74948 - Statistics for Healthcare

Learning outcomes

To introduce you to probability theory and classical statistical methodology, with applications to healthcare. To show you how to apply and interpret the results of statistical analyses in your future role as a health/healthcare researcher or manager. To prepare you for Econometrics, the second course in Quantitative Methods in Health and Healthcare.

Course contents

(Updated with minor edits on 18 September 2021)

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 healthcare;

2. explain some of the fundamental concepts of probability theory, the difference between a population and a 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, and be able to carry out, numerical and graphical analysis of data in a sample using descriptive statistics;

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

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

8. using software such as Stata or MS 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. (Free download available).

*** Probability, Statistics and Econometrics, O.B. Linton 2017. Academic Press. (University of Bologna e-book).

*** Statistics for Business and Economics, Global Edition. P. Newbold W. Carlson, B. Thorne 2019. 9th edition. (University of Bologna e-book).

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

Teaching methods

Lectures, computer-based workshops and tutor classes.

Assessment methods

Examination with multiple choice, short answer and short essay questions.

Teaching tools

Lectures, computer-based workshops and tutor classes.

Office hours

See the website of Martin Forster