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SCORPION-xisa [38]
3 years ago
12

5208 divided by 4 in long division

Mathematics
1 answer:
Veronika [31]3 years ago
4 0

Answer:

 1 3 0 2

4 5 2 0 8

− 4      

 1 2    

− 1 2    

   0 0  

 −   0  

     0 8

   −   8

       0

Step-by-step explanation:


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Need help with questions 17 and 18
Pavlova-9 [17]
The answer to 17 is 18.6 and the 6 is repeating
6 0
3 years ago
A hovercraft takes off from a platform. Its height (in meters), xxx seconds after takeoff, is modeled by: h(x)=-2x^2+20x+48h(x)=
Ad libitum [116K]

the maximum height is the y-value of the vertex.

h(x) = -2x² + 20x + 48

      <em>  a=-2, b=20, c=48</em>

x = \frac{-b}{2a} = \frac{-20}{2(-2)} = \frac{-20}{-4} = 5

h(5) = -2(5)² + 20(5) + 48

      =  -50   +  100   + 48

      =          50         + 48

      =                98

Answer: 98 meters

8 0
3 years ago
Evaluate 9 – b when b = 8.
FromTheMoon [43]

Answer:

9 - b = ? 9 - 8 = 1 So, your answer is 1.

Step-by-step explanation:

5 0
3 years ago
A club has 10 members.
TEA [102]
That is the combination of 10 over 3, which is calculated as the quotient of factorials:
n!/k!(n-k)!
where n = 10 and k = 3:
= 10!/3!(10 - 3)!
= 10!/3!*7!
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6 0
3 years ago
Read 2 more answers
Listed below is data on profit and market capitalization for a sample of 15 different firms in U.S. Profit is the y variable and
MissTica

Answer:

Step-by-step explanation:

Hello!

You have two study variables:

Dependent variable

Y: Profit of the firm in the U.S.

Independent variable

X: Market capitalization of the firm

a.

See the scatterplot in the attachment.

Looking at the graphic it seems that there is a positive regression between the profit and the market capitalization, meaning that every time the market capitalization of the firm increases, the profit of this firm also increases. But not all the "firms" adjust linearly, so I wouldn't expect the regression to be powerful.

b.

The regression model is E(Yi)= α + βXi

Where the parameters of the model are α and β, these two parameters are to be estimated to estimate the regression equation. The estimator for α is a and the estimator for β is b:

a= Y[bar] - bX[bar]

b= [∑XY-(∑X*∑Y)/n]/[∑X²-(∑X)²/n]

I'll use a statistic software to calculate the estimated regression equation:

^Yi= a + bXi

^Yi= 325.89 + 0.07Xi

c.

You need to predict the value of Y (Profit) given a value of X= 70721.3 (million). To make this prediction you have to use the estimated equation:

^Yi= 325.89 + 0.07Xi

^Yi= 325.89 + 0.07(70721.3)= 5276.381

The predicted profit for a market capitalization value of 70,721.3 is 5276.381 million.

I hope this helps!

6 0
3 years ago
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