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
Afterword
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
In present day reality which is defined as the era of information technology, one should remember of another side of the medical practitioner's work with a specialist in mathematics or information technology, not necessarily limited to the statistical analyses.
Common access to enormous databases and to adequate, often extremely diversified IT instruments opens totally new collaboration possibilities of medical sciences with mathematical applications. The new quality of this collaboration consists in defining common research projects of medical matters in whose realisation an information scientist (a mathematician) can apply non-standard models, verifying the mechanism of processes responsible for the living organisms functioning.
If we run a little ahead and indulge in daydreams, it will prove that solving numerous problems, including the most important one concerning neoplasm forming, becomes possible and even close.
Voices are raised in discussion upon the mechanisms leading to disorders with which organism is unable to cope by itself. There is an audacious hypothesis saying that there are innumerable clinical and experimental data (cells, experimental animals). Most frequently these are very detailed data, concerning the particulars of various processes occurring in the organism both at the stage preceding a neoplasm change and during its expansion. The difficulty in interpretation of those data, sometimes very differentiated consists in the fact, that the tools are missing that would enable examination of a large number of detailed data. Opinions expressed in scientific papers, such as Nature or Science sound that only a close collaboration of mathematicians with physicians will (maybe in nearest future) recognize the correctly functioning mechanisms.
- Type
- Chapter
- Information
- Statistics by Prescription , pp. 242Publisher: Jagiellonian University PressPrint publication year: 2009