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Marrrta [24]
3 years ago
10

Sum of 12/13+(-1/13)=

Mathematics
2 answers:
max2010maxim [7]3 years ago
4 0
\frac{12}{13} + (- \frac{1}{13} )

First, simplify the brackets. / Your problem should look like: \frac{12}{13} - \frac{1}{13}
Second, simplify. / Your problem should look like: \frac{11}{13}

Answer as fraction: \frac{11}{13}
Answer as decimal: 0.8462


valkas [14]3 years ago
3 0
\frac{12}{13} + (-\frac{1}{13}) = \frac{12}{13} - \frac{1}{13} = \frac{12-1}{13} =\boxed{ \frac{11}{13}}
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Let X denote the number of flaws along a 100-m reel of magnetic tape (an integer-valued variable). Suppose Zdenote the number of
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Answer:

a) P(20 \leq X \leq 30) = P(20-0.5 \leq X \leq 30+0.5)

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And we can find this probability like this:

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P(X

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Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Continuity correction means that we need to add and subtract 0.5 before standardizing the value specified.

Part a

Let X the random variable that represent the variable of interest of a population, and for this case we know the distribution for X is given by:

X \sim N(25,5)  

Where \mu=25 and \sigma=5

Part a

For this case we want to find this probability:

P(20 \leq X \leq 30) = P(20-0.5 \leq X \leq 30+0.5)

And if we use the z score given by:

z =\frac{x-\mu}{\sigma}

We got this:

P(19.5 \leq X \leq 30.5) = P(\frac{19.5-25}{5} \leq Z \leq \frac{30.5 -25}{5})=P(-1.1 \leq Z \leq 1.1)

And we can find this probability like this:

P(-1.1 \leq Z \leq 1.1)= P(Z\leq 1.1) -P(Z\leq -1.1) = 0.864-0.136= 0.728

Part b

For this case we want this probability:

P(X \leq 30)

And if we use the continuity correction we got:

P(X \leq 30)= P(X

And using the z score we got:

P(X

Part c

For this case we want this probability:

P(X

And if we use the continuity correction we got:

P(X

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