Giving the table below which shows <span>the percent increase of donations made on behalf of a non-profit organization for the period of 1984 to 2003.
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Year: 1984 1989 1993 1997 2001 2003
Percent: 7.8 16.3 26.2 38.9 49.2 62.1
The scatter plot of the data is attached with the x-axis representing the number of years after 1980 and the y-axis representing the percent increase <span>of donations made on behalf of a non-profit organization.
To find the equation for the line of regression where </span><span>the x-axis representing the number of years after 1980 and the y-axis representing the percent increase of donations made on behalf of a non-profit organization.
![\begin{center} \begin{tabular}{ c| c| c| c| } x & y & x^2 & xy \\ [1ex] 4 & 7.8 & 16 & 31.2 \\ 9 & 16.3 & 81 & 146.7 \\ 13 & 26.2 & 169 & 340.6 \\ 17 & 38.9 & 289 & 661.3 \\ 21 & 49.2 & 441 & 1,033.2 \\ 23 & 62.1 & 529 & 1,428.3 \\ [1ex] \Sigma x=87 & \Sigma y=200.5 & \Sigma x^2=1,525 & \Sigma xy=3,641.3 \end{tabular} \end{center}](https://tex.z-dn.net/?f=%5Cbegin%7Bcenter%7D%0A%5Cbegin%7Btabular%7D%7B%20c%7C%20c%7C%20c%7C%20c%7C%20%7D%0A%20x%20%26%20y%20%26%20x%5E2%20%26%20xy%20%5C%5C%20%5B1ex%5D%20%0A%204%20%26%207.8%20%26%2016%20%26%2031.2%20%5C%5C%20%20%0A%209%20%26%2016.3%20%26%2081%20%26%20146.7%20%5C%5C%20%0A13%20%26%2026.2%20%26%20169%20%26%20340.6%20%5C%5C%20%0A17%20%26%2038.9%20%26%20289%20%26%20661.3%20%5C%5C%20%0A21%20%26%2049.2%20%26%20441%20%26%201%2C033.2%20%5C%5C%20%0A23%20%26%2062.1%20%26%20529%20%26%201%2C428.3%20%5C%5C%20%5B1ex%5D%0A%5CSigma%20x%3D87%20%26%20%5CSigma%20y%3D200.5%20%26%20%5CSigma%20x%5E2%3D1%2C525%20%26%20%5CSigma%20xy%3D3%2C641.3%20%20%0A%5Cend%7Btabular%7D%0A%5Cend%7Bcenter%7D)
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Recall that the equation of the regression line is given by

where

and

Thus, the equation of the regresson line is given by

The graph of the regression line is attached.
Using the equation, we can predict the percent donated in the year 2015. Recall that 2015 is 35 years after 1980. Thus x = 35.
The percent donated in the year 2015 is given by

Therefore, the percent donated in the year 2015 is predicted to be 90.5
Answer:
B. Food market
Step-by-step explanation:
You typically buy all of your groceries at Grocery Mart. This week, your favorite cereal is on sale there, 4 boxes for $10. At Food Market, where you don’t typically shop, the same cereal is on sale for $2.25 a box. Based on price, which is the better value option?
A.Grocery Mart
B. Food Market
Grocery market:
4 boxes for $10
Unit price = cost / quantity
= $10 / 4 boxes
= $2.50 per box
Food market:
Price per box = $2.25
The better value option based on price is food market because it cost less to buy a box of cereal than grocery mart
Hi!
I have attached 2 images that should help you understand :)
First, look at the edits I made to the image you posted. I separated the shape into smaller shapes so that we can find the area of each individual one.
Let's start with the rectangle.
To find the area of a rectangle, multiply the width times the height.
10
· 4 = 40
Rectangle = 40cm
Next up, the red triangles.
I have included another image showing the triangles combined into rectangles. So we can find the area of the triangles just like we would rectangles!
(let me know if you don't understand how I found the width + height of the triangles)
5 · 10 = 50
Red triangles = 50cm
And finally, the green triangles.
8 · 7 = 56
Green triangles = 56cm
Add it all together and you get...
40 + 50 + 56 = 146
The answer to the question is
146cm.
Next time you are having trouble with something like this, picture the triangles as rectangles! :)
Answer:
a) 98.01%
b) 13.53\%
c) 27.06%
Step-by-step explanation:
Since a car has 10 square feet of plastic panel, the expected value (mean) for a car to have one flaw is 10*0.02 = 0.2
If we call P(k) the probability that a car has k flaws then, as P follows a Poisson distribution with mean 0.2,
a)
In this case, we are looking for P(0)
So, the probability that a car has no flaws is 98.01%
b)
Ten cars have 100 square feet of plastic panel, so now the mean is 100*0.02 = 2 flaws every ten cars.
Now P(k) is the probability that 10 cars have k flaws and
and
And the probability that 10 cars have no flaws is 13.53%
c)
Here, we are looking for P(1) with P defined as in b)
Hence, the probability that at most one car has no flaws is 27.06%