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Reasoning with statistics: how to read quantitative research / Frederick Williams, Peter Monge

Por: Williams, Frederick, 1933- [autor/a].
Monge, Peter [autor/a].
Tipo de material: Libro impreso(a) Libro impreso(a) Editor: Boston, Massachusetts, United States: Wadsworth, c2001Edición: Fifth edition.Descripción: xi, 228 páginas : gráf., ilustraciones ; 24 centímetros.ISBN: 0155068156; 9780155068155.Tema(s): Métodos estadísticos | Métodos cuantitativosClasificación: 001.422 / W5 Nota de bibliografía: Incluye bibliografía e índice: páginas 223-228 Número de sistema: 52787Contenidos:Mostrar Resumen:
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This text is designed to help students become knowledgeable readers of cross-curriculum quantitative research literature. It provides a clear inviting view of quantitative research strategies for those students who may or may not have a mathematical background. The authors impart a conceptual understanding rather than teach calculational methods. The text can be used as a supplement for a basic statistics course or for any course requiring students to read and digest quantitative research literature. Examples are cross-curriculum and generic. Its strength is that it is very brief and doesn't overwhelm with too much detail.
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Acervo General (AG) 		Acervo General 001.422 W5 Disponible ECO020012891

Incluye bibliografía e índice: páginas 223-228

Part I: On Conducting Quantitative Research.. 1. Why Do Quantitative Research?.. 2. Statistics and Research.. Part II: Descriptive Statistics.. 3. Levels of Measurement.. 4. Describing Distributions.. Part III: Population Statistics.. 5. Predicting Parameters.. 6. Testing Hypotheses.. Part IV: Analyses of Differences.. 7. The Test.. 8. Single-Factor Analysis of Variance.. 9. Multiple-Factor Analysis of Variance.. 10. Nonparametric Tests.. Part V: Analysis of Relationships.. 11. Correlation.. 12. Regression.. 13. Multiple Regression.. Part VI: Analyses of Complex Differences and Relationships.. 14. Factor Analysis.. 15. Discriminant Analysis.. 16. Time-Series Analysis.

This text is designed to help students become knowledgeable readers of cross-curriculum quantitative research literature. It provides a clear inviting view of quantitative research strategies for those students who may or may not have a mathematical background. The authors impart a conceptual understanding rather than teach calculational methods. The text can be used as a supplement for a basic statistics course or for any course requiring students to read and digest quantitative research literature. Examples are cross-curriculum and generic. Its strength is that it is very brief and doesn't overwhelm with too much detail. eng

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