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      <title>Unit 3 Project  by Nayelli Arteaga</title>
      <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql</link>
      <description></description>
      <language>en-us</language>
      <pubDate>2024-03-04 20:55:10 UTC</pubDate>
      <lastBuildDate>2024-03-11 04:41:18 UTC</lastBuildDate>
      <webMaster>hello@padlet.com</webMaster>
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         <url></url>
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      <item>
         <title>Purpose: </title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2905098089</link>
         <description><![CDATA[<p>The purpose of the project is to learn how water usage impacts households. The data was collected from Mr. Bacchi's third period data science class. The information was collected from a range of students that live in Antelope, Roseville, and Citrus Heights. </p>]]></description>
         <enclosure url="" />
         <pubDate>2024-03-04 21:00:34 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2905098089</guid>
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      <item>
         <title>Question(s):</title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2905101606</link>
         <description><![CDATA[<p>Is there a relationship between household size and water usage? </p><p><br></p><p>What does the r value tell us in our least squares regression line?</p><p><br></p><p>Is this a spurious or causal relationship?</p><p><br></p><p> Are there any mediating or confounding variables that help explain the story? </p>]]></description>
         <enclosure url="" />
         <pubDate>2024-03-04 21:04:36 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2905101606</guid>
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         <title>Scatterplot Image: </title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2905111258</link>
         <description><![CDATA[<p>Explanation: This graph tells the story of the average amount of water used in each household that was collected from our class. It also shows how there are not many students that fall on the line of best fit. </p>]]></description>
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         <pubDate>2024-03-04 21:15:57 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2905111258</guid>
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      <item>
         <title>Equations </title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2906899680</link>
         <description><![CDATA[<p>Equation: <em>y</em>= 97.6 + 79.1x</p><p>Explanation of slope: The slope is 79.1 this means that 97.1 gallons is added to each person in the household. </p><p>Explanation of y-intercept: the y- intercept is 97.6 this shows that the data started with the number 97.6 gallons of water for even zero people. </p>]]></description>
         <enclosure url="" />
         <pubDate>2024-03-05 21:05:51 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2906899680</guid>
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      <item>
         <title>My Point On The Graph</title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2906904039</link>
         <description><![CDATA[<p>Explanation: The amount of gallons myself and my family uses (206) per day compared to the least square regression line if off. My household is not close to the line which shows the error that has occurred. </p>]]></description>
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         <pubDate>2024-03-05 21:11:37 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2906904039</guid>
      </item>
      <item>
         <title>Error and r^2 Values: </title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2908705173</link>
         <description><![CDATA[<p>r2= 0.26 and r^2= 0.068 They tell us the goodness of the fit on the Least square regression line and how accurate the points are to the line. </p><p>&nbsp;Data = Model + Error: The data shows how far the points are on the graph. Since majority of the points are farther away from the line this tells us that the model error is fairly high. </p>]]></description>
         <enclosure url="" />
         <pubDate>2024-03-06 20:53:38 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2908705173</guid>
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      <item>
         <title>Claim and Medating Variable: </title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2908729348</link>
         <description><![CDATA[<p>Claim: The household water usage is a causal relationship because I believe that we are missing the variable income. From the data shown I feel like those who have a lower income with a bigger household could tend to be more cautious with their water bill.</p><p><br></p><p>Mediating Variable: There are probably mediating variables because in order to connect the household size and water usage would probably be income. The reason I say this is because some people tend to be cautious especially if they have a bigger household when it comes to the use of water. They tend to put a cap on shower times to ensure their bill is not above what they can pay.&nbsp;</p>]]></description>
         <enclosure url="" />
         <pubDate>2024-03-06 21:21:53 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2908729348</guid>
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      <item>
         <title>Lateral Reading and What I learned:</title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2908732699</link>
         <description><![CDATA[<p>Lateral reading:  <em>There is evidence behind there being a relationship between population and state water usage. The reason is because it depends on the urban demand for that state. Certain states vary on where they are located. In California more specifically Southern California there are more businesses and residences this leads to more population which connects to a higher amount of water usage in specific states. Those states that are big cities tend to use more water rather than states which are smaller and more condensed.&nbsp;</em></p><p><br></p><p>What I learned: I learned that there are many aspects that need to be taken into consideration when looking at water usage for different states. There may be states that require for water for their cities to function. Let's take New York and Rhode Island they have a fairly different population difference so that means that their water usage is going to be drastically different. </p>]]></description>
         <enclosure url="" />
         <pubDate>2024-03-06 21:25:48 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2908732699</guid>
      </item>
      <item>
         <title>Model Information on City: </title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910325171</link>
         <description><![CDATA[<p>Explanation: I feel like we could not use this information that was collected because since only the Roseville City School districts data was collected there is still a large amount of the population that is not included. I feel like there would need to be a larger survey taken. With the data we were given we should not make predictions because we only surveyed </p><p><br></p><p>Roseville Water Usage Equation: </p><p>225+ 53.6<em>(154,817)</em></p><p>= 829,8416.2 gallons a day</p><p><br></p><p>Explanation: I feel like the total water usage for Roseville in this equation could be accurate for how much water a household uses. It would not work for finding out how much Roseville uses as a whole city. We only included the number of people in Roseville and plugged it into the equation. One aspect that was not accounted for is the business and other buildings that use water daily.</p>]]></description>
         <enclosure url="" />
         <pubDate>2024-03-07 19:46:59 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910325171</guid>
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      <item>
         <title>1. Questioning: </title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910330409</link>
         <description><![CDATA[]]></description>
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         <pubDate>2024-03-07 19:52:28 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910330409</guid>
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      <item>
         <title>2. Modeling:</title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910331801</link>
         <description><![CDATA[]]></description>
         <enclosure url="" />
         <pubDate>2024-03-07 19:53:53 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910331801</guid>
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      <item>
         <title>3. Analyzing:</title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910332752</link>
         <description><![CDATA[]]></description>
         <enclosure url="" />
         <pubDate>2024-03-07 19:54:58 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910332752</guid>
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      <item>
         <title>4. Communicating: </title>
         <author>nayelliarteaga1_7</author>
         <link>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910333835</link>
         <description><![CDATA[]]></description>
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         <pubDate>2024-03-07 19:56:06 UTC</pubDate>
         <guid>https://padlet.com/nayelliarteaga1_7/xxjr16m2r5htviql/wish/2910333835</guid>
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