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172 lines
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HTML
172 lines
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<h1 class="center">Univariate and Bivariate Data</h1>
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<p class="center">Univariate: one variable, <br>
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Bivariate: two variables</p>
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<p class="center"> </p>
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<div class="words">
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<p><span class="center"><b>Univariate</b> means "one variable"</span> (one type of data)</p>
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</div>
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<div class="example">
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<h3>Example: Travel Time (minutes): <b>15, 29, 8, 42, 35, 21, 18, 42, 26</b></h3>
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<p>The variable is <b>Travel Time</b></p>
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</div>
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<div class="example">
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<p style="float:right; margin: 0 0 5px 10px;"><img src="../algebra/images/pups.jpg" width="239" height="125" alt="pups" /></p>
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<h3>Example: Puppy Weights</h3>
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<p>You weigh the pups and get these results:</p>
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<p class="center"> <b>2.5, 3.5, 3.3, 3.1, 2.6, 3.6, 2.4</b> </p>
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<p>The variable is <b>Puppy Weight</b></p>
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</div>
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<p>We can do lots of things with univariate data:</p>
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<ul>
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<li>Find a central value using <a href="../mean.html">mean</a>, <a href="../median.html">median</a> and <a href="../mode.html">mode</a></li>
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<li>Find how spread out it is using <a href="range.html">range</a>, <a href="quartiles.html">quartiles</a> and <a href="standard-deviation.html">standard deviation</a></li>
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<li>Make plots like <a href="bar-graphs.html">Bar Graphs</a>, <a href="pie-charts.html">Pie Charts</a> and <a href="histograms.html">Histograms</a></li>
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</ul>
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<p> </p>
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<div class="words">
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<p><span class="center"><b>Bivariate</b> means "two variables"</span>, in other words there are two types of data</p>
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</div>
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<p>With bivariate data we have <b>two</b> sets of related data we want to <b>compare</b>:</p>
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<div class="example">
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<h3>Example: Sales vs Temperature</h3>
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<p>An ice cream shop keeps track of how much ice cream they sell versus the temperature on that day. </p>
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<p class="center larger">The two variables are <b>Ice Cream Sales</b> and <b>Temperature</b>.</p>
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<p>Here are their figures for the last 12 days: </p>
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<table border="3" align="center" cellpadding="4">
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<tr align="center">
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<td colspan="2"><b><em>Ice Cream Sales vs Temperature</em><em></em></b></td>
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</tr>
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<tr align="center">
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<th>Temperature °C</th>
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<th>Ice Cream Sales</th>
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</tr>
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<tr align="center">
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<td>14.2°</td>
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<td>$215 </td>
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</tr>
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<tr align="center">
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<td>16.4°</td>
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<td> $325 </td>
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</tr>
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<tr align="center">
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<td>11.9° </td>
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<td>$185 </td>
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</tr>
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<tr align="center">
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<td>15.2° </td>
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<td>$332 </td>
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</tr>
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<tr align="center">
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<td>18.5° </td>
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<td>$406 </td>
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</tr>
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<tr align="center">
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<td>22.1° </td>
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<td>$522 </td>
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</tr>
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<tr align="center">
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<td>19.4° </td>
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<td>$412 </td>
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</tr>
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<tr align="center">
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<td>25.1° </td>
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<td>$614 </td>
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</tr>
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<tr align="center">
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<td>23.4° </td>
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<td>$544 </td>
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</tr>
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<tr align="center">
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<td>18.1°</td>
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<td> $421 </td>
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</tr>
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<tr align="center">
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<td>22.6°</td>
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<td> $445 </td>
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</tr>
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<tr align="center">
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<td>17.2°</td>
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<td>$408</td>
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</tr>
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</table>
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<p>And here is the same data as a <a href="scatter-xy-plots.html">Scatter Plot</a>:</p>
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<p class="center"><img src="images/scatter-ice-cream1.svg" alt="scatter plot ice cream sales vs temperature" style="max-width:100%" /></p>
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<p>Now we can easily see that <b>warmer weather</b> and <b>more ice cream sales</b> are linked, but the relationship is not perfect. </p>
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</div>
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<p>So with bivariate data we are interested in <b>comparing</b> the two sets of data and finding any <b>relationships</b>. </p>
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<p>We can use Tables, <a href="scatter-xy-plots.html">Scatter Plots</a>, <a href="correlation.html">Correlation</a>, Line of Best Fit, and plain old common sense.</p>
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<p> </p>
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<div class="related">
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<a href="index.html">Data Index</a>
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