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MariettaO [177]
2 years ago
13

Gretchen went to the market.she bought 4/8kg of flour and 8/9kg of rice.How much more rice than flour did she buy?

Mathematics
1 answer:
Natasha2012 [34]2 years ago
3 0
Gretchen bought 7/18 more rice than flour.
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Between 02 30 and 05 30,the same day,the volume of water in a reservoir increased from 6000 L to 18 000 L.What was the average r
irinina [24]

Answer:

4,000 L/h

Step-by-step explanation:

First we'll find the amount of the change.

18,000 - 6,000 = 12,000 L

The time of the volume change was 3 hours: 0230 - 0530

Since we're looking for liters per hour, we will divide the liters (12,000) by the hours (3)

12,000/3 = 4,000 L/h

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2 years ago
Why does each number only have one square root?
Tamiku [17]

Answer:

it gets  multiplied by the value of the root .that is just more concise way of writing it .

Step-by-step explanation:

3 0
3 years ago
There are 72 packs of sugar in a box. Each sugar pack is 9/10 of an ounce. How many ounces are in a box?
mixas84 [53]
9/10 of an ounce is 0.9. 0.9 X 72 = 64.8.

There is 64.8 ounces in a box.
7 0
3 years ago
An exit poll in an election is a survey taken of voters just after they have voted. One major use of exit polls has been so that
3241004551 [841]

Answer:

P(A) = 0.39

Step-by-step explanation:

We are given;

P(W|A) = 0.7

P(W|A^c ) = 0.3

We are told that 60% of the respondents said they voted for A. Thus;

P(A|W) = 60% = 0.6

Now, using the principle of drawing lots, we can be able to find the probability of the event that they are willing to participate in the exit poll which is P(W).

Thus;

P(W) = [P(W|A) × P(A)] +[P(W∣A^c) × P(A^c)]

Now, P(A^c) can be expressed as 1 - P(A)

Thus, we now have;

P(W) = [P(W|A) × P(A)] + [P(W∣A^c) × (1 - P(A)]

Plugging in the relevant values gives;

P(W) = 0.7P(A) + 0.3(1 - P(A))

P(W) = 0.7P(A) + 0.3 - 0.3P(A)

P(W) = 0.3 + 0.4P(A)

Now,using Baye's theorem, we can find an expression for P(A|W)

Thus;

P(A|W) = [P(A ∩ W)]/P(W)

This can be further expressed as;

P(A|W) = [P(A) × P(W|A)]/P(W)

Plugging in relevant values, we have;

0.6 = 0.7P(A)/(0.3 + 0.4P(A))

Cross multiply to get;

0.6(0.3 + 0.4P(A)) = 0.7P(A)

0.18 + 0.24P(A) = 0.7P(A)

0.18 = 0.7P(A) - 0.24P(A)

0.46P(A) = 0.18

P(A) = 0.18/0.46

P(A) = 0.39

7 0
3 years ago
Suppose you roll a fair die. Let X be the value of the roll. What is the Moment Generating Function of X?
Alex_Xolod [135]

Answer:

μ₁`= 1/6

μ₂=  5/36

Step-by-step explanation:

The rolling of a fair die is described by the binomial distribution, as  the

  1. the probability of success remains constant for all trials, p.
  2. the successive trials are all independent
  3. the experiment is repeated a fixed number of times
  4. there are two outcomes success, p, and failure ,q.

The moment generating function of the binomial distribution is derived as below

M₀(t) = E (e^tx)

        = ∑ (e^tx) (nCx)pˣ (q^n-x)

        = ∑ (e^tx) (nCx)(pe^t)ˣ (q^n-x)

        = (q+pe^t)^n

the expansion of the binomial is purely algebraic and needs not to be interpreted in terms of probabilities.

We get the moments by differentiating the M₀(t) once, twice with respect to t and putting t= 0

μ₁`= E (x) = [ d/dt (q+pe^t)^n]  t= 0

            = np

μ₂`=  E (x)² =[ d²/dt² (q+pe^t)^n]  t= 0

              = np +n(n-1)p²

μ₂=μ₂`-μ₁` =npq

in similar way the higher moments are obtained.

μ₁`=1(1/6)= 1/6

μ₂= 1(1/6)5/6

   = 5/36

4 0
3 years ago
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