https://wiki.cs.earlham.edu/index.php?title=Decision_making_Based_on_Evidence_-_Emily&feed=atom&action=historyDecision making Based on Evidence - Emily - Revision history2024-03-29T12:00:54ZRevision history for this page on the wikiMediaWiki 1.32.1https://wiki.cs.earlham.edu/index.php?title=Decision_making_Based_on_Evidence_-_Emily&diff=13349&oldid=prevAdmin: Blanked the page2012-08-27T11:24:21Z<p>Blanked the page</p>
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 11:24, 27 August 2012</td>
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<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"># Have an idea or causal theory that directs the gathering and assessment of evidence. Follow these tips:</del></div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">*put data in an appropriate context for assessing cause and effect </del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">*make good quantitative comparisons including examining why something did not occur</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">*consider alternate explanations </del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">*assess possible errors</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">['''Visual Explanations''', page 29-36. emp]</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"># Multiples are useful when analyzing multi-variable processes. Allows for the combination of detail and overview on one display. Combine multiples with narrative text and images for monitoring data-rich processes. ['''Visual Explanations''', page 110. emp]</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"># Graphic displays should have simplicity of design and complexity of data. This makes comprehension easier, while still maintaining a large amount of data. Avoid unnecessary symbols and decorations, while showing detail. [''' The Visual Display of Quantitative Information''', page 177. emp]</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline"># Avoid “cherry-picking” by presenting data in a way that is not skewed for a specific benefit. Ask questions such as, “Do the findings grow from the evidence or from the process of evidence construction?”, “Would the process survive a research audit?”, and “Are the findings too good to be true?” [''' Beautiful Evidence''', page 144-147. emp]</del></div></td><td colspan="2"> </td></tr>
</table>Adminhttps://wiki.cs.earlham.edu/index.php?title=Decision_making_Based_on_Evidence_-_Emily&diff=13324&oldid=prevEmpavlo10: Created page with "# Have an idea or causal theory that directs the gathering and assessment of evidence. Follow these tips: *put data in an appropriate context for assessing cause and effect *mak..."2012-08-26T18:39:34Z<p>Created page with "# Have an idea or causal theory that directs the gathering and assessment of evidence. Follow these tips: *put data in an appropriate context for assessing cause and effect *mak..."</p>
<p><b>New page</b></p><div># Have an idea or causal theory that directs the gathering and assessment of evidence. Follow these tips:<br />
*put data in an appropriate context for assessing cause and effect <br />
*make good quantitative comparisons including examining why something did not occur<br />
*consider alternate explanations <br />
*assess possible errors<br />
['''Visual Explanations''', page 29-36. emp]<br />
# Multiples are useful when analyzing multi-variable processes. Allows for the combination of detail and overview on one display. Combine multiples with narrative text and images for monitoring data-rich processes. ['''Visual Explanations''', page 110. emp]<br />
# Graphic displays should have simplicity of design and complexity of data. This makes comprehension easier, while still maintaining a large amount of data. Avoid unnecessary symbols and decorations, while showing detail. [''' The Visual Display of Quantitative Information''', page 177. emp]<br />
# Avoid “cherry-picking” by presenting data in a way that is not skewed for a specific benefit. Ask questions such as, “Do the findings grow from the evidence or from the process of evidence construction?”, “Would the process survive a research audit?”, and “Are the findings too good to be true?” [''' Beautiful Evidence''', page 144-147. emp]</div>Empavlo10