FOR EVERYONE WHO NEEDS IT: EDGENUITY 2020 PERFORMANCE TASK LOGISTIC MODELS ANSWERS. GOOGLE DOC IN REPLY

Please keep this question alive by giving me a random answer

1. Using the graphs, explain why a logistic model makes sense for the data. (4 points)

it's good to model and predict events. It allows to show a progression and gives us an idea of a trend that

may be happening based on the data given to us. A logistic function has a limiting value aswell.

2. Referring to the data table, complete the following steps to create a logistic growth model in the form

for the generation of wind in the state of Kansas.

a) According to the table, what is the initial value of the data and how can this information be translated to

an ordered pair? (2 points)

3.3834×10^305

(0, 3.3834×10^305)

b) Based on the current resources, there is an estimated limit of 28,000 thousand megawatt hours. How

does this fit into the standard form of the logistic model? (2 points)

It fits in as the C variable in the logistic model

c) Using your answers from parts a and b above, solve for the value of b in the logistic function. (4 points)

0.348992

d) Use your results from above and the data point for 2017 to find the value of r in the logistic function. (4

points)

If I plug in the original numbers without rounding...

R is .9866

_

e) Based on your above calculations, write the logistic equation that models the data. (2 points

(I have a picture of the equation in the doc.)

f) Use the equation above to algebraically determine the estimated generated wind energy in the year

2021 for Kansas. (2 points)

With my calculator I solved it by plugging 2021 for x

I got: 247186.17684

g) Explain how you could use a graphing tool to verify that your answer to the above problem is correct.

(2 points)

By looking at the 2021 on the y axis the I could find how much the estimated generated wind energy

would be at that time on the x axis.

Part 2: Find and apply a logistic regression model.

1. Use a graphing tool and the data provided in the table in Part 1 to write a logistic regression equation

for the generation of wind in the state of Kansas. (8 points)

I have mentioned this before, the logistic regression equation is the one with the red circle next

to it on the previous picture.

2. Is the regression equation you found a good model for the data? Explain. (2 points)

Yes because if I plug in a year for x in the equation, the same answer could be found on the

chart.

3. In Part 1, it was given that there is an estimated limit of 28,000 thousand megawatt hours based on the

current resources. How does this compare to the regression model and what could account for the

difference? (4 points)

The model no longer rises at about 28,000 instead it remains constant.

4. Based on the logistic regression model, in what year did the generation of energy by wind transition

from an increasing rate of change to a decreasing rate of change? Explain. (4 points

At about the year 2056.3 i noticed that it stopped increasing. This is because of the

limiting factor at about 28,000.

Part 3: Justify and interpret logistic models.

1. Compare the model you wrote in Part 1 with the regression model you found in Part 2. Which do you

think is a better model? Explain. (4 points)

I am not sure what Edgenuity is getting at, but it seems like my model is perfect.

2. Shown is a graph of net generation wind for Texas. The graph appears to take the shape of an

exponential function. Would you recommend using a logistic function, like the model for Kansas, or an

exponential function for this data? (3 points)

And exponential function would do better because a logarithmic function doesn’t fit the shape , of this

graph. An expontential function would work because it’s shape matches more to that of the one on this

graph.

"Wind Energy in Texas." Wind Exchange. Accessed September 25, 2019. https://windexchange. energy. gov/states/tx.

Student Guide (continued)

Copyright © Edgenuity Inc.

3. One logistic equation to model the California data is the equation found using regression.

Which state, Kansas or California, had a greater number of years in which the growth of wind energy was

increasing? Explain. (3 points)

Kansas, because Kansas in the chart has numbers constantly rising, while california was inconsistent,

going up and down.