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frutty [35]
3 years ago
8

What is 9/4 pounds equal to as a mixed number

Mathematics
1 answer:
Rufina [12.5K]3 years ago
4 0
Mixed number: 9/4 = 2 1/4
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∠F and ∠G are supplementary angles. If m∠F is two less than six times the measure of ∠G, find the measures of both angles
Mnenie [13.5K]

Answer:

∠ G = 26°, ∠ F = 154°

Step-by-step explanation:

Express ∠ F in terms of ∠ G, that is

F = 6G - 2

and since the angles are supplementary, then

G + 6G - 2 = 180, that is

7G - 2 = 180 ( add 2 to both sides )

7G = 182 ( divide both sides by 7 )

G = 26

Thus

∠ G = 26° and ∠ F = 6(26) - 2 = 156 - 2 = 154°

4 0
3 years ago
What property is (a•3)x b = b x(a•3) Using algebraic Expressions
Archy [21]

Answer:  Commutative Property of Multiplication

<u>Step-by-step explanation:</u>

Commutative property is when two terms trade places.

(a · 3) × b = b × (a · 3)

Notice that (a · 3) switched places with b

8 0
3 years ago
Please help with this, Thank You.
Dmitry [639]

Answer:

x = 12

Step-by-step explanation:

3x + 9 = 5x - 15

2x = 24

x = 12

4 0
2 years ago
A child tosses a baseball up into the air. On its way down, it gets caught in a tree for several seconds before falling back dow
8090 [49]

Answer:

what is the question because I don't understand what you mean

8 0
3 years ago
It is believed that 3% of people actually have this predisposition. The genetic test is 99% accurate if a person actually has th
fiasKO [112]

Answer:

Required Probability = 0.605

Step-by-step explanation:

Let Probability of people actually having predisposition, P(PD) = 0.03

Probability of people not having predisposition, P(PD') = 1 - 0.03 = 0.97

Let PR = event that result are positive

Probability that the test is positive when a person actually has the predisposition, P(PR/PD) = 0.99

Probability that the test is positive when a person actually does not have the predisposition, P(PR/PD') = 1 - 0.98 = 0.02

So, probability that a randomly selected person who tests positive for the predisposition by the test actually has the predisposition = P(PD/PR)

Using Bayes' Theorem to calculate above probability;

 P(PD/PR) = \frac{P(PD)*P(PR/PD)}{P(PD)*P(PR/PD)+P(PD')*P(PR/PD')}

                   = \frac{0.03*0.99}{0.03*0.99+0.97*0.02} = \frac{0.0297}{0.0491} = 0.605 .

7 0
3 years ago
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