# data[].attributes.body
-r & r^2 value show moderate to weak correlation
-Increasing
-Spurious relationship
-Moderating variables
The purpose of the LSRL is to try and show the correlation between the 2 variables, so far it is showing that the correlation is pretty weak. There is possibly no direct relationship, meaning there are other variables impacting.
- we predict that 69.98 gallons of water are used by 1 person
- we predict that 379.8 people use 0 gallons of water

# data[].attributes.body
-r & r^2 values show a moderate to weak correlation
-Increasing
-spurious relationship
-moderating variables
-The purpose of the LSRL is to show if there is a correlation between the 2 variables. This data set shows that there is not a strong relationship, meaning there are other variables impacting.
-We predict that 54.1 gallons of water are used for 1 person
-We predict that 338.8 people use 0 gallons of water

# data[].attributes.body
-r and r^2 value show weak to moderate correlation
-Increasing
-Spurious relationship
-Moderating variables
-The purpose of the LSRL is to show if there is a correlation between the 2 variables. This data set shows that the relationship between the variables are weak and there are other things impacting it.
-We predict that 53.6 gallons of water are used for 1 person
-We predict that 225 people use 0 gallons of water

# data[].attributes.body
-r and r^2 values show a really strong correlation
-Increasing
-causal relationship
-The purpose of the LSRL is to show if there is a correlation between the 2 variables, in this data set it shows that there actually is.
-We predict that 132.7 gallons of water are used for 1 person
-We predict that 76279729.4 people use 0 gallons of water