# HAR6035: Introduction to Statistics and Critical Appraisal

The Introduction to Statistics and Critical Appraisal module is led by Stephen Walters. It runs in the Autumn semester and is worth 15 credits.

### Overview

The Introduction to Statistics and Critical Appraisal module is led by Stephen Walters. It runs in the Autumn semester and is worth 15 credits.

It is one of the modules on:

• European Masters Programme in Public Health (core)
• Master of Public Health (Health Services Research) (core)
• Master of Public Health (MPH) (core)
• MSc Clinical Research (NIHR for Academic Clinical Fellows) (core)
• MSc Clinical Research (standard route) (core)
• MSc Human Nutrition (core)

This module is available as a CPD option

This module is available Faculty-wide in year 1 as a DDP module

### Introduction

This module introduces students to the basic concepts and techniques of medical statistics, such as hypothesis testing and confidence interval estimation.

Students will learn some simple statistical methods and the principles behind some of the more advanced techniques such as regression. It will equip students with the knowledge and skills necessary to understand and critically appraise statistics in research literature.

The course is not aimed at 'doers' of statistics; that is, students who are going to design their own studies to collect and analyse their own data. It will not teach you how to analyse, present and report your own data. If you require this please see HAR6045.

### Objectives

This unit aims to:

• introduce students to fundamental concepts and methods in medical statistics
• enable students to apply these concepts to critically appraise research literature

### Learning outcomes

On satisfactory completion of the course, a student will be able to:

• Classify and appropriately display and summarise different types of data.
• Describe the properties of the Normal distribution.
• Distinguish between a population and a sample, and describe the precision of a sample estimate of a population parameter.
• Explain the concept of confidence intervals as applied to means, proportions, differences in means, and differences in proportions.
• Describe the process of setting and testing statistical hypothesis.
• Distinguish between ‘statistical significance’ and ‘clinical significance/importance’.
• Evaluate the quality of published research.

### Teaching methods

Lectures will be used to impart knowledge of key statistical concepts and methods, while structured exercise classes will apply these concepts to example data or published studies.