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wilcoxon_single.html
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<!DOCTYPE html>
<html>
<head>
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<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<title>EZ Statistics: Wilcoxon single sample</title>
<meta name="description" content="EZ Statistics wilcoxon single sample">
<link rel="stylesheet" href="style/stats.css">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.12.4/jquery.min.js"></script>
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</head>
<body>
<center><img class="round" src="style/logo.png" height="105"/></center>
<div style="text-align: right"><a href="index.html">Back to main page</a></div>
<h3 class="f18b">Wilcoxon signed-ranks, single sample for the mean</h3>
Tests the hypotheses:
<table>
<tr>
<th class="dark" width="110">H<sub>0</sub></th>
<td class="border">There is no difference between the mean of the sample and the specified mean </td>
</tr>
<tr>
<th class="dark">H<sub>1</sub> (two-tailed)</th>
<td class="border">The mean of the sample is different than the specified mean </td>
</tr>
<tr>
<th class="dark">H<sub>1</sub> (one-tailed)</th>
<td class="border">The mean of the sample is either less than or greater than the specified mean </td>
</tr>
</table>
<div class="smalltext">
<div class="label16">
<h3 class="f16"> Test Hypothesis</h3>
</div>
<br/>
<form action="" id="testtype">
<input class="type" type="radio" name="hyp" id="1" value="1" checked> <b>≠</b> The mean of sample is different than the specified mean (two-tailed)<br>
<input class="type" type="radio" name="hyp" id="2" value="2"> <b><</b> The mean of sample is less than the specified mean (one-tailed)<br>
<input class="type" type="radio" name="hyp" id="3" value="3"> <b>></b> The mean of sample is greater than the specified mean (one-tailed)
</form>
<div class="label16">
<h3 class="f16"> Data Entry</h3>
</div>
<br/>
<table>
<tr>
<td>Sample:</td>
<td><input class="sample" name="sampA" id="samp1" value="2128.7, 2679.1, 1317.2, 1001.3, 1107.6, 718.4, 787.4, 1562.3, 1356.9, 1153.2, 1167.1, 1387.5, 679.9, 1323.2, 788.4, 1153.6, 1423.3, 1122.6, 1644.3, 737.4"></td>
<tr/>
<tr>
<td>Mean:</td>
<td><input class="value" name="spmean" id="spmean" value="1000.0"></td>
<tr/>
<tr>
<td>Significance level α: </td>
<td><input class="value" name="alpha" id="alpha" value="0.05"></td>
</tr>
<tr>
<td>Upload CSV file:</td>
<td>
<input type="file" name="File Upload" id="txtFileUpload" accept=".csv" />
</td>
</tr>
</table>
<br>
<button class="test" onclick="javascript:run_wilcoxon_single()">Run Test</button>
<button class="clear" onclick="javascript:clear_fields(1)">Clear</button>
<div id="error">
</div>
<div id="test_results" style="display: none;">
<div class="label16">
<h3 class="f16"> Test Result</h3>
</div>
<br/>
<table class="border">
<thead>
<tr>
<th colspan=4 class="dark">Data Summary</th>
</tr>
<tr>
<th class="dark" width="70">Sample</th>
<th class="dark" width="40">N</th>
<th class="dark" width="100">Mean</th>
<th class="dark" width="100">Stdev</th>
</tr>
</thead>
<tbody>
<tr>
<th class="dark">A</th>
<td class="border" id="n1"> </td>
<td class="border" id="mean1"> </td>
<td class="border" id="stdev1"> </td>
</tr>
</tbody>
</table>
<br/>
<table class="border">
<thead>
<tr>
<th class="dark" width="550" colspan="2">Result</th>
</tr>
</thead>
<tbody>
<tr>
<td class="dark" width="130"><b>Mean<sub>A</sub> - mean:</b></td>
<td class="border" width="420" id="mean"> </td>
</tr>
<tr>
<td class="dark"><b>Significance level α:</b></td>
<td class="border" id="sign_level"> </td>
</tr>
<tr>
<td class="dark"><b>P-value:</b></td>
<td class="border" id="p"> </td>
</tr>
<tr>
<td class="dark"><b>Score:</b></td>
<td class="border" id="r"> </td>
</tr>
<tr>
<td class="dark"><b>Result:</b></td>
<td class="border" id="res"> </td>
</tr>
</tbody>
</table>
<div id="power">
<div class="label16">
<h3 class="f16"> Power Analysis <button class="help" onclick="javascript:toggle('pahelp')";>?</button></h3>
</div>
<div id="pahelp" style="display: none;">
<br>
The first table shows the minimum required sample sizes for low, medium and high statistical power respectively.
The second table shows the current statistical power for the samples and test type.
</div>
<br>
<table class="border">
<thead>
<tr>
<th colspan=3 class="dark">Required sample sizes</th>
</tr>
<tr>
<th class="dark" width="120">Power</th>
<th class="dark" width="150">Min sample size</th>
</tr>
</thead>
<tbody>
<tr>
<td class="border">Low (20%)</td>
<td class="border" id="n_low"> </td>
</tr>
<tr>
<td class="border">Medium (50%)</td>
<td class="border" id="n_medium"> </td>
</tr>
<tr>
<td class="border">High (80%)</td>
<td class="border" id="n_high"> </td>
</tr>
</tbody>
</table>
<br>
<table class="border">
<thead>
<tr>
<th class="dark" width="150">Current power</th>
</tr>
</thead>
<tbody>
<tr>
<td class="border" id="pwr"> </td>
</tr>
</tbody>
</table>
</div>
<div id="assumptions">
<div class="label16">
<h3 class="f16"> Check test assumptions <button class="help" onclick="javascript:toggle('ashelp')";>?</button></h3>
</div>
<div id="ashelp" style="display: none;">
<br>
The test does not require that the sample is normally distributed. If it is, consider using <a href="ttest_single.html">T-test for single sample</a> instead.
Note that the normality test is not entirely accurate for sample sizes under 20.
</div>
<br>
<div id="normtest">
<table class="border">
<thead>
<tr>
<th class="dark" width="550" colspan="2">Shapiro-Wilk test for normally distributed samples</th>
</tr>
</thead>
<tbody>
<tr>
<td class="dark" colspan="2"><center><b>Sample</b></center></td>
</tr>
<tr>
<td class="dark" width="100"><b>Result:</b></td>
<td class="border" id="sw_res_1"> </td>
</tr>
<tr>
<td class="dark"><b>P-value:</b></td>
<td class="border" id="sw_p_1"> </td>
</tr>
</tbody>
</table>
</div>
</div>
<div id="viz">
<div class="label16">
<h3 class="f16"> Data Visualization</h3>
</div>
<div id="chart"></div>
</div>
</div>
</div>
</body>
</html>