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andrew11 [14]
1 year ago
7

The expression 11(1.022)^t11(1.022)

Mathematics
1 answer:
Lena [83]1 year ago
6 0

Answer: growth factor = 1.022

Step-by-step explanation:

The expression 11(1.022)^t is an exponential expression where the rate of increase is 2.2%

What 1.022 represent in this equation is the growth factor of per capita gross domestic product (GDP) of the US

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A rope is 66 feet long. It is cut into two pieces such that one piece is half the length of the other. What is the length of the
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So if one bit of the length, is half the size of the other bit then we can make the following equation, for x being the length of rope:

x + 2x = 66
3x = 66
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That is the length, of the smaller one (half the big one), so 2x = 44. Hence d) is your answer.

Hope I helped!
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Johann fits a linear model to a set of data. The line of best fit has the equation y=0.331986x+5.33286. The scatter plot with th
Rasek [7]

Answer:

6.33

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Here, we are asked to give a residual value at x = 3

This mean we are to predict the value of y at the point x= 3

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The line of best fit equation according to the question is;

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Substituting x here, we have

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Question asks to give answer to the nearest hundredth and that is 6.33

5 0
1 year ago
Mya is a performance athlete. She wants to use a function to represent the number of calories that she burns while training, whe
Lerok [7]

Answer:

The actual number of calories that Mya burned when she

trained for 30 minutes is 240.

Step-by-step explanation:

We have an exponential function that is the best fit for the number of calories Mya burns, in function of time (minutes).

The function is:

y=45.3e^{0.0548x}

Where y: calories burned, and x: training time.

Whenever we use regression models, we have a real value and a predicted value. The difference between them, the measure we want to minimize when we adjust with this typo of models, is called residual.

In the table is shown as one of the columns.

For example, for x=10 minutes, we have a real value of 30 and a predicted value of 78.36, so the residual becomes e=30-78.36=-48.36.

e=y-\hat y=30-78.36=-48.36

For x=30 minutes, we have only the residual, that has a value of 5.53. That means that the predicted value, which we can calculate, is 5.53 below the real value.

The predicted value for x=30 is:

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1 year ago
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