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      <title>Household Water Usage story by Kurt Collin Javier</title>
      <link>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv</link>
      <description>Claim: Many people consume more water </description>
      <language>en-us</language>
      <pubDate>2024-03-07 18:22:53 UTC</pubDate>
      <lastBuildDate>2024-03-14 17:04:28 UTC</lastBuildDate>
      <webMaster>hello@padlet.com</webMaster>
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         <title>Modeling</title>
         <author>kurtcollinjavier1_7</author>
         <link>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2915868868</link>
         <description><![CDATA[<ul><li><p><strong>What can you see from the scatterplot?</strong></p><p>-The scatterplot was unorganized but somehow increasing.</p></li></ul><p><br></p><ul><li><p><strong>What is the purpose of the LSRL and how does it relate to the actual data points?</strong></p></li></ul><p>      -The LSRL is the best fit line to see if there's a relationship within variable A and variable B. This connects to the data by understanding if there is a correlation between how many people is the household and how much water does our household use per day</p><p><br></p><ul><li><p><strong>Explain what the slope &amp; y-intercept mean in context from your line of best fit.</strong></p></li></ul><p>    - An individual consumes 96 gallons of water per day. Within those 96 gallons of water. a household uses water in the way they need it 47 times.</p><p><br></p><ul><li><p><strong>Add your YOUR household to the scatterplot, circle your “point”.&nbsp; How does the number of gallons from YOUR household compare to the least square regression line model you found? Explain what this means (Find the residual and use it in your answer)</strong></p><p>- The regression line didn't touch my household data which means that my household consume a lot of water, however I think that my residual is reasonable because there are machines that uses water in my house so for four people in the household a residual of 404.08 gallons per day could be reasonable.</p></li></ul><p><br></p><ul><li><p><strong>What do the r &amp; r<sup>2</sup> values tell you about how well the Least Square Regression Line (LSRL) fits the data?&nbsp;</strong></p><p>-The R value is meaning full because 0.776 is a great r value for social science while r squared was also reasonable because <em> </em>0.602 is more than 0.35 which means so it means that there is a strong correlation between the two variabl3</p></li></ul><p><br></p><p><br></p>]]></description>
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         <pubDate>2024-03-12 15:56:46 UTC</pubDate>
         <guid>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2915868868</guid>
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      <item>
         <title>Equation</title>
         <author>kurtcollinjavier1_7</author>
         <link>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2915873407</link>
         <description><![CDATA[<p><em>ŷ</em> = 47.7805 + 96.8372<em>x</em></p><p><em>r squared = </em>0.602</p><p>r value = 0.776</p>]]></description>
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         <pubDate>2024-03-12 15:59:58 UTC</pubDate>
         <guid>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2915873407</guid>
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         <title>Residual </title>
         <author>kurtcollinjavier1_7</author>
         <link>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2915908425</link>
         <description><![CDATA[<p>Predicted = 407.8(Estimate)</p><p>Actual = 407.8 = 96.8372<em>x + </em>47.7805 </p><p><em>      - </em>47.7805 = 96.8372<em>x</em></p><p><em>      360.0195  / </em>96.8372<em>x</em></p><p><em>=3.71 or 3.72</em></p><p><em>Residual = 3.72 - 407.8 = 404.08</em></p><p><br></p><p><br></p>]]></description>
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         <pubDate>2024-03-12 16:26:51 UTC</pubDate>
         <guid>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2915908425</guid>
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      <item>
         <title>Analyzing</title>
         <author>kurtcollinjavier1_7</author>
         <link>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2916068156</link>
         <description><![CDATA[<ul><li><p><strong>What statement(s) about water usage and number of people in a household can you make?&nbsp;Use supporting evidence for your statement(s).</strong></p><p>-Based on the scatter plot some household with less people consumes more with household with many people.</p><p><br></p></li><li><p><strong>Are there any confounding variables that led to your personal household’s residual?</strong></p><p>-Confounding Variables: Amenities in the house that uses water(Pool), the use of things that consume water ex: Washing machine, foset, hose for a garden, shower etc..</p><p><br></p></li><li><p><strong>What story do you think our bivariate data model tells?</strong>&nbsp;&nbsp;</p><p>-The bivariate data shows that there is a correlation between household and the water usage by showing us that people need to use water everyday and some people use water extremely or thrifty.</p><p><br></p></li><li><p><strong>Use your data science and detective thinking skills to make your final claimed statement about what you learned from our household water usage has been answered.&nbsp; Be sure to explain thoroughly.</strong></p><p>-There is a relationship between how many people in a household and how much water does a household use per day. </p><p>-If there's no people in a household there is zero consumption of water, if there is one people, there is less consumption of water, if there's a lot of people, there is a lot of consumption of water. However, the majority of the household with more people consumes less water while some less household consumes more water than with more people household. </p></li></ul>]]></description>
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         <pubDate>2024-03-12 18:27:05 UTC</pubDate>
         <guid>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2916068156</guid>
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      <item>
         <title>Communicating</title>
         <author>kurtcollinjavier1_7</author>
         <link>https://padlet.com/kurtcollinjavier1_7/53ex6zh32w09nkbv/wish/2919203254</link>
         <description><![CDATA[<ul><li><p><strong>Can we use this information to predict the water usage for our whole school or our entire district? </strong></p><p> -We could use this data to examine our school or district data because it's useful by identifying the behavior of people when it comes to water.</p><p><br></p></li><li><p><strong>What about our city or state?&nbsp; Should we make water usage predictions based on our district model?&nbsp;What about the model of all the “city data”?&nbsp; Explain.</strong></p><p> -No, we could not make any predictions based on our district model because if we compare to the whole city or state, it wouldn't be accurate or even a little bit the same in our district data because our district data was does not have the same data with the other city/state.</p><p><br></p></li><li><p><strong>How much water would our city be predicted to use per day?&nbsp; How much water would our state be predicted to use per day?&nbsp; Are these predictions aligned with the other states similar to CA?</strong></p></li></ul><p>       -According to <a rel="noopener noreferrer nofollow" href="http://sacramentocityexpress.com"><em>sacramentocityexpress.com</em></a><em> </em>the water usage in our city is estimated 80 million gallons per day. In the whole state while California's have a 36 billion gallons per day. This could be similar or similar to other states because some states have less or more population than California but when it comes to water it could be the same or different to because it just really depends on how people is using water.</p><p><br></p><ul><li><p><strong>Explain if the city and state predictions are reasonable and what other variables might be affecting water usage for the state.</strong></p><p>-It is reasonable because considering that there are some outliers in the city or state data when it comes to building the estimated data up, we could assume that a household can be not using water that much due to bill while some might use it a lot due to amenities or some things that could include water a lot in their daily lives.</p></li></ul>]]></description>
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         <pubDate>2024-03-14 15:44:54 UTC</pubDate>
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