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report.html
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<!DOCTYPE html>
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8"/>
<title></title>
<style type="text/css">
body, td {
font-family: sans-serif;
background-color: white;
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max-width: 800px;
margin: auto;
line-height: 20px;
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tt, code, pre {
font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace;
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font-size:2.2em;
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visibility: hidden;
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padding-right: 1em;
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tr, img {
page-break-inside: avoid;
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img {
max-width: 100% !important;
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@page :left {
margin: 15mm 20mm 15mm 10mm;
}
@page :right {
margin: 15mm 10mm 15mm 20mm;
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p, h2, h3 {
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</style>
</head>
<body>
<h1></h1>
<h2>Here's a report I made for my_data</h2>
<h3>Model summary</h3>
<!-- html table generated in R 3.0.3 by xtable 1.7-3 package -->
<!-- Thu Jun 05 09:09:19 2014 -->
<TABLE border=1>
<TR> <TH> </TH> <TH> Estimate </TH> <TH> Std. Error </TH> <TH> t value </TH> <TH> Pr(>|t|) </TH> </TR>
<TR> <TD align="right"> (Intercept) </TD> <TD align="right"> -2923.66 </TD> <TD align="right"> 893.01 </TD> <TD align="right"> -3.27 </TD> <TD align="right"> 0.00 </TD> </TR>
<TR> <TD align="right"> variableReference </TD> <TD align="right"> -6.72 </TD> <TD align="right"> 1.52 </TD> <TD align="right"> -4.42 </TD> <TD align="right"> 0.00 </TD> </TR>
<TR> <TD align="right"> Year </TD> <TD align="right"> 1.46 </TD> <TD align="right"> 0.44 </TD> <TD align="right"> 3.29 </TD> <TD align="right"> 0.00 </TD> </TR>
</TABLE>
<h3>Figure of restoration and reference by year</h3>
<p><img 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" alt="plot of chunk reg_fig"/> </p>
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