Answer: There is change of $0.9 billion in government expenditures.
Step-by-step explanation:
Since we know that
Marginal propensity to consume tells that the rate at which there is change in consumption due to change in income.
According to our situation, MPC is the change in amount of gross domestic product due to change in government expenditure.
So, it becomes,

Hence, there is change of $0.9 billion in government expenditures.
<span>x/900(pi) = 135/360
x = [900pi][135/360] = 337.5(pi) sq ft (area that receives water)
Hope this helps!
~{Oh Mrs.Believer}</span>
Answer:
There are 7123 boxes of ice cream left in the factory
Step-by-step explanation:
Initially produced in factory : 6911 boxes
135 boxes are sold, so the factory now has 6911 - 135 = 6776
347 more boxes are produced, so we add this number to what there was in the factory: 6776 + 347 = 7123
Question:
A solar power company is trying to correlate the total possible hours of daylight (simply the time from sunrise to sunset) on a given day to the production from solar panels on a residential unit. They created a scatter plot for one such unit over the span of five months. The scatter plot is shown below. The equation line of best fit for this bivariate data set was: y = 2.26x + 20.01
How many kilowatt hours would the model predict on a day that has 14 hours of possible daylight?
Answer:
51.65 kilowatt hours
Step-by-step explanation:
We are given the equation line of best fit for this data as:
y = 2.26x + 20.01
On a day that has 14 hours of possible daylight, the model prediction will be calculated as follow:
Let x = 14 in the equation.
Therefore,
y = 2.26x + 20.01
y = 2.26(14) + 20.01
y = 31.64 + 20.01
y = 51.65
On a day that has 14 hours of daylight, the model would predict 51.65 kilowatt hours