# data[].attributes.body
Is there a relationship between household size and water usage?

# data[].attributes.body
There is generally a week correlation between the data

# data[].attributes.headline
What's the equation for the least squares regression line?

# data[].attributes.subject
What's the equation for the least squares regression line?

# data[].attributes.body
y=44.7x+249

# data[].attributes.headline
Explain what the slope & y-intercept mean in context from your line of best fit

# data[].attributes.subject
Explain what the slope & y-intercept mean in context from your line of best fit

# data[].attributes.body
The 44.7 in the equation means that you are going up by 44.7 and over 1 while the 249 in the equation represents where the line of best fit crosses the y axis

# data[].attributes.headline
Show where YOUR household is on the scatterplot by circling your “point”.  How does the number of gallons from YOUR household compare to the least square regression line model you found (think residual)?  Explain what this means.

# data[].attributes.subject
Show where YOUR household is on the scatterplot by circling your “point”.  How does the number of gallons from YOUR household compare to the least square regression line model you found (think residual)?  Explain what this means.

# data[].attributes.body
Its right on the line of best fit telling me that my households water usage is right where its supposed to be according to the class data

# data[].attributes.body
The r2 values tell me about whether or not the correlation is strong or week between the data and also tells me how far away the data points are away from the line of best fit

# data[].attributes.headline
Statement about water compared to household usage

# data[].attributes.subject
Statement about water compared to household usage

# data[].attributes.body
the points on the scatterplot vary so much which you can also see by looking at the r2 which is 20 percent showing that the data is not correlating based on the varying data due to the difference in water usage affected by number of people in the home

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Are there any confounding or mediating variables that led to your decision?

# data[].attributes.subject
Are there any confounding or mediating variables that led to your decision?

# data[].attributes.body
yes because we have outside information on the data such as how many showers are taken a day etc.

# data[].attributes.headline
Total amount of water used each day and how many showers taken each day

# data[].attributes.subject
Total amount of water used each day and how many showers taken each day

# data[].attributes.body
Strong, I did since i think showers would impact a lot

# data[].attributes.headline
Water usage and how long the kitchen sink is on

# data[].attributes.subject
Water usage and how long the kitchen sink is on

# data[].attributes.body
Weak, Yes since the sink isn't on for very long

# data[].attributes.headline
After doing some lateral reading of online articles or data what did you further learn?

# data[].attributes.subject
After doing some lateral reading of online articles or data what did you further learn?

# data[].attributes.body
Showers account for 20 percent of our indoor water usage which did confirm my hypothesis since I said i felt as though showers had a big impact and the longer the shower the more impact is has on the water usage while the kitchen sink has a much smaller impact since it doesn't come close to the amount of water used to shower

# data[].attributes.headline
Use your data science and detective thinking skills to make your final claimed statement about what you learned from household water usage. Be sure to explain thoroughly.

# data[].attributes.subject
Use your data science and detective thinking skills to make your final claimed statement about what you learned from household water usage. Be sure to explain thoroughly.

# data[].attributes.body
Water usage and showers have a strong correlation since showers make up for more than 20 percent of indoor water usage so the more showers take or the longer they greater impact it has on household water usage

# data[].attributes.headline
Can we use this information to predict the water usage for larger households or even our school, city or state?  Should we make these predictions based on our model?  Explain why or why not?

# data[].attributes.subject
Can we use this information to predict the water usage for larger households or even our school, city or state?  Should we make these predictions based on our model?  Explain why or why not?

# data[].attributes.body
No we cannot since there are plenty of places such as the mall, restaurants, and gyms that use water regularly throughout the day but are not considered a household so they're not included within this data making it inaccurate

# data[].attributes.headline
Show your calculations to find our city’s (Roseville) water usage for a day. Do you think this value is reasonable?  Explain why or why not?

# data[].attributes.subject
Show your calculations to find our city’s (Roseville) water usage for a day. Do you think this value is reasonable?  Explain why or why not?

# data[].attributes.body
y=.133(162,674) +76280

Answer: 21711922

# data[].attributes.headline
Me when I saw all the work you made me do for this section alone

# data[].attributes.subject
Me when I saw all the work you made me do for this section alone