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Talja [164]
3 years ago
6

What is the quotient?

Mathematics
2 answers:
jonny [76]3 years ago
4 0
Solutions 

Use Negative Power Rule  

<span>1/(7^4/7^9) 

= </span><span>16807 

= 1 (7^5) 

= (B) 


</span>
AleksandrR [38]3 years ago
3 0
I wanna say the 1st or the last one
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What is the domain of the function represented by the graph?
dezoksy [38]

Answer:  Choice C.  x \ge -3

============================================

Explanation:

The domain is the set of all allowed x inputs.

Here we see that x = -3 is the smallest x value possible as it is from the left-most point. The graph goes on forever to the right, so there is no largest x value. Effectively infinity is the largest x value even though infinity is not a number.

We can say the domain is -3 \le x < \infty which can be simplified to -3 \le x or x \ge -3

In short: x can be -3 or larger.

8 0
3 years ago
Camila built a rectangular vegetable garden, as shown in the figure.
Elan Coil [88]
Https://dlsfile.com/dd/MTQ1ODE5dnJpZ3doanhobV8zNDEzMjU
7 0
2 years ago
(3 points) Blades of grass Suppose that the heights of blades of grass are Normally distributed and independent, with each heigh
NemiM [27]

The final answer is:

a) P( Y < 42.5 )  = 0.8541

b) P( 39.5 < Y < 40.5 ) = 0.1670.

What is the normal distribution?

A continuous probability distribution for a real-valued random variable in statistics is known as a normal distribution or Gaussian distribution.

If x follows a normal distribution with mean μ and standard deviation σ then the distribution of

\sum_{i =1}^{n}x_{i}  follows an approximately normal distribution with a mean n\mu and standard deviation \sqrt{n }\sigma

let x be the height of blades of grass

x follows normal distribution with mean = μ = 4 and standard deviation = σ = 0.75.

Y = x1 + x2 +...........+x10

Y = \sum_{i =1}^{10}x_{i}

Distribution of Y is normal with,

Mean = \mu _{y}=10*4 = 40 and standard deviation = \sigma _{y}=\sqrt{10}*0.75 = 2.3717

a)

P( Y < 42.5 )

Using normal distribution formmula,

f(x)= {\frac{1}{\sigma\sqrt{2\pi}}}e^{- {\frac {1}{2}} (\frac {x-\mu}{\sigma})^2}

=NORMDIST( x, mean, SD , 1 )      

=NORMDIST(42.5, 40, 2.3717, 1 )

=0.8541

P( Y < 42.5 )  = 0.8541

b)

P( 39.5 < Y < 40.5 ) = P( Y < 40.5 ) - P( Y < 39.5 )

Using normal distribution formmula,

f(x)= {\frac{1}{\sigma\sqrt{2\pi}}}e^{- {\frac {1}{2}} (\frac {x-\mu}{\sigma})^2}

P( Y < 40.5 )  =NORMDIST(40.5, 40, 2.3717, 1 ) = 0.5835

P( Y < 39.5 ) = NORMDIST(39.5, 40, 2.3717, 1 ) = 0.4165

P( 39.5 < Y < 40.5 ) = 0.5835 - 0.4165  = 0.1670

P( 39.5 < Y < 40.5 ) = 0.1670

Hence, the final answer is:

a) P( Y < 42.5 )  = 0.8541

b) P( 39.5 < Y < 40.5 ) = 0.1670.

To learn more about the normal distribution visit,

brainly.com/question/4079902

#SPJ4

5 0
1 year ago
Hey anyone in 7th grade I need advise, on a guy
nadezda [96]

Answer:

im in 6th but i gotchu, spilllll

Step-by-step explanation:

7 0
3 years ago
Whats 95 + r = 2,736-2
babymother [125]

Answer:

r=2639

Steps below

Step-by-step explanation:

Step 1: Simplify both sides of the equation.

95+r=2736−2

95+r=2736+−2

r+95=(2736+−2)(Combine Like Terms)

r+95=2734

r+95=2734

Step 2: Subtract 95 from both sides.

r+95−95=2734−95

r=2639

Hope this helps.

8 0
3 years ago
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