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vredina [299]
2 years ago
7

What is the formula of the curved surface of a cylinder?

Mathematics
1 answer:
VladimirAG [237]2 years ago
3 0

Answer:

2πr × h = 2πrh

Step-by-step explanation:

that is the formula for a curved surface of a cylinder 2πr × h = 2πrh.

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Y+7x9;x=-1,0,3
DanielleElmas [232]

Answer:

Step-by-step explanation:

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3 0
3 years ago
3-14 plzzz except #13 20 points!
Marianna [84]
#3: 15

#4: 13.2

#5: 5.44 (curious as to how you guessed 7)

#6: 7

#7: 7.3

#8: 15

#9: You'd round 0.9 to 1 and 3.78 to 4. 4/1 = 4

#10: Round 2.5 to 3. 36/3 = 12

#11: If they want you to round 0.25 down to 0, then 7/0 is undefined. 

#12: 9.5 rounds to 10 142.5 rounds to 143. 143/10 = 14.3

#14: 24.8 cm divided by 175 = approximately 0.1417 cm per year. Round that up to approximately 0.14 per year. 


4 0
3 years ago
Determine the center of the circle from the equation.
allsm [11]

Answer:

A. (2, -3).

Step-by-step explanation:

The first step is to complete the square on the terms in x and the terms in y:

x² - 4x +4 +y² +6y + 9 =4

= (x - 2)² - 4 + (y + 3)² - 9 + 4 + 9 = 4

= = (x - 2)² + (y + 3)² - 9 + 9 - 4 + 4 = 4

=  (x - 2)² - (y + 3)²  = 4.

So the centre is at (2, -3).

7 0
3 years ago
Victoria counts this week's food donations at a pet shelter. There are 16 full cases of canned food. There are 4 cases of canned
Kryger [21]

Answer:

HOPE THIS HELPS YOU!!!! :D

Step-by-step explanation:

Could you help me with my work?

5 0
3 years ago
Helpi accendintly made the question I just posted 5 points but this one is 50
Umnica [9.8K]

(a) For any probability distribution, the total probability must be 1. That is, the area under the probability density curve must be equal to 1.

The empirical rule for normal distributions says

• approximately 68% of the distribution lies within 1 standard deviation of the mean

• approx. 95% lies within 2 s.d. of the mean

• approx. 99.7% lies within 3 s.d. of the mean

In this case, with mean 3500 and s.d. 470, this translates to

• Pr(3500 - 470 < X < 3500 + 470) = Pr(3030 < X < 3970) ≈ 0.68

• Pr(3500 - 2*470 < X < 3500 + 2*470) = Pr(2560 < X < 4440) ≈ 0.95

• Pr(3500 - 3*470 < X < 3500 + 3*470) = Pr(2090 < X < 4910) ≈ 0.997

Continuous probability distributions also have the property that

Pr(a < X < b) = Pr(a < X < c) + Pr(c < X < b)

if a < c < b.

Combining all these properties, we can find the probabilities for each of the 8 regions in the graph to be (from left to right)

• Pr(-∞ < X < 2090) ≈ (1 - 0.997)/2 ≈ 0.0015

• Pr(2090 < X < 2560) ≈ (1 - 0.95 - 2*0.0015)/2 ≈ 0.0235

• Pr(2560 < X < 3030) ≈ (1 - 0.68 - 2*0.0235 - 2*0.0015)/2 ≈ 0.135

• Pr(3030 < X < 3500) ≈ 0.68/2 ≈ 0.34

and since the distribution is symmetric about its mean, we already know the remaining probabilities,

• Pr(3500 < X < 3970) ≈ 0.34

• Pr(3970 < X < 4440) ≈ 0.135

• Pr(4440 < X< 4910) ≈ 0.0235

• Pr(4910 < X < ∞) ≈ 0.0015

(b) Per the rule, 99.7% of babies would weight between 2090 and 4910 grams.

(c) The proportion of babies weighing less than 3030 grams is the sum of the proportions of babies weighing less than 2090, between 2090 and 2560, and between 2560 and 3030 grams. So

Pr(X < 3030) = Pr(-∞ < X < 2090) + Pr(2090 < X < 2560) + P(2560 < X < 3030)

Pr(X < 3030) ≈ 0.0015 + 0.0235 + 0.135

Pr(X < 3030) ≈ 0.16 = 16%

(d) Similarly,

Pr(X > 2560) = Pr(2560 < X < 3030) + Pr(3030 < X < 3500) + … + Pr(4910 < X < ∞)

Pr(X > 2560) ≈ 0.135 + 0.34 + 0.34 + 0.135 + 0.0235 + 0.0015

Pr(X > 2560) ≈ 0.975 = 97.5%

8 0
2 years ago
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