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1. |
Record Nr. |
UNISA990005967260203316 |
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Autore |
PANZA, Maria Onorina |
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Titolo |
L' architettura delle "camere urbane" / Maria Onorina Panza ; presentazione e introduzione di Antonio Conte |
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ISBN |
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Descrizione fisica |
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Collana |
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Collana architettura e paesaggio |
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Disciplina |
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Soggetti |
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Collocazione |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910999792303321 |
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Autore |
Twisk Jos W. R |
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Titolo |
Basic Principles of Applied Medical Statistics : A Practical Guide / / by Jos W. R. Twisk |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (XII, 268 p. 59 illus., 34 illus. in color.) |
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Disciplina |
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Soggetti |
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Biometry |
Sampling (Statistics) |
Biostatistics |
Methodology of Data Collection and Processing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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- 1. Introduction -- 2. Descriptive Statistics -- 3. Basic Principles of Explanatory Statistics -- 4. The Analysis of a Continuous Outcome Variable -- 5. The Analysis of a Dichotomous Outcome Variable -- 6. The Analysis of Survival Data -- 7. Multiple Regression Analysis – Association Models and Prediction Models -- 8. Machine Learning -- 9. Other Outcome Variables -- 10. Missing Data -- 11. Pitfalls in (Multiple) Regression Analysis -- 12. Miscellaneous -- 13. Overview -- 14. Example Datasets. |
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Sommario/riassunto |
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This book describes the basic principles of medical statistics. Although there are many texts on this topic, this one is different in that it limits the mathematics to an absolute minimum. It will therefore be extremely useful for non-mathematical researchers who need to use statistical methods in their work. Here, they will learn how to choose the appropriate statistical method and how to interpret the results obtained from statistical software. An important feature of the book is that it highlights the common thread throughout the statistical methods. By understanding this common thread, the analyses become much easier to comprehend. Each chapter contains multiple examples, and because the example datasets are available, the readers can reanalyze them and practice how to perform a particular statistical analysis. |
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