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  <titleInfo>
    <title>Applied regression analysis</title>
  </titleInfo>
  <name type="personal">
    <namePart>Draper, Norman R.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Smith, Harry.</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">xxu</placeTerm>
    </place>
    <place>
      <placeTerm type="text">New York</placeTerm>
    </place>
    <publisher>John Wiley and sons INC</publisher>
    <dateIssued>1998</dateIssued>
    <edition>3rd ed.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>xvii,706p.: ill.; 24cm.</extent>
  </physicalDescription>
  <tableOfContents>Contents: About the software -- Basic prerequisite knowledge -- Fitting a straight line by least squares -- Checking the straight line fit -- Fitting straight lines: Special topics -- Regression in matrix terms: Straight line case -- The general regression situation -- Extra sums of squares and tests for several parameters being zero -- Serial correlation in the residuals and the durbin-watson test -- More on checking fitted models -- Multiple regression: Special topics -- Bias in regression estimates, and expected values of mean squares and sums of squares -- On worthwhile regressions, big F's and R2 -- Models containing functions of the predictors including polynomial models -- Transformation of the response variable -- Dummy variables -- Selecting the best regression equation -- III-Conditioning in regression data -- Ridge regression -- Generalized linear models (GLIM) -- Mixture ingredients as predator variables -- The geometry of least sqaures -- More geometry of least squares -- Orthogonal polynomials and summary data -- Mutiple regression applied to analysis of variance problems -- An introduction to nonlinear estimation -- Robust regression -- Resampling procedures (bootstrapping).</tableOfContents>
  <note type="statement of responsibility">Norman R. Draper</note>
  <note>Includes index and bibliography.</note>
  <classification authority="lcc">QA278.2.D7</classification>
  <identifier type="isbn">9780471170822</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">140625</recordCreationDate>
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