The graph shows the data points in the table and the exponential regression model associated with the data. A 2-column table wit
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Down payment is 20% of the price of the home. Since the couple saved $35,000, and assuming they will pay the whole money as down payment, the highest priced home they can get is a price whose 20% is $35,000.
We can setup an equation in x (being the price of home) to get the price of the most expensive home they can buy.
<em>Which number (x) , multiplied by 20%, is equal to $35,000?</em>
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So, the most expensive house they can buy is worth $175,000.
ANSWER: $175,000
Alright, so the rate of change is the same thing as the slope, so we can find this by using the slope formula (which I took a picture of because it's super messy to type it out like this)
Now that we know the slope formula, we need to find the x values and the y values to plug into the equation. We'll say that the years are our x values and the money spent (in billions) are our y values. Now that we've set up an axis, we can create points! Our points would be (2000, 1243) and (2005, 1838)
Now we can plug our points into our equations! On the top of our equation, we'll put (1838-1243), and on the bottom we'll put (2005-2000). When we simplify that, we end up with 595/5, which simplifies to 119. Now we know that the rate of change for the credit cards was 119 billion!
Now that we know the slope formula, we need to find the x values and the y values to plug into the equation. We'll say that the years are our x values and the money spent (in billions) are our y values. Now that we've set up an axis, we can create points! Our points would be (2000, 1243) and (2005, 1838)
Now we can plug our points into our equations! On the top of our equation, we'll put (1838-1243), and on the bottom we'll put (2005-2000). When we simplify that, we end up with 595/5, which simplifies to 119. Now we know that the rate of change for the credit cards was 119 billion!