day 1
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
Provisional Timetable Day 2
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.
Course Fees and Registration
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.
Online Software Applications
These applications are provided for illustrative purposes only. They have only been tested with MS IE v6 and may not function properly with other browsers.
For each application, the About button provides instructions on the use of the site. Click here to download a set of example data that can be used with these applications.
- Student’s 1-sample t-test
- Student’s 2-sample t-test
- Wilcoxon 1-sample non-parametric test
- Mann-Whitney 2-sample non-parametric test
- Significance test for Differences in Proportions
- Power calculations for differences in means
- Power calculations for differences in proportions
- 1-way ANOVA
- ROC analysis
- Relative risk and odds ratio
- McNemar's test
- Bland-Altman analysis
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
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