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gtnhenbr [62]
4 years ago
12

How do you find the g field at a point between 2 masses?

Physics
1 answer:
Allisa [31]4 years ago
6 0

Answer:

Newton's Law of Gravitation states that the gravitational force ⎯⎯ between two point masses and a distance apart in a vacuum, is attractive, acts along the line joining their centres, and is proportional to the masses and inversely proportional to the square of their separations.

∝2

In the SI system, the constant of proportionality is , the gravitational constant, which has a value of 6.67×10−11Nm2kg−2, and so we may write this as,

=2

The gravitational field is the gravitational force per unit mass that would be exerted on a small (so it doesn't measurably affect the gravitational field) test mass at that point. It is a vector field, and points in the direction of the force that a small test mass would feel at that point. For a point particle of mass , the magnitude of the resultant gravitational field strength , at distance from , is

=2

The gravitational force acting on a mass , which is also sometimes described as its weight in the gravitational field ⎯⎯, is given by:

⎯⎯=⎯⎯

At the surface of the Earth, ⎯⎯ has a magnitude of 2=9.81ms−2, where is the radius of the Earth.

Explanation:I am so(maybe)Big brain...

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A boy takes 20 minutes to cover 3.2 km on a bicycle find the speed in km/hr​
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4 0
3 years ago
a. What proportion of resistors have resistances less than 90 Ω? b. Find the mean resistance. c. Find the standard deviation of
Anettt [7]

Answer:

a) 0.0625 = 6.25%

b) 106.67 Ω

c) 9.43 Ω

d) 1

Explanation:

The probability distribution is given as

f(x) = (x - 80)/800 for 80 < x < 120

f(x) = 0 otherwise.

f(x) = (x/800) - (0.1)

a) Proportion of resistors with resistance less than 90 Ω

P(X < 90) = ∫⁹⁰₈₀ f(x) dx

∫⁹⁰₈₀ f(x) dx = ∫⁹⁰₈₀ [(x/800) - (0.1)]

= [(x²/1600) - 0.1x]⁹⁰₈₀

= [(90²/1600) - 0.1(90)] - [(80²/1600) - 0.1(80)]

= (5.0625 - 9) - [4 - 8]

= -3.9375 + 4 = 0.0625 = 6.25%

b) The mean is given by the expected value expression E(X) = = Σ xᵢpᵢ (with the sum done all over the data set for each variable and its corresponding probability)

It can be written in integral form as

Mean = ∫¹²⁰₈₀ xf(x) dx (with the integral done all over the probability function, i.e. from, 80 to 120)

Mean = ∫¹²⁰₈₀ x[(x/800) - (0.1)] dx

= ∫¹²⁰₈₀ [(x²/800) - (0.1x)] dx

= [(x³/2400) - (0.05x²)]¹²⁰₈₀

= [(120³/2400) - (0.05(120²)] - [(80³/2400) - (0.05(80²)]

= [720 - 720] - [213.33 - 320] = 106.67 Ω

c) Standard deviation = √(variance)

Variance = Var(X) = Σx²p − μ²

μ = mean = expected value = 106.67 Ω

Σx²p = ∫¹²⁰₈₀ x²f(x) dx = ∫¹²⁰₈₀ x² [(x/800) - (0.1)] dx = ∫¹²⁰₈₀ [(x³/800) - (0.1x²)] dx

= [(x⁴/3200) - (0.0333x³)]¹²⁰₈₀

= [(120⁴/3200) - (0.0333(120³)] - [(80⁴/3200) - (0.0333(80)³)]

= (64800 - 57600) - (12800 - 17066.667)

= 11466.667

Variance = 11466.667 - 106.67² = 88.85

Standard deviation = √88.85 = 9.43 Ω

d) Cdf = sum of probabilities over the entire probability function

Cdf = ∫¹²⁰₈₀ f(x) dx = ∫¹²⁰₈₀ [(x/800) - (0.1)] dx

= [(x²/1600) - 0.1x]¹²⁰₈₀ = [(120²/1600) - 0.1(120)] - [(80²/1600) - 0.1(80)] = (9 - 12) - (4 - 8) = -3+4 = 1 as it should be!!!

Hope this Helps!!!

4 0
4 years ago
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