A path of 0.5 meter wide runs round within a square garden of side 15 m.Find it's perimeter ?<br>

A couple book a cruise to Alaska that promises to refund 100 per day of rain on the seven day cruise up to a maximum of 300. The

zubka84 [21]

Answer:

the variance of the refund payment to the couple = 9463.394

Step-by-step explanation:

Given that :

A couple book a cruise to Alaska that promises to refund 100 per day of rain on the seven day cruise up to a maximum of 300.

It is possible that the couple won't be able to refund up 100 per day or more than 100 per day.

SO; let assume that the refund payment happens to be 0, 100,200, 300

Let X be the total refund payment on the seven day cruise.

We can say X = 0, if there is no rain on all 7 days.

$P(X = 0) = _nC_x * P^x * (1 - P)n-x$

$P(X = 0) = _7C_o * 0.2^0 * (1-0.2)^{7-0$

$P(X = 0) =1 * 1* (1-0.2)^{7$

$P(X = 0) =(0.8)^{7$

$P(X = 0) =0.2097152$

If it rains on any one day; then X = 100

$P(X = 100) = _nC_x * P^x * (1 - P)n-x$

$P(X = 100) = _7C_1 * 0.2^1 * (1-0.2)^{7-1$

$P(X = 0) =7 * 0.2* (1-0.2)^{6$

$P(X = 100) =7* 0.2* (0.8)^{6$

$P(X = 100) =0.3670016$

if it rains on any two day ; then X = 200

$P(X = 200) = _nC_x * P^x * (1 - P)n-x$

$P(X = 200) = _7C_2 * 0.2^2 * (1-0.2)^{7-2$

$P(X = 200) = 21 * 0.2^2 * (0.8)^{5$

$P(X = 200) = 0.2752512$

if it rains on any three day or more than that ; then X = 300

$P(X \ge 300) = 1 - P(X < 300) \\ \\ P(X \ge 300) = 1 - [P(X = 0) + P(X = 100) + P(X = 200)] \\ \\ P(X \ge 300) = 1 - [0.2097152 + 0.3670016 + 0.2752512] \\ \\ P(X \ge 300) = 0.148032$

Now; we have our probability distribution function as:

P(X = 0) = 0.2097152

P(X = 100) = 0.3670016

P(X = 200) = 0.2752512

P(X = 300) = 0.148032

In order to determine the variance of the refund payment to the couple; we use the formula:

variance of the refund payment to the couple $[Var X] =E [X^2] - (E [X])^2$

where;

$E[X^2] = \sum x^2 \times p \\ \\ E[X^2] = 0^2 * 0.2097152 + 100^2 * 0.3670016 + 200^2 * 0.2752512 + 300^2 * 0.148032 \\ \\ E[X^2] = 0 + 3670.016 + 11010.048+ 13322.88 \\ \\ E[X^2] =28002.944$

$(E [X]) = \sum x * p\\ \\ (E [X]) = 0 * 0.2097152 + 100 * 0.3670016 + 200 * 0.2752512 + 300 * 0.148032 \\ \\ (E [X]) = 0 + 36.70016 + 55.05024 + 44.4096\\ \\ (E [X]) = 136.16 \\ \\ (E [X])^2 = 136.16^2 \\ \\ (E [X])^2 = 18539.55$

NOW;

the variance of the refund payment to the couple = 28002.944 - 18539.55

the variance of the refund payment to the couple = 9463.394

7 0

3 years ago

Jane is building a bookcase with 4 shelves. Each shelf is 24 inches long. How much wood does Jane need to make the 4 shelves?

Ksivusya [100]

Answer: 96 inches of wood

Step-by-step explanation:

24 × 4 = 96

So he would need 96 inches of wood!

Hope this helps!!! Good luck!!! ;)

7 0

3 years ago

In your own words, explain the Normal Distribution and provide a real world example.

elena-14-01-66 [18.8K]

Answer:

The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:

Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:

$X \sim N(\mu , \sigma)$

The two parameters are:

$\mu$ who represent the mean and is on the center of the distribution

$\sigma$ who represent the standard deviation

One particular case is the normal standard distribution denoted by:

$Z \sim N(0,1)$

Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated

Step-by-step explanation:

The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:

Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:

$X \sim N(\mu , \sigma)$

The two parameters are:

$\mu$ who represent the mean and is on the center of the distribution

$\sigma$ who represent the standard deviation

One particular case is the normal standard distribution denoted by:

$Z \sim N(0,1)$

Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated

4 0

3 years ago

How to find the volume of a pyramid

lbvjy [14]