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bogdanovich [222]
3 years ago
8

Two equivalent fraction for 3/12​

Mathematics
2 answers:
shusha [124]3 years ago
8 0
9/36 and 1/4 because you and divide and multiple those
denpristay [2]3 years ago
4 0

Answer:

1/4 and 6/24

Step-by-step explanation:

3 divided by 3 equals 1. So then you have to do the same for the denominator. 12 divided by 3 equals 4. And you get 1/4.

Another is 3 x 2 = 6 and 12 x 2 = 24. 6/24

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Below is a proof showing that the sum of a rational number and an irrational number is an irrational number.
Korvikt [17]
Did you ever get an answer?
7 0
3 years ago
Solve for x:<br><br> 2+x=8-x
dsp73

2+x=8-x

add x to each side to get all the x's on one side

2+x+x = 8-x+x

2 + 2x = 8

now subtract 2 from each side to get all the numbers on the other side

2 + 2x -2 = 8-2

2x = 6

divide by 2 on each side to get x alone

2x/2 = 6/2

x=3


Answer: x=3


7 0
3 years ago
Determine whether the results appear to have statistical​ significance, and also determine whether the results appear to have pr
vivado [14]

Answer:

Due to the fact that there is 21% chance of getting that many girls by chance and also In conjunction to that; there is no test involved as well , we can conclude that the method does not have statistical significance.

The result does not appear to have a practical significance.

Step-by-step explanation:

Given that:

In  a random selection 1936 users, we observed that the method gave birth to  950 boys and 986 girls

There is about a 21​% chance of getting that many girls if the method had no effect.

Due to the fact that there is 21% chance of getting that many girls by chance and also In conjunction to that; there is no test involved as well , we can conclude that the method does not have statistical significance.

Given that:

The number of girls = 986

Number of boys = 950

Number of babies born = 1936

The percentage of girls = number of girls born/ number of babies born

The percentage of girls = 986 /1936

The percentage of girls = 0.5093

The percentage of girls =  50.93%

We can infer that this method does not have a practical significance  because most couples would not prefer to use a method that raise the likelihood of a girl from the approximately 50% rate expected by chance to the 50.93% .

3 0
3 years ago
10/f - 12<br> (write a word phrase for the algebraic expression)
diamong [38]

Answer: Twelve is less than ten divided by f.

Step-by-step explanation:

12 is being subtracted from the 10/f which means it has to be less than 10 divide by f.

4 0
3 years ago
with the salary cap in the NFL, it is said that on "any given Sunday" any team could beat any other team. If we assume every wee
prohojiy [21]

Answer:

P(X \geq 1) = 1-P(X

And we can find the individual probability like this:

P(X=0) = 16C0 (0.5)^0 (1-0.5)^{16-0} = 0.0000153

And replacing we got:

P(X \geq 1) = 1-P(X

Step-by-step explanation:

Assuming the following question: With the salary cap in the NFL, it is said that on any given Sunday any team could beat any other team. If we assume every week of the 16 week season a team has a 50% chance of winning, what is the probability that a team will have at least 1 win?

Previous concepts  

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".  

Solution to the problem

Let X the random variable of interest, on this case we now that:  

X \sim Binom(n=16, p=0.5)  

The probability mass function for the Binomial distribution is given as:  

P(X)=(nCx)(p)^x (1-p)^{n-x}  

Where (nCx) means combinatory and it's given by this formula:  

nCx=\frac{n!}{(n-x)! x!}  

And we want this probability:

P(X \geq 1)

And using the complement rule we got:

P(X \geq 1) = 1-P(X

And we can find the individual probability like this:

P(X=0) = 16C0 (0.5)^0 (1-0.5)^{16-0} = 0.0000153

And replacing we got:

P(X \geq 1) = 1-P(X

7 0
3 years ago
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