| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910460937803321 |
|
|
Titolo |
English for academic purposes : approaches and implications / / edited by Paul Thompson and Giuliana Diani |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Newcastle upon Tyne, England : , : Cambridge Scholars Publishing, , 2015 |
|
©2015 |
|
|
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Descrizione fisica |
|
1 online resource (357 p.) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
English language - Study and teaching (Higher) |
Academic language - Study and teaching (Higher) |
Electronic books. |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Description based upon print version of record. |
|
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references and index. |
|
|
|
|
|
|
Sommario/riassunto |
|
The analysis of academic genres and the use of corpus resources, methods and analytical tools are now central to a great deal of research into English for Academic Purposes (EAP). Both genre analysis and corpus investigations have revealed the patterning of academic texts, at the levels of lexicogrammar and discourse, and have led to richer understandings of the variations in such patterning between genres and between disciplines. The thirteen contributions included in this volume address issues in academic discourse studies from a range of perspectives: namely, corpus-based research into EAP |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNINA9910153105803321 |
|
|
Autore |
Agresti Alan |
|
|
Titolo |
Statistics: Pearson New International Edition: The Art and Science of Learning from Data |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
[Place of publication not identified], : Pearson Education Limited, 2013 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[3rd ed.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (811 pages) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Statistics |
Statistical methods |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Bibliographic Level Mode of Issuance: Monograph |
|
|
|
|
|
|
Nota di contenuto |
|
Cover -- Table of Contents -- Agresti/Franklin CD Contents -- An Introduction to the Applets -- Chapter 1. Statistics: The Art and Science of Learning From Data -- Chapter 2. Exploring Data with Graphs and Numerical Summaries -- Chapter 3. Association: Contingency, Correlation, and Regression -- Chapter 4. Gathering Data -- Part Review 1 -- Chapter 5. Probability in Our Daily Lives -- Chapter 6. Probability Distributions -- Chapter 7. Sampling Distributions -- Part Review 2 -- Chapter 8. Statistical Inferences: Confidence Intervals -- Chapter 9. Statistical Inference: Significance Tests About Hypotheses -- Chapter 10. Comparing Two Groups -- Part Review 3 -- Chapter 11. Analyzing the Association Between Categorical Variables -- Chapter 12. Analyzing the Association Between Quantitative Variables: Regression Analysis -- Chapter 13. Multiple Regression -- Chapter 14. Comparing Groups: Analysis of Variance Methods -- Chapter 15. Nonparametric Statistics -- Part Review 4 -- Answers -- Index -- Index of Applications -- Photo Credits -- End paper. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
Statistics: The Art and Science of Learning from Data, Third Edition, helps students become statistically literate by encouraging them to ask and answer interesting statistical questions. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible without compromising necessary rigor. Authors Alan Agresti and Christine Franklin believe that it's important for students to learn and analyze both quantitative and categorical |
|
|
|
|
|
|
|
|
|
|
data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data. The Third Edition has been edited for conciseness and clarity to keep students focused on the main concepts. The data-rich examples that feature intriguing human-interest topics now include topic labels to indicate which statistical topic is being applied. New learning objectives for each chapter appear in the Instructor's Edition, making it easier to plan lectures and Chapter 7 (Sampling Distributions) now incorporates simulations in addition to the mathematical formulas. |
|
|
|
|
|
| |