Book contents
- Frontmatter
- Dedication
- INTRODUCTION
- STEP 1 Descriptive statistics
- STEP 1 – exercise Preliminary data analysis
- STEP 2 We analyse the distribution of the measurable variable
- STEP 2 – exercise Data analysis
- STEP 3 The χ2 (chi-square) test of the goodness of fit
- STEP 3 – exercise Checking the type of distribution
- STEP 4 T-test and F-test
- STEP 4 – exercise F-test and T-test
- STEP 5 ANOVA test
- STEP 5 – exercise ANOVA test
- STEP 6 Correlation and regression
- STEP 6 – exercise Correlation and regression
- STEP 7 The Pearson's χ2 (chi-square) test (The χ2 independence test)
- STEP 7 – exercise χ2 (chi-square) test of independence
- STEP 8 Nonparametric tests (distribution-free tests)
- STEP 8 – exercise Nonparametric tests (distribution free tests)
- STEP 9 Comprehensive Analysis
- STEP 9 – exercise Comprehensive Analysis
- STEP 10 Survival analysis
- STEP 10 – exercise Survival analysis
- Recapitulation
- Afterword
- Supplementary Tables
- Vocabulary
- Further Readings
- Index
- Contents
INTRODUCTION
Published online by Cambridge University Press: 05 September 2014
- Frontmatter
- Dedication
- INTRODUCTION
- STEP 1 Descriptive statistics
- STEP 1 – exercise Preliminary data analysis
- STEP 2 We analyse the distribution of the measurable variable
- STEP 2 – exercise Data analysis
- STEP 3 The χ2 (chi-square) test of the goodness of fit
- STEP 3 – exercise Checking the type of distribution
- STEP 4 T-test and F-test
- STEP 4 – exercise F-test and T-test
- STEP 5 ANOVA test
- STEP 5 – exercise ANOVA test
- STEP 6 Correlation and regression
- STEP 6 – exercise Correlation and regression
- STEP 7 The Pearson's χ2 (chi-square) test (The χ2 independence test)
- STEP 7 – exercise χ2 (chi-square) test of independence
- STEP 8 Nonparametric tests (distribution-free tests)
- STEP 8 – exercise Nonparametric tests (distribution free tests)
- STEP 9 Comprehensive Analysis
- STEP 9 – exercise Comprehensive Analysis
- STEP 10 Survival analysis
- STEP 10 – exercise Survival analysis
- Recapitulation
- Afterword
- Supplementary Tables
- Vocabulary
- Further Readings
- Index
- Contents
Summary
This book is based on a series of lectures on statistical methods delivered at the Faculty of Medicine of the Jagiellonian University Medical College. The goal of this course is to introduce basic statistical concepts and tools necessary to analyse medical data. It is not assumed that a medical student – the future doctor – will go into raptures over statistical methods, quit his/her beautiful profession and become a statistician. It is, however, assumed that in the future professional career they both will find their common language. The doctor will communicate with the statistician and actively participate in analysis of medical data which gradually accumulate in his/her data base. If there are 10–20 patients, the doctor remembers all of them and their related events. However, when the number of patients reaches a number of thousand or even more, data analysis can be performed only with the use of statistical tools.
Trends in the development of medicine demonstrate the increasing role of monitoring and continuous analysis of medical data. The need for permanent analysis is forced by constant changes in life conditions within a given region (climate changes, wealth, fashion, lifestyle, travelling, etc.). It becomes not only necessary but also convenient to record problems the patients discuss with their doctors (family physician, hospital doctor, emergency doctor, etc.). A large number of new drugs that appear on the market also prompt individual analysis of their effects.
The presentation of basic statistical notions and concepts is supported by examples of statistical tests performed using the SAS software package (version 3). It is assumed that the reader is familiar with Microsoft Office Excel. These statistical tests in SAS are presented in a separate section not to interrupt the continuity of statistical reasoning with technical details related to performance of a test.
- Type
- Chapter
- Information
- Statistics by Prescription , pp. 7 - 8Publisher: Jagiellonian University PressPrint publication year: 2009