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3 years ago

What do you suppose is true about a sum added to its opposite?

1 answer:

6 0

Opposite number, also called the additive inverse, is by defition a number that if you add it to its opposite, the result will be 0!!!

so you know that a number added to its opposite will be 0!

in practice this means that it's the same value with the opposite sign.

You might be interested in

The diagonal of a square has length 10√2. Find the area of the square.

alex41 [277]

Answer: $A = 100$ square unit

Step-by-step explanation:

The formula for calculating the area of a square when the diagonal is given is :

$Area = d^{2} / 2$

That is :

$A = \frac{(10\sqrt{2})^{2}}{2}$

$A = \frac{100(2)}{2}$

$A = 100$ square unit

3 0

2 years ago

Please help no idea what to do

ololo11 [35]

You just substitute the heights for H. 25 + 1.17(34) then find what that equals to the nearest inch and do the same for the boy

4 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 $= \sigma _{y}=\sqrt{10}*0.75 = 2.3717$

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

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

There is concern that increased industrialization may be increasing the mineral content of river water. Ten years ago, the silic

Tema [17]

Answer:

a) P value = 0.0013

b) No, it is not plausible that the silicon content of the water is no greater than it was 10 years ago

Step-by-step explanation:

The null hypothesis here is “Mean is equal to 5” while alternate hypothesis is that “Mean is greater than 5”

Given

Mean = 5, x’ = 5.4 and sigma = 1.2 and n = 85

Z = x-u’/sigma/sqrt n

Substituting the given values, we get –

Z = 3.02

A) P value = 0.0013 which is less than 0.05 and thus we will reject the null hypothesis

B) There is enough evidence to reject the null hypothesis

6 0

2 years ago

If P(not A) = 0.18 and P(A and B) = 0.44, what is P(B given A)?

pickupchik [31]

p(not A)=0.18

p(A&B)= 0.44

A= 0.44- 0.18

= 0.26

P(B given A)= 0.26+0.18+0.44

=0.7

3 0

2 years ago