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3 years ago

5 oranges cost $2. Find the cost of 20 oranges.

Mathematics

2 answers:

vagabundo [1.1K]3 years ago

5 0

Answer:

Step-by-step explanation:

if 5 oranges cost $2 then 1 orange costs 2/5 of a dollar, or 40 cents

20 oranges multiplied by 40 cents is $8

or you can set up a proportion:

2/5 = x/20

cross-multiply to get:

5x = 40

x = 8

Sonja [21]3 years ago

4 0

<h3>Answer: $8</h3>

===================================================

Work Shown:

(5 oranges)/(2 dollars) = (20 oranges)/(x dollars)

5/2 = 20/x

5x = 2*20 .... cross multiply

5x = 40

x = 40/5 .... dividing both sides by 5

x = 8

20 oranges cost $8

--------------

Another way to approach the problem is to note that the jump from "5 oranges" to "20 oranges" is "times 4".

5*4 = 20

So we'll apply the "times 4" operation to the old cost of $2 to get the new cost being 2*4 = 8 dollars

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3 years ago

Find the mean, variance &a standard deviation of the binomial distribution with the given values of n and p.

MrMuchimi

A random variable following a binomial distribution over $n$ trials with success probability $p$ has PMF

$f_X(x)=\dbinom nxp^x(1-p)^{n-x}$

Because it's a proper probability distribution, you know that the sum of all the probabilities over the distribution's support must be 1, i.e.

$\displaystyle\sum_xf_X(x)=\sum_{x=0}^n\binom nxp^x(1-p)^{n-x}=1$

The mean is given by the expected value of the distribution,

$\mathbb E(X)=\displaystyle\sum_xf_X(x)=\sum_{x=0}^nx\binom nxp^x(1-p)^{n-x}$
$\mathbb E(X)=\displaystyle\sum_{x=1}^nx\frac{n!}{x!(n-x)!}p^x(1-p)^{n-x}$
$\mathbb E(X)=\displaystyle\sum_{x=1}^n\frac{n!}{(x-1)!(n-x)!}p^x(1-p)^{n-x}$
$\mathbb E(X)=\displaystyle np\sum_{x=1}^n\frac{(n-1)!}{(x-1)!((n-1)-(x-1))!}p^{x-1}(1-p)^{(n-1)-(x-1)}$
$\mathbb E(X)=\displaystyle np\sum_{x=0}^n\frac{(n-1)!}{x!((n-1)-x)!}p^x(1-p)^{(n-1)-x}$
$\mathbb E(X)=\displaystyle np\sum_{x=0}^n\binom{n-1}xp^x(1-p)^{(n-1)-x}$
$\mathbb E(X)=\displaystyle np\sum_{x=0}^{n-1}\binom{n-1}xp^x(1-p)^{(n-1)-x}$

The remaining sum has a summand which is the PMF of yet another binomial distribution with $n-1$ trials and the same success probability, so the sum is 1 and you're left with

$\mathbb E(x)=np=126\times0.27=34.02$

You can similarly derive the variance by computing $\mathbb V(X)=\mathbb E(X^2)-\mathbb E(X)^2$ , but I'll leave that as an exercise for you. You would find that $\mathbb V(X)=np(1-p)$ , so the variance here would be

$\mathbb V(X)=125\times0.27\times0.73=24.8346$

The standard deviation is just the square root of the variance, which is

$\sqrt{\mathbb V(X)}=\sqrt{24.3846}\approx4.9834$