74948 - Statistics for Healthcare

Learning outcomes

At the end of the course the student is provided with the essential concepts of statistics and probability, with the dual objective of illustrating the basic tools for the exploratory analysis of health-related data and introducing the founding elements of econometrics.

Course contents

By the end of this course, you should be able to:

1. explain why risk and uncertainty are fundamental to research and decision-making in health care;

2. explain the fundamental concepts of probability theory, the population and the sample, experiments, observational studies and sampling error;

3. explain the difference between qualitative and quantitative variables and describe the main discrete and continuous random variables that are relevant for classical statistics. Define and be able to interpret the probability mass and density function,
measures of central tendency and dispersion, including the expected value, variance and standard deviation;

4. explain what is meant by making causal inferences, why randomised controlled experiments may permit us to make them, and the challenges of making causal inferences with observational data sets;

5. explain what is meant by the sampling distribution of a population parameter, confidence intervals, hypothesis tests, p-values and test statistics. Be able to test hypotheses for population means and proportions;

6. explain what is meant by simple regression and multiple regression;

7. using software such as Stata or Excel, carry out suitable exploratory analyses using numerical, graphical and tabular descriptive methodologies and test hypotheses using experimental and observational data sets. Be able to interpret the results of such analyses, explain the statistical methodology underlying the results and interpret the results in a manner which may be understood by non-statisticians.

Readings/Bibliography

Chapter 3, 'Statistical Tools for Health Economics' in The Economics of Health and Health Care, S. Folland, A. C. Goodman and M. Stano 2017, 2014, 2013, 2010 (8, 7e, 7, 6 Editions), Routledge/Pearson/Prentice Hall.

Chapter 1, ‘Sample Space and Probability’ in Introduction to Probability, D. Bertsekas and J. Tsitsiklis 2008. Athena Scientific.

Introductory Statistics and Analytics: A Resampling Perspective, P. C. Bruce and I. Yahav 2015. John Wiley & Sons, Inc.

Practical Statistics for Medical Research. D. Altman 1991. 1st Edition. Chapman and Hall.

 

 

 

Teaching methods

8 Lectures, 2 computer classes and 2 tutor classes.

Assessment methods

Online exam.

Teaching tools

8 Lectures, 2 computer classes and 2 tutor classes.

Office hours

See the website of Martin Forster