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3 years ago

(2x-1) (3x+5) -(2x-1) (x+4)

Mathematics

1 answer:

Veseljchak [2.6K]3 years ago

8 0

Answer:

4x^2−1

Step-by-step explanation:

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A ladder is leaning against a vertical wall. The distance from the top of the ladder to the base of the wall is 17 feet. The dis

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Answer:

18.4 feet

Step-by-step explanation:

-use the formula C^2 = A^2 + B^2 for a right triangle, which is made by the ladder and the wall.

-let the ladder be C, the wall be a, the base to the bottom be b.

-substitude into the equation, which will leave us with:

C^2 = 17^2 + 7^2

C^2 = 289 + 49

C^2 = 338

C = square root of 338, which is 18.4 feet!

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At the market 8 batteries cost 10 dollars how much will 6 cost

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In a population of similar households, suppose the weekly supermarket expense for a typical household is normally distributed wi

Rina8888 [55]

Answer:

P(Y ≥ 15) = 0.763

Step-by-step explanation:

Given that:

Mean =135

standard deviation = 12

sample size n = 50

sample mean $\overline x$ = 140

Suppose X is the random variable that follows a normal distribution which represents the weekly supermarket expenses

Then,

$X \sim N ( \mu \sigma)$

The probability that X is greater than 140 is :

P(X>140) = 1 - P(X ≤ 140)

$P(X>140) = 1 - P( \dfrac{X-\mu}{\sigma} \leq \dfrac{140-135}{12})$

$P(X>140) = 1 - P( \dfrac{X-\mu}{\sigma} \leq \dfrac{5}{12})$

$P(X>140) = 1 - P( Z\leq0.42)$

From z tables,

$P(X>140) = 1 - 0.6628$

$P(X>140) = 0.3372$

Similarly, let consider Y to be the variable that follows a binomial distribution of the no of household whose expense is greater than $140

Then;

$Y \sim Binomial (np)$

$Y \sim Binomial (50,0.3372)$

∴

P(Y ≥ 15) = 1- P(Y< 15)

P(Y ≥ 15) = 1 - ( P(Y=0) + P(Y=1) + P(Y=2) + ... + P(Y=14) )

$P(Y \geq 15) = 1 - \begin {pmatrix} ^{50}_0 \end {pmatrix} (0.3372)^0 (1-0,3372)^{50} + \begin {pmatrix} ^{50}_1 \end {pmatrix} (0.3372)^1 (1-0,3372)^{49} + \begin {pmatrix} ^{50}_2 \end {pmatrix} (0.3372)^2 (1-0,3372)^{48} +... + \begin {pmatrix} ^{50}_{50{ \end {pmatrix} (0.3372)^{50} (1-0,3372)^{0}$

P(Y ≥ 15) = 0.763

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3 years ago