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zarbspace committed Jun 18, 2024
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38 changes: 6 additions & 32 deletions docs/intro.html
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<script src="site_libs/quarto-nav/quarto-nav.js"></script>
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</li>
<li>publishing models.</li>
</ul>
<p>We provide improved guidance on what a proportionate approach to assurance means (in chapter X) and have made the whole guide applicable to all types of analysis.</p>
<p>We provide improved guidance on what <a href="https://best-practice-and-impact.github.io/aqua_book_revision/proportionality.html">a proportionate approach to assurance means</a> and have made the whole guide applicable to all types of analysis.</p>
<section id="who-is-the-aqua-book-for" class="level2" data-number="1.1">
<h2 data-number="1.1" class="anchored" data-anchor-id="who-is-the-aqua-book-for"><span class="header-section-number">1.1</span> Who is the AQuA Book for?</h2>
<p>In this edition we have tried to make our guidance relevant to anyone who commissions, uses, undertakes or assures analysis. It is about the whole process of producing analysis that is fit for purpose and not just about the checks after the analysis has been completed.</p>
<p>We would like to see analysts from all backgrounds using this book. Our intended audience includes;</p>
<p>We would like to see analysts from all backgrounds using this book, especially those producing analysis, evidence and research to support decision making in government. Our intended audience includes:</p>
<ul>
<li>customers – helping you to get the most out of your commission;</li>
<li>members of the government analytical professions. This might include:
<li>Customers – helping you to get the most out of your commission;</li>
<li>Members of the government analytical professions. This might include:
<ul>
<li>operational researchers, statisticians and economists;</li>
<li>geographers;</li>
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<li>data scientists developing advanced analytics;</li>
<li>and anyone else carrying out analysis.</li>
</ul></li>
<li>senior leaders with an interest in analytical assurance.</li>
<li>Senior leaders with an interest in analytical assurance.</li>
</ul>
</section>
<section id="why-should-i-pay-attention-to-this-guidance" class="level2" data-number="1.2">
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</li>
<li><strong>Professional pride in your work.</strong></li>
</ul>
<p>(For information, not part of the draft: example of a citation reference linked to references.bib file: See <span class="citation" data-cites="knuth84">Knuth (<a href="references.html#ref-knuth84" role="doc-biblioref">1984</a>)</span> for additional discussion of literate programming. )</p>


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<div id="ref-knuth84" class="csl-entry" role="listitem">
Knuth, Donald E. 1984. <span>“Literate Programming.”</span> <em>Comput. J.</em> 27 (2): 97–111. <a href="https://doi.org/10.1093/comjnl/27.2.97">https://doi.org/10.1093/comjnl/27.2.97</a>.
</div>
</div>
</section>
<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
<hr>
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6 changes: 3 additions & 3 deletions docs/search.json
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"href": "intro.html",
"title": "1  Introduction",
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"text": "1.1 Who is the AQuA Book for?\nIn this edition we have tried to make our guidance relevant to anyone who commissions, uses, undertakes or assures analysis. It is about the whole process of producing analysis that is fit for purpose and not just about the checks after the analysis has been completed.\nWe would like to see analysts from all backgrounds using this book. Our intended audience includes;",
"text": "1.1 Who is the AQuA Book for?\nIn this edition we have tried to make our guidance relevant to anyone who commissions, uses, undertakes or assures analysis. It is about the whole process of producing analysis that is fit for purpose and not just about the checks after the analysis has been completed.\nWe would like to see analysts from all backgrounds using this book, especially those producing analysis, evidence and research to support decision making in government. Our intended audience includes:",
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"text": "customers – helping you to get the most out of your commission;\nmembers of the government analytical professions. This might include:\n\noperational researchers, statisticians and economists;\ngeographers;\nfinance professionals making spending forecasts;\nactuaries;\nsocial researchers carrying out qualitative research;\ndata scientists developing advanced analytics;\nand anyone else carrying out analysis.\n\nsenior leaders with an interest in analytical assurance.",
"text": "Customers – helping you to get the most out of your commission;\nMembers of the government analytical professions. This might include:\n\noperational researchers, statisticians and economists;\ngeographers;\nfinance professionals making spending forecasts;\nactuaries;\nsocial researchers carrying out qualitative research;\ndata scientists developing advanced analytics;\nand anyone else carrying out analysis.\n\nSenior leaders with an interest in analytical assurance.",
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"title": "1  Introduction",
"section": "1.2 Why should I pay attention to this guidance?",
"text": "1.2 Why should I pay attention to this guidance?\nHere are a few reasons why.\n\nYour analytical insights will be used for major decisions and operations. You need to do your best to get them right, thus minimising the risk of being complicit in causing operational, business or reputational damage;\nTrust is hard to obtain but easy to lose. A simple error that could have been prevented by assurance could lead to your and your team’s work being doubted;\nPrevention is better than cure. Analysis is more likely to be right first time when you consider quality from the start. Having appropriate quality assurance in place helps to manage mistakes, handle changes to requirements and ensure appropriate re-use;\nDelivering quality analysis provides the confidence that is needed for transparency and public openness;\nAssurance is required for audit purposes2; and\n\nProfessional pride in your work.\n\n(For information, not part of the draft: example of a citation reference linked to references.bib file: See Knuth (1984) for additional discussion of literate programming. )\n\n\n\n\nKnuth, Donald E. 1984. “Literate Programming.” Comput. J. 27 (2): 97–111. https://doi.org/10.1093/comjnl/27.2.97.",
"text": "1.2 Why should I pay attention to this guidance?\nHere are a few reasons why.\n\nYour analytical insights will be used for major decisions and operations. You need to do your best to get them right, thus minimising the risk of being complicit in causing operational, business or reputational damage;\nTrust is hard to obtain but easy to lose. A simple error that could have been prevented by assurance could lead to your and your team’s work being doubted;\nPrevention is better than cure. Analysis is more likely to be right first time when you consider quality from the start. Having appropriate quality assurance in place helps to manage mistakes, handle changes to requirements and ensure appropriate re-use;\nDelivering quality analysis provides the confidence that is needed for transparency and public openness;\nAssurance is required for audit purposes2; and\n\nProfessional pride in your work.",
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