State the property that is demonstrated: (3)(8) = (8)(3).

Simplify the expression (2^3x5^3) x ( 2x5^4)^3 Fill in the blank with the correct values. PLZ if u know how to do this PLZ give

Dmitry [639]

Answer:

244140625000

Step-by-step explanation:

4 0

3 years ago

Let X equal the number of flips of a fair coin that are required to observe

Nataliya [291]

Answer:

(a) I attached a photo with the diagram.

(b) $f(x) = \big( \frac{1}{2} \big)^{x-1}$

(c) 1/4

(d) 4

(e) $k^2/2$

Step-by-step explanation:

(a) I attached a photo with the diagram.

(b) The easiest way to think about this part is in terms of combinatorics. Think about it like this.

To begin with, look at the three each level of the three represents a possible outcome of throwing the coin n-times. If you throw the coin 3 times at the end in total there are 8 possible outcomes. But The favorable outcomes are just 2.

1 - Your first outcome is HEADS and all the others are different except the last one.

2 - Your first outcome is TAILS and all the others are different except the last one.

Therefore the probability of the event is

$f(x) = P(X=x) = \frac{2}{2^x} = \frac{1}{2^{x-1}} = \big( \frac{1}{2} \big)^{x-1}$

(c)

P(X = 0) = 0 because it is not possible to have two consecutive tails or heads.

$E(X > 4) = 1 - P(X \leq 3) = 1 - ( P(X = 0 ) + P(X = 1) + P(X = 2) + P(X = 3))\\= 1 - ( \frac{1}{2} + \frac{1}{4} ) = \frac{1}{4}$

(d)

Remember that this is a geometric distribution therefore

$E[X] = p/(1-p)$ , in this case $p = 1/2$ so $E[X] = 1$ and

$E[X+1]^2 = ( E[X] +1 )^2 = (1+1)^2 = 2^2 = 4$

Also

(e)

This is a geometric distribution so its variance is

$Var(X) = \frac{1-p}{p^2} = 1/2 / 1/4 = 1/2$

And using properties of variance

$Var(kX - k ) = Var(kX) = k^2 var(X) = k^2 /2$

3 0

4 years ago

Explain how you would name a sorting rule for 1 square, 1 rectangle, and 1 triangle.

Makovka662 [10]

Answer:

We can sort them by the number of corners or sides.

Step-by-step explanation:

We can sort the given figures such as:

1 square, 1 rectangle, and 1 triangle.

by the number of corners each have as we know that a triangle has three corners or the vertex while a square and a rectangle have four corners.

Also a triangle is a polygon which is made up of three sides while a rectangle and a square are made up of four sides.

5 0

3 years ago

Read 2 more answers

PLEASE ANSWER FOR ME I REALLY NEED HELP. CORRECT ANSWERS ONLY

larisa [96]

Answer:

D, B, F

Step-by-step explanation:

$2 each pound

x= pounds

y= total cost

1 pound= $2

the $2 : constant

the number of pounds: variable

the equation is y=2x

1 pound: $2

2 pounds: $4

4 pounds: $8

5 pounds: $10

these also could be written as coordinates

the coordinates are (1,2),(2,4),(4,8),(5,10)

6 0

3 years ago

Read 2 more answers

A catering company provides packages for weddings and for showers. The cost per person for small groups

Tomtit [17]

Using the <em>normal distribution and the central limit theorem</em>, it is found that the probability the mean cost of the weddings is more than the mean cost of the showers is of 0.9665.

<h3>Normal Probability Distribution</h3>

In a normal distribution with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

It measures how many standard deviations the measure is from the mean.

After finding the z-score, we look at the z-score table and find the p-value associated with this z-score, which is the percentile of X.

By the Central Limit Theorem, the sampling distribution of sample means of size n has standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

When two variables are subtracted, the mean is the subtraction of the means, while the standard error is the square root of the sum of the variances.

<h3>What is the mean and the standard error of the distribution of differences?</h3>

For each sample, they are given by:

$\mu_W = 82.3, s_W = \frac{18.2}{\sqrt{9}} = 6.0667$

$\mu_S = 65, s_S = \frac{17.73}{\sqrt{6}} = 7.2382$

For the distribution of differences, we have that:

$\mu = \mu_W - \mu_S = 82.3 - 65 = 17.3$

$s = \sqrt{s_W^2 + s_S^2} = \sqrt{6.0667^2 + 7.2382^2} = 9.4444$

The probability the mean cost of the weddings is more than the mean cost of the showers is P(X > 0), that is, <u>one subtracted by the p-value of Z when X = 0</u>, hence:

$Z = \frac{X - \mu}{\sigma}$

By the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$Z = \frac{0 - 17.3}{9.4444}$

$Z = -1.83$

$Z = -1.83$ has a p-value of 0.0335.

1 - 0.0335 = 0.9665.

More can be learned about the <em>normal distribution and the central limit theorem</em> at brainly.com/question/24663213

5 0

2 years ago