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sweet-ann [11.9K]

2 years ago

5

To win the game, the team must score at least 8 goals. What inequality represents the number of goals, g, the team must score? D

rag and drop the appropriate symbol to complete the inequality. g 8 ><≤≥

2 answers:

Nat2105 [25]2 years ago

8 0

Solution:

The statement about a game in which various teams are playing:

It is given that To win the game, the team must score at least 8 goals.

The meaning of word atleast is that , the team can score either 8 goals or more than 8 goals.

So, we will write this situation in terms of inequality as

The value of g will be greater than equal to 8.

→g ≥ 8→→Option (D)

miskamm [114]2 years ago

5 0

G $\geq$ 8 is the answer I believe

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Jamal's deck is in the shape of a polygon and is shown on the grid below.(-8,6)(6,6)o[(-8, -4),(6,-4)What is the area of Jamal's

PSYCHO15rus [73]

Let;

A(-8,6) B(6,6) C(6, -4) D(-8, -4)

Let's find the length AB

x₁= -8 y₁=6 x₂=6 y₂=6

We will use the distance formula;

$d=\sqrt[]{(x_2-x_1)^2+(y_2-y_1)^2}$

$=\sqrt[]{(6+8)^2+(6-6)^2}$ $=\sqrt[]{14^2+0}$ $=14$

Next, we will find the width BC

B(6,6) C(6, -4)

x₁= 6 y₁=6 x₂=6 y₂=-4

substitute into the distance formula;

$d=\sqrt[]{(6-6)^2+(-4-6)^2}$

$=\sqrt[]{(-10)^2}$ $=\sqrt[]{100}$ $=10$

Area = l x w

= 14 x 10

= 140 square units

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1 year ago

A conical tent made of canvas has a base that is 34 feet across and a slant height of 12 feet to the nearest whole unit what is

RideAnS [48]

Check the picture below.

$\bf \textit{total surface area of a cone}\\\\
SA=\pi r\sqrt{r^2+h^2}+\pi r^2~~
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r=17\\
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SA=\pi (17)(12)+\pi (17)^2\implies SA=204\pi +289\pi \implies SA=493\pi$

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3 years ago

An employee shreds 341 pages in 11 minutes of work. How many pages will she shred in 20 minutes?

gavmur [86]

We have been given that an employee shreds 341 pages in 11 minutes of work.

First of all we will divide 341 by 11 to find number of pages shred by employee in one minute.

$\text{Pages shred by employee in one minute}=\frac{341}{11}=31$

Now let us multiply 31 by 20 to find number of pages shred by employee in 20 minutes.

$\text{Pages shred by employee in 20 minutes}=31\cdot20=620$

Therefore, employee will shred 620 pages in 20 minutes.

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2 years ago

An article suggests that a poisson process can be used to represent the occurrence of structural loads over time. suppose the me

kirill115 [55]

Answer:

a) $\lambda_1 = 2*2 = 4$

And let X our random variable who represent the "occurrence of structural loads over time" we know that:

$X(2) \sim Poi (4)$

And the expected value is $E(X) = \lambda =4$

So we expect 4 number of loads in the 2 year period.

b) $P(X(2) >6) = 1-P(X(2)\leq 6)= 1-[P(X(2) =0)+P(X(2) =1)+P(X(2) =2)+...+P(X(2) =6)]$

$P(X(2) >6) = 1- [e^{-4}+ \frac{e^{-4}4^1}{1!}+ \frac{e^{-4}4^2}{2!} +\frac{e^{-4}4^3}{3!} +\frac{e^{-4}4^4}{4!}+\frac{e^{-4}4^5}{5!}+\frac{e^{-4}4^6}{6!}]$

And we got: $P(X(2) >6) =1-0.889=0.111$

c) $e^{-2t} \leq 2$

We can apply natural log in both sides and we got:

$-2t \leq ln(0.2)$

If we multiply by -1 both sides of the inequality we have:

$2t \geq -ln(0.2)$

And if we divide both sides by 2 we got:

$t \geq \frac{-ln(0.2)}{2}$

$t \geq 0.8047$

And then we can conclude that the time period with any load would be 0.8047 years.

Step-by-step explanation:

Previous concepts

The exponential distribution is "the probability distribution of the time between events in a Poisson process (a process in which events occur continuously and independently at a constant average rate). It is a particular case of the gamma distribution". The probability density function is given by:

$P(X=x)=\lambda e^{-\lambda x}$

The exponential distribution is "the probability distribution of the time between events in a Poisson process (a process in which events occur continuously and independently at a constant average rate). It is a particular case of the gamma distribution"

Solution to the problem

Let X our random variable who represent the "occurrence of structural loads over time"

For this case we have the value for the mean given $\mu = 0.5$ and we can solve for the parameter $\lambda$ like this:

$\frac{1}{\lambda} = 0.5$

$\lambda =2$

So then $X(t) \sim Poi (\lambda t)$

X follows a Poisson process

Part a

For this case since we are interested in the number of loads in a 2 year period the new rate would be given by:

$\lambda_1 = 2*2 = 4$

And let X our random variable who represent the "occurrence of structural loads over time" we know that:

$X(2) \sim Poi (4)$

And the expected value is $E(X) = \lambda =4$

So we expect 4 number of loads in the 2 year period.

Part b

For this case we want the following probability:

$P(X(2) >6)$

And we can use the complement rule like this

$P(X(2) >6) = 1-P(X(2)\leq 6)= 1-[P(X(2) =0)+P(X(2) =1)+P(X(2) =2)+...+P(X(2) =6)]$

And we can solve this like this using the masss function:

$P(X(2) >6) = 1- [e^{-4}+ \frac{e^{-4}4^1}{1!}+ \frac{e^{-4}4^2}{2!} +\frac{e^{-4}4^3}{3!} +\frac{e^{-4}4^4}{4!}+\frac{e^{-4}4^5}{5!}+\frac{e^{-4}4^6}{6!}]$

And we got: $P(X(2) >6) =1-0.889=0.111$

Part c

For this case we know that the arrival time follows an exponential distribution and let T the random variable:

$T \sim Exp(\lambda=2)$

The probability of no arrival during a period of duration t is given by:

$f(T) = e^{-\lambda t}$

And we want to find a value of t who satisfy this:

$e^{-2t} \leq 2$

We can apply natural log in both sides and we got:

$-2t \leq ln(0.2)$

If we multiply by -1 both sides of the inequality we have:

$2t \geq -ln(0.2)$

And if we divide both sides by 2 we got:

$t \geq \frac{-ln(0.2)}{2}$

$t \geq 0.8047$

And then we can conclude that the time period with any load would be 0.8047 years.

3 0

3 years ago

Suppose that E and F are two events and that P(E)=0.3 and P(F|E)=0.5. What is P(E and F)?

Sergio [31]

E and F are two events and that P(E)=0.3 and P(F|E)=0.5. Thus, P(E and F)=0.15

Bayes' theorem is transforming preceding probabilities into succeeding probabilities. It is based on the principle of conditional probability. Conditional probability is the possibility that an event will occur because it is dependent on another event.

P(F|E)=P(E and F)÷P(E)

It is given that P(E)=0.3,P(F|E)=0.5

Using Bayes' formula,

P(F|E)=P(E and F)÷P(E)

Rearranging the formula,

⇒P(E and F)=P(F|E)×P(E)

Substituting the given values in the formula, we get

⇒P(E and F)=0.5×0.3

⇒P(E and F)=0.15

∴The correct answer is 0.15.

If, E and F are two events and that P(E)=0.3 and P(F|E)=0.5. Thus, P(E and F)=0.15.

Learn more about Bayes' theorem on

brainly.com/question/17010130

#SPJ1

4 0

2 years ago