Associations and Correlations for Medical Research
Associations and Correlations for Medical Research
A Holistic Strategy To Help You Discover The Story of Your Data
About the Book
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In Associations and Correlations for Medical Research, award-winning statistician and author Lee Baker guides you through the building blocks of discovering and visualising the relationships within your data.
Associations and correlations are ways of describing how a pair of variables change together as a result of their connection. In other words, if one of your variables changes, the other is likely to change too.
These types of analysis are some of the most used – and misunderstood – statistical techniques. Most results you’ll encounter are wrong, and for a very good reason. In this book you’re going to learn just why this is, avoid the most common pit-falls and learn how to make sure you get the correct results first time, every time.
Here, you’ll learn a holistic method of discovering the story of all the relationships in your data by guiding you through a variety of the most used association and correlation tests in medical statistics – and helping you to choose them correctly. The holistic method is about selecting the most appropriate univariate and multivariate tests and using them together in a single strategic framework to give you confidence that the story you discover is likely to be the true story of your data.
Associations and Correlations for Medical Research is written in plain English with a focus on understanding the data, how to work with it, choose the right ways to analyse it, select the correct statistical tools and how to interpret the results in a way that is easy to understand. It enables medical researchers to understand and to evaluate critically the results of analyses that they will encounter in their own research and in that of others.
Best of all, it makes no assumptions about your previous experience with statistics, is packed with visually intuitive examples from medical research and is perfect for beginners!
Discover the world of medical associations and correlations. Get this book, TODAY!
About the Author
Bundles that include this book
Reader Testimonials
Heather Krausse
Data Science and Information Design
Great material at a reduced price for the #nptech crowd
David Napoli
Advanced Analytics Strategy & Data Visualization Director
Start your week off right by drinking from the firehose of #stats knowledge
Vincent Granville
Executive Data Scientist, Co-Founder, Data Science Central
As featured in '13 Great Articles and Tutorials about Correlation' on Data Science Central
Table of Contents
Introduction
Section 1: Preparing Your Data
Chapter 1: Data Collection and Cleaning
1.1: Data Collection
1.2: Data Cleaning
Chapter 2: Data Classification
2.1: Quantitative and Qualitative Data
Section 2: Your Statistical Toolbox
Chapter 3: Introduction to Associations and Correlations
3.1: What are Associations and Correlations?
3.2: Discovering the Story of Your Data
3.3: Correlation v Causation
3.4: Assessing Relationships
3.5: Assessing the Strength of Relationships
Chapter 4: Univariate Statistics
4.1: Correlations
4.2: Associations
4.3: Survival Analysis
Chapter 5: Multivariate Statistics
5.1 Types of Multivariate Analysis
5.2 Using Multivariate Tests As Univariate Tests
5.3 Univariate v Multivariate Analyses
5.4 Limitations & Assumptions of Multivariate Analysis
5.5 Step-Wise Methods of Analysis
5.6 Creating Predictive Models with the Results of Multivariate Analyses
Section 3: The Story of Your Data
Chapter 6: Visualising Your Relationships
6.1: A Holistic Strategy to Discover Independent Relationships
6.2: Visualising the Story of Your Data
Chapter 7: Bonus: Automating Associations and Correlations
7.1: What is the Problem?
7.2: CorrelViz
Summary: A Holistic Strategy to Discover the Story of Your Data
Epilogue
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