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3 years ago

Pls answer this ASAP! 

Mathematics

2 answers:

ki77a [65]3 years ago

8 0

Answer:

Step-by-step explanation:

Alika [10]3 years ago

3 0

B. 2.9, square root of 7, 1.9, square root of 2

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PLS HELP ME IM BEING TIMED AND I HAVE 20 MINS TO TURN IN.

Natasha_Volkova [10]

Answer:

2.a) 3 ( x - 1 ) = 5x - 6 (Because the sides of a square are always equal)

b) 3 ( x - 1 ) = 5x - 6

=> 3x - 3 = 5x - 6

=> 3x - 5x = -6 + 3 (Law of transposition)

=> -2x = -3

=> -x = -3/2

=> -x = -1.5

=> x = 1.5 (By cancelling out the negative sign from both the sides)

c) 3(x-1) = 3 (1.5 - 1)

=> 3 (0.5)

=> 3 * 0.5 = 1.5

Both the angles are 1.5 because they are equal

If my answer helped, please mark me as the brainliest!!

Thank You!

8 0

3 years ago

Solve the compound inequality.

oksano4ka [1.4K]

5x - 11 < -11
5x < 0
x < 0

4x + 2 > 14
4x > 12
x > 3

x<0 or x > 3

7 0

3 years ago

Read 2 more answers

2. The quality assurance department inspects its production line. The product either fails or passes the inspection. Past experi

Oksana_A [137]

Answer:

(a) $E(X) = 950$

(b) $COV = 0.007255$

Step-by-step explanation:

The given problem can be solved using binomial distribution since the product either fails or passes, the probability of failure or success is fixed and there are n repeated trials.

probability of failure = q = 0.05

probability of success = p = 1 - 0.05 = 0.95

number of trials = n = 1000

(a) What is the expected number of non-defective units?

The expected number of non-defective units is given by

$E(X) = n \times p \\\\E(X) = 1000 \times 0.95 \\\\E(X) = 950$

(b) what is the COV of the number of non-defective units?

The coefficient of variance is given by

$COV = \frac{\sigma}{E(X)}$

Where the standard deviation is given by

$\sigma = \sqrt{n \times p\times q} \\\\\sigma = \sqrt{1000 \times 0.95\times 0.05} \\\\\sigma = 6.892$

So the coefficient of variance is

$COV = \frac{6.892}{950}$

$COV = 0.007255$

(c) What is the probability of having more than 980 non-defective units?

We can use the Normal distribution as an approximation to the Binomial distribution since n is quite large and so is p.

$P(X > 980) = 1 - P(X < 980)\\\\P(X > 980) = 1 - P(Z < \frac{x - \mu}{\sigma} )\\\\$

We need to consider the continuity correction factor whenever we use continuous probability distribution (Normal distribution) to approximate discrete probability distribution (Binomial distribution).

$P(X > 980) = 1 - P(Z < \frac{979.5 - 950}{6.892} )\\\\P(X > 980) = 1 - P(Z < \frac{29.5}{6.892} )\\\\P(X > 980) = 1 - P(Z < 4.28)\\\\$

The z-score corresponding to 4.28 is 0.99999

$P(X > 980) = 1 - 0.99999\\\\P(X > 980) = 0.00001\\\\$

So it means that it is very unlikely that there will be more than 980 non-defective units.

8 0

3 years ago

Help please math test 3

aleksandrvk [35]

Answer:

Divide

Step-by-step explanation:

Jus divide it inthink

5 0

3 years ago

660 divided by 15 is the same as?

djyliett [7]

Answer:

Step-by-step explanation:

Just divide 660 by 15 to get 44.

4 0

3 years ago