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Juliette [100K]
2 years ago
10

Solve for x. Will brainlist correct answer

Mathematics
1 answer:
Vladimir79 [104]2 years ago
3 0

Answer:

(8x-27)4* R=0

Step-by-step explanation:

4Cr(8x)4-r(-27)r

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HELP ASAP I GIVE 15 POINTS AND BRAINLIEST
IgorC [24]

Answer:

110%

Step-by-step explanation:

if each square is a whole, then when one is filled, it's 100% . 10% of the other square is filled so you just add the two.

4 0
3 years ago
Give an example of an equation that is true.
bonufazy [111]

Answer:

5 + 4 = 9

Step-by-step explanation:

7 0
3 years ago
State of the number 49/9 (square root) is a rational or irrational
lina2011 [118]
Hey there!!

49/9 = 7
is a rational number as it has a definite answer 7.

Hope it helps you.
5 0
3 years ago
The maximum acceptable level of a certain toxic chemical in vegetables has been set at 0.4 parts per million (ppm). A consumer h
Elodia [21]

Answer:

Null hypothesis : \mu \leq 0.4

Alternative hypothesis: \mu >0.4

And for this case a type of error I for this case would be reject the null hypothesis that the population mean is lower or equal than 0.4 when actually is true.

A Type I error would occur if, in fact, μ ≤ 0.4 ppm, but the results of the sampling lead to the conclusion that μ > 0.4 ppm

Step-by-step explanation:

Previous concepts

A hypothesis is defined as "a speculation or theory based on insufficient evidence that lends itself to further testing and experimentation. With further testing, a hypothesis can usually be proven true or false".  

The null hypothesis is defined as "a hypothesis that says there is no statistical significance between the two variables in the hypothesis. It is the hypothesis that the researcher is trying to disprove".  

The alternative hypothesis is "just the inverse, or opposite, of the null hypothesis. It is the hypothesis that researcher is trying to prove".  

Type I error, also known as a “false positive” is the error of rejecting a null  hypothesis when it is actually true. Can be interpreted as the error of no reject an  alternative hypothesis when the results can be  attributed not to the reality.  

Type II error, also known as a "false negative" is the error of not rejecting a null  hypothesis when the alternative hypothesis is the true. Can be interpreted as the error of failing to accept an alternative hypothesis when we don't have enough statistical power

Solution to the problem

For this case we are trying to check the following hypothesis:

Null hypothesis : \mu \leq 0.4

Alternative hypothesis: \mu >0.4

And for this case a type of error I for this case would be reject the null hypothesis that the population mean is lower or equal than 0.4 when actually is true.

A Type I error would occur if, in fact, μ ≤ 0.4 ppm, but the results of the sampling lead to the conclusion that μ > 0.4 ppm

7 0
3 years ago
Two number cubes, each with faces numbered 1 to 6, will be tossed at the same time. What is the probability of tossing a sum of
Katen [24]
The probability of tossing a sum of 7:
6/36


the probability of tossing a sum greater than 7 :

not 100% sure
but I think it is 16/36


the probability of tossing a sum less than 13

36/36



good luck
7 0
2 years ago
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