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Vinil7 [7]
2 years ago
10

Can someone please help me.

Mathematics
2 answers:
emmasim [6.3K]2 years ago
6 0

Answer:

volume= 1/3πr²h

932.58=1/3×3.14×r²×11

3×932.58=<u>34.54×r</u><u>²</u><u> </u> ×3

3

<u>2,797.74</u> = <u>34.54×r²</u>

34.54. 34.54

√r²= √81

r=9mm

Anika [276]2 years ago
5 0

Answer:

Radius= 8.99 mm (9 mm)

Step-by-step explanation:

We use the formula for the volume of a cone which is

1/3 pi ×(radius)^2 *height

932.58 = (pi) × (11) ×(r^2/3)

Radius^2 = (932.58×3) / (11pi)

= 80.96m

Radius= 8.99mm

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An automobile dealer wants to see if there is a relationship between monthly sales and the interest rate. A random sample of 4 m
SVETLANKA909090 [29]

Answer:

a) y=-6.254 x +75.064  

b) r =-0.932

The % of variation is given by the determination coefficient given by r^2 and on this case -0.932^2 =0.8687, so then the % of variation explained by the linear model is 86.87%.

Step-by-step explanation:

Assuming the following dataset:

Monthly Sales (Y)     Interest Rate (X)

       22                               9.2

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       10                                10.4

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Part a

And we want a linear model on this way y=mx+b, where m represent the slope and b the intercept. In order to find the slope we have this formula:

m=\frac{S_{xy}}{S_{xx}}  

Where:  

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}  

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}  

With these we can find the sums:  

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=278.65-\frac{32.5^2}{4}=14.5875  

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i){n}}=696.9-\frac{32.5*97}{4}=-91.225  

And the slope would be:  

m=\frac{-91.225}{14.5875}=-6.254  

Nowe we can find the means for x and y like this:  

\bar x= \frac{\sum x_i}{n}=\frac{32.5}{4}=8.125  

\bar y= \frac{\sum y_i}{n}=\frac{97}{4}=24.25  

And we can find the intercept using this:  

b=\bar y -m \bar x=24.25-(-6.254*8.125)=75.064  

So the line would be given by:  

y=-6.254 x +75.064  

Part b

For this case we need to calculate the correlation coefficient given by:

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}  

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The % of variation is given by the determination coefficient given by r^2 and on this case -0.932^2 =0.8687, so then the % of variation explained by the linear model is 86.87%.

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Answer:

? = h

Step-by-step explanation:

v = lwh

v / wh = lwh / wh

v / wh = l

Hopefully this helped!

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