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Kitty [74]
3 years ago
10

What is 1 and five eights plus 2 and threee sixteenths plus 7 and one half?

Mathematics
2 answers:
Helen [10]3 years ago
8 0

Answer:

11 and 5/16

Hope this answers your question

Finger [1]3 years ago
7 0

Answer:

11 and 5/16

Step-by-step explanation:

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What is the simplified expression for the expression below?
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Answer:

A

Step-by-step explanation:

- 1/5 of 5x is  -1 or just -x and -1/5 of 20 is -4. Then the other one is-1/4 of 4 is -x and -1/4 of -28 is 7. Now combine like terms so -x + -x is -2x and 7+ -4 or 7-4 is 3

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3 years ago
If s= the number of stamps that sara has, which mathematical sentence expresses the information?
Monica [59]
S*x!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
7 0
3 years ago
Jesus loves you!!!<br><br> Jesus te ama!!!
sattari [20]

Answer:

yesss!!!!

Step-by-step explanation:

4 0
3 years ago
Read 2 more answers
3 times the sum of b and f can also be written as
Troyanec [42]
<span>3 times the sum of b and f can also be written as </span>3(b+f)
6 0
3 years ago
Suppose that X has a discrete uniform distribution on the integers 0 through 9. Determine the mean, variance, and standard devia
Anna35 [415]
With 10 integers available, X has PMF

\mathbb P(X=x)=\begin{cases}\dfrac1{10}&\text{for }0\le x\le9,x\in\mathbb Z\\\\0&\text{otherwise}\end{cases}

We're interested in the statistics of the new random variable Y=5X. To do this, we need to know the PMF for Y. This isn't too hard to find.

\mathbb P(Y=y)=\mathbb P(5X=y)=\mathbb P\left(X=\dfrac y5\right)

Since the PMF for X gives a value of \dfrac1{10} whenever x is an integer between 0 and 9, it follows that \dfrac y5 must also be an integer for the PMF to give the identical value of \dfrac1{10}. This means

\mathbb P(Y=y)=\begin{cases}\dfrac1{10}&\text{for }y\in\{0,5,\ldots,45\}\\\\0&\text{otherwise}\end{cases}

Now the mean (expectation) is

\mathbb E(Y)=\displaystyle\sum_yy\mathbb P(Y=y)=\frac1{10}\sum_{y\in\{0,\ldots,45\}}y
\mathbb E(Y)=\dfrac{225}{10}=22.5

The variance would be

\mathbb V(X)=\mathbb E(X^2)-\mathbb E(X)^2
\mathbb V(X)=\displaystyle\sum_yy^2\mathbb P(Y=y)-\mathbb E(Y)^2
\mathbb V(X)=\displaystyle\frac1{10}\sum_{y\in\{0,\ldots,45\}}y^2-\left(\frac{225}{10}\right)^2
\mathbb V(X)=\dfrac{7125}{10}-\dfrac{50625}{100}=206.25

The standard deviation is the square root of the variance, so you have

\sqrt{\mathbb V(X)}=\sqrt{206.25}\approx14.3614
8 0
3 years ago
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