<p><strong><font size="3">Modern Experimental Design (Wiley Series in Probability and Statistics)<!--Element not supported - Type: 8 Name: #comment--><br/></font></strong>by <a href="http://www.amazon.com/exec/obidos/search-handle-url/102-6000963-8150550?%5Fencoding=UTF8&search-type=ss&index=books&field-author=Thomas%20P.%20Ryan"><font color="#003399">Thomas P. Ryan</font></a> (Author) <br/><a href="http://www.amazon.com/gp/reader/0471210773/ref=sib_dp_pt/102-6000963-8150550#reader-link"><img id="prodImage" height="240" alt="Modern Experimental Design (Wiley Series in Probability and Statistics)" src="http://ecx.images-amazon.com/images/I/41a6KwvjJ0L._BO2,204,203,200_PIsitb-dp-500-arrow,TopRight,45,-64_OU01_AA240_SH20_.jpg" width="240" border="0"/></a></p><li><b>Hardcover:</b> 593 pages </li><li><b>Publisher:</b> Wiley-Interscience; 1 edition (February 2, 2007) </li><li><b>Language:</b> English </li><li><strong>Review<br/></strong>"A very interesting and useful book…highly recommended." (<i>CHOICE</i>, August 2007) <p>"It is definitely nice to have such a book in the library." (<i>International Statistical Review, 2007)</i><br/>   <br/><br/><b>Book Description</b><br/>Suitable for use as either an undergraduate or graduate text, depending on the audience, this book covers a wide range of topics, including some that have received increased attention in recent years, such as hard-to-change factors, uniform designs, multiple response optimization, and Analysis of Means (ANOM). Conditional effects are emphasized and advocated for the first time as a routine and important method of analysis. There is a large number of cited references and extensive discussions of software capabilities, with considerable illustrative use of Design-Expert, in particular, JMP, and Minitab. </p></li><li><p> </p></li><li><p><strong><font size="4">contents </font></strong></p></li><li><p><strong>Preface.</strong><br/><strong><font color="#ff0000"><font color="#000000">1. Introduction.<br/>2. Completely Randomized Design.<br/>3. Designs that Incorporate Extraneous (Blocking) Factors.<br/>4. Full Factorial Designs with Two Levels.<br/>5. Fractional factorial Designs with Two-Levels.<br/>6. Designs With More Than Two Levels.<br/>8. Robust Designs.<br/>9. Split-Unit, Split-Lot, and Related Designs.<br/>10. Response Surface Designs.<br/>11. Repeated Measure Designs.<br/>12. Multiple Responses.<br/>13. Miscellaneous Design Topics.<br/>14. Tying It All Together.<br/>Subject Index.</font></font></strong></p></li><li><p><strong><font color="#ff0000">金币+1      </font></strong><strong><font color="#ff0000">魅力+5      </font></strong><strong><font color="#ff0000">积分+50</font></strong></p></li><li><p><strong><font color="#0000ff">版主评语：</font></strong><font color="#0000ff">非常之详细的内容说明！</font></p></li>

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