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3 years ago

11

What is eight times negative six

2 answers:

Semmy [17]3 years ago

5 0

Answer:

$-48$

Step-by-step explanation:

$--------------------------------------------$

$1\cdot-6$ = $-6$

$2\cdot-6$ = $-12$

$3\cdot-6$ = $-18$

$4\cdot-6$ = $-24$

$5\cdot-6$ = $-30$

$6\cdot-6$ = $-36$

$7\cdot-6$ = $-42$

$8\cdot-6$ = $-48$

$Answer$ ↑

$--------------------------------------------$

<em>Hope this helps! <3</em>

$--------------------------------------------$

Sav [38]3 years ago

4 0

Answer:

-48

Step-by-step explanation:

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3 years ago

Find the value of xx, yy, and zz in the parallelogram below.

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Answer: x = 92, y = -119

Step-by-step explanation:

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5 0

2 years ago

Read 2 more answers

-2.3,-2 2/4,-2.6 from least to greatest

Pie

If you think about it, you have your answer in your question.

Convert 2/4 to 1/2 which in decimal form, is .5.

You’re final answer is -2.3,-2 2/4,-2.6.

I hope this helps!

7 0

3 years ago

In a semiconductor manufacturing process, three wafers from a lot are tested. Each wafer is classified as pass or fail. Assume t

Angelina_Jolie [31]

Answer:

$P(X = 0) = 0.027$

$P(X = 1) = 0.189$

$P(X = 2) = 0.441$

$P(X = 3)= 0.343$

Step-by-step explanation:

The probability mass function P(X = x) is the probability that X happens x times.

When n trials happen, for each $x \leq n$ , the probability mass function is given by:

$P(X = x) = pe_{n,x}.p^{x}.(1-p)^{n-x}$

In which p is the probability that the event happens.

$pe_{n,x},$ is the permutation of n elements with x repetitions(when there are multiple events happening(like one passes and two not passing)). It can be calculated by the following formula:

$pe_{n,x} = \frac{n!}{x!}$

The sum of all P(X=x) must be 1.

In this problem

We have 3 trials, so $n = 3$

The probability that a wafer pass a test is 0.7, so $p = 0.7$

Determine the probability mass function of the number of wafers from a lot that pass the test.

$P(X = 0) = (0.7)^{0}.(0.3)^{3} = 0.027$

$P(X = 1) = pe_{3,1}.(0.7).(0.3)^{2} = 0.189$

$P(X = 2) = pe_{3,2}.(0.7)^{2}.(0.3) = 0.441$

$P(X = 3) = (0.7)^{3} = 0.343$

5 0

4 years ago