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  <titleInfo>
    <title>Statistics for sports and exercise science</title>
  </titleInfo>
  <name type="personal">
    <namePart>Newell, John</namePart>
    <namePart type="termsOfAddress">Dr</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Aitchison, Tom.</namePart>
  </name>
  <name type="personal">
    <namePart>Grant, Stanley.</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">bibliography</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">enk</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Harlow, England</placeTerm>
    </place>
    <publisher>Pearson Education Limited</publisher>
    <dateIssued>c2010</dateIssued>
    <dateIssued encoding="marc">2010</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>p. cm.</extent>
  </physicalDescription>
  <tableOfContents>Discovering statistics -- Why bother with statistics in sports science? -- The basic approach -- Some basic vocabulary -- More on variables -- Some underlying ideas -- Examples of case studies -- Summary -- Designing a study -- Introduction -- Collecting the data (sampling) -- Sources of variablility -- Other important issues in designing a study -- Summary -- Summarising and displaying data -- Introduction -- Numerical summaries for continuous variables -- Graphical methods for continuous variables -- Single-sample problems (independent data) -- Designs involving between-subject factors only -- Within-subject designs (dependent data) -- Designs with between- and within-subject factors -- Between-subject designs incorporating a covariate -- Modelling relationships (correlation and regression) -- Summary -- Technical appendix -- Estimating parameters -- Introduction -- Interval estimation -- Interval estimation for a population mean -- Comparing two population means (the simplest between-subject design) -- Interval estimation for paired data (the simplest within-subject design) -- One between- and one within-subject factor (each at two levels) -- Prediction and tolerance intervals -- What if the normality assumption is questionable? -- Summary.</tableOfContents>
  <note type="statement of responsibility">John Newell, Tom Aitchison, Stanley Grant.</note>
  <note>Includes bibliographical references and index.</note>
  <subject authority="lcsh">
    <topic>Sports sciences</topic>
    <topic>Statistical methods</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Sports sciences</topic>
    <topic>Research</topic>
  </subject>
  <classification authority="lcc">GV558 .N475 2010</classification>
  <classification authority="ddc" edition="22">613.7/1</classification>
  <identifier type="isbn">9780132042543 (pbk. : alk. paper)</identifier>
  <identifier type="lccn">2009016104</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">090416</recordCreationDate>
    <recordIdentifier>15701794</recordIdentifier>
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