Simplify i to the 31st power

let dogs be heads. Let cats be tails. A coin has two sides, in which you are flipping two of them. Note that there can be the possible outcomes  

h-h, h-t, t-h, t-t.  

How this affects the possibility of two dogs & two cats. Note that there are 1/2 a chance of getting those two (with the others being one of each), which means that out of 4 chances, 2 are allowed.  

2/4 = 1/2  

50% is your answer

Heads represents cats and tails represents dogs. There is two coins because we are checking the probability of two pets. You have to do the experiment to get your set of data, once you get your set of data, you will be able to divide it into the probability for cats or dogs. To change the simulation to generate data for 3 pets, simply add a new coin and category for the new pet.

Hope this helps you out!

9514 1404 393

Answer:

  15

Step-by-step explanation:

For numbers to be divisible by 3, the sum of their digits must be divisible by 3.

This means we require ...

  (7 + 1 + 2 + 3 + A + 3 + 2) mod 3 = 0   ⇒   A mod 3 = 0

  (2 + B + 2 + 5 + 6 + 8 + 9) mod 3 = 0   ⇒   (2+B) mod 3 = 0   ⇒   B mod 3 = -2

  (4 + 5 + 0 + A + B + C + 6) mod 3 = 0   ⇒   (C -2) mod 3 = 0

Possible values of C are 2, 5, 8. Their sum is 15.

_____

For example, let A=0, B=1, C=2. Then we have ...

  7123032 = 2374344×3

  2125689 = 708563×3

  4500126 = 1500042×3

Answer:

-36/7

Step-by-step explanation:

-22-14=6x+x

-36=7x

-36/7=7x/7

x=-36/7

Answer:

(w^3)^8 * (w^5)^5 = w^49

Step-by-step explanation:

(w^24) * (w^25)

using exponent rule

w^24 • w^25 = w^24+25

w^49

Answer:

Step-by-step explanation:

(W^24)*(W^25)

W^24+25

=W^49

Answer:

0.01375 = 1.375% probability that the number of lost-time accidents occurring over a period of 10 days will be no more than 2.

Step-by-step explanation:

We have the mean during the interval, which means that the Poisson distribution is used.

Poisson distribution:

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:

[tex]P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}[/tex]

In which

x is the number of sucesses

e = 2.71828 is the Euler number

[tex]\mu[/tex] is the mean in the given interval.

Lost-time accidents occur in a company at a mean rate of 0.8 per day.

This means that [tex]\mu = 0.8n[/tex], in which n is the number of days.

10 days:

This means that [tex]n = 10, \mu = 0.8(10) = 8[/tex]

What is the probability that the number of lost-time accidents occurring over a period of 10 days will be no more than 2?

This is:

[tex]P(X \leq 2) = P(X = 0) + P(X = 1) + P(X = 2)[/tex]

In which

[tex]P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}[/tex]

[tex]P(X = 0) = \frac{e^{-8}*8^{0}}{(0)!} = 0.00034[/tex]

[tex]P(X = 1) = \frac{e^{-8}*8^{1}}{(1)!} = 0.00268[/tex]

[tex]P(X = 2) = \frac{e^{-8}*8^{2}}{(2)!} = 0.01073[/tex]

So

[tex]P(X \leq 2) = P(X = 0) + P(X = 1) + P(X = 2) = 0.00034 + 0.00268 + 0.01073 = 0.01375[/tex]

0.01375 = 1.375% probability that the number of lost-time accidents occurring over a period of 10 days will be no more than 2.

Answer:

5/4

Step-by-step explanation:

Use the slope formula which is y2-y1/x2-x1.

1. Plug the given values into the equation: 3-(-7)/4-(-4)=5/4

Answer:

4

Step-by-step explanation:

2x - (4y - 3) + 5xz

Let  x = -3, y = 2, and z = ‐1.

2(-3) -( 4(2) -3) +5(-3)(-1)

-6 - (8-3) +15

-6 - 5 +15

-11 +15

4

Answer:

mean=21.17

mode=20,22

median=3.5

range=15

Step-by-step explanation: MEAN=sum of all observations/ no. of observations

mean=22+20+14+22+29+20/6

mean=127/6

mean=21.17

MODE= most frequent observations

mode=22,20

MEDIAN=1/2(n/2+n+2/2)

=1/2(6/2+6+2/2)

=1/2(3+4)

=1/2(7)

=7/2

=3.5

RANGE=X max -X min

=29-14

=15

Answer:

25288

Step-by-step explanation:

shown in the picture

Answer:

46,000 yards

Step-by-step explanation:

if in the hundreds place the number is 0-499 round down

if it's 500-999 round up

9514 1404 393

Answer:

  (b)  x = 1

Step-by-step explanation:

A graph shows the solution to f(x) = g(x) is x = 1.

__

We want to solve ...

  g(x) -f(x) = 0

  x^3 +2x^2 -x -2 -(-11/3x +11/3) = 0

  x^2(x +2) -1(x +2) +11/3(x -1) = 0 . . . . . factor first terms by grouping

  (x^2 -1)(x +2) +11/3(x -1) = 0 . . . . .  . the difference of squares can be factored

  (x -1)(x +1)(x +2) +(x -1)(11/3) = 0 . . . . we see (x-1) is a common factor

  (x -1)(x^2 +3x +2 +11/3) = 0

The zero product rule tells us this will be true when x-1 = 0, or x = 1.

__

The discriminant of the quadratic factor is ...

  b^2 -4ac = 3^2 -4(1)(17/3) = 9 -68/3 = -41/3

This is less than zero, so any other solutions are complex.

Answer:

Orthocenter would be in the middle of the shape.

Step-by-step explanation:

B.

Answer:

Its quantitive cause its giving a number and quantity/quantitive is for numbers

Answer:

The data is quantitative (because it is asking for measurement or numbers).

Step-by-step explanation:

The second and third I'm not sure how to answer, however,

"A discrete function is a function with distinct and separate values. This means that the values of the functions are not connected with each other. For example, a discrete function can equal 1 or 2 but not 1.5. A continuous function, on the other hand, is a function that can take on any number within a certain interval. For example, if at one point, a continuous function is 1 and 2 at another point, then this continuous function will definitely be 1.5 at yet another point. A continuous function always connects all its values while a discrete function has separations. Now, let's look at these two types of functions in detail."

Hope this helps :)

Answer:

A

Step-by-step explanation:

the function for this graph is:

[tex]y = {(x - 1)}^{2} [/tex]

so the domain (the input AKA THE x values) is all the real numbers.

Answer:

is the second answer 2x+1/x-1

Work Shown:

1 pound = 16 ounces

4*(1 pound) = 4*(16 ounces)

4 pounds = 64 ounces

Step-by-step explanation:

50-20=30 rate of markup

Answer:

The expected value for an event with outcomes:

{x₁, x₂, ..., xₙ}

Each one with probability:

{p₁, p₂, ..., pₙ}

Is just:

Ev = x₁*p₁ + ... + xₙ*pₙ

here we have two outcomes:

x₁ = the object worths $25

x₂ = the object is worth $4.

Each one with probability p₁ and p₂ respectively, such that:

p₁ + p₂ = 1

Then the expected value is:

Ev = p₁*($25) + p₂*($4)

Now we want to know how should be the probabilities, such that buying the object for $16 is whort.

Well, the purchase will be whort if the expected value is larger than $16.

This is equivalent to:

p₁*($25) + p₂*($4) - $16 > $0

Knowing that:

p₁ + p₂ = 1

we can rewrite:

p₂ = 1 - p₁

replacing that in the above inequality we get:

p₁*($25) + ( 1 - p₁)*($4) - $16 > $0

Now we can solve this for p₁

p₁*($25 - $4) + $4 - $16 > $0

p₁*$21 - $12 > $0

p₁*$21 > $12

p₁ > $12/$21 = 0.571

The probability of the object being authentic should be larger than  0.571 to take the gamble.

Answer:

2ab(3b^2+2a+4)

Step-by-step explanation:

6ab^3 + 4a^2b + 8ab

2*3*a*b*b^2 +2*2*a*a*b +2*2*2*a*b

Factor out the common terms

2ab( 3*b^2 +2*a +2*2)

2ab(3b^2+2a+4)

Answer:

b

Step-by-step explanation:

Answer:

12

Step-by-step explanation:

Answer:

0.2405 = 24.05% probability that the sample proportion of households spending more than $125 a week is less than 0.31.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score 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. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

Assume the population proportion is 0.34 and a simple random sample of 124 households is selected from the population.

This means that [tex]p = 0.34, n = 124[/tex]

Mean and standard deviation:

[tex]\mu = p = 0.34[/tex]

[tex]s = \sqrt{\frac{0.34*0.66}{124}} = 0.0425[/tex]

What is the probability that the sample proportion of households spending more than $125 a week is less than 0.31?

This is the p-value of Z when X = 0.31, so:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]Z = \frac{0.31 - 0.34}{0.0425}[/tex]

[tex]Z = -0.705[/tex]

[tex]Z = -0.705[/tex] has a p-value of 0.2405.

0.2405 = 24.05% probability that the sample proportion of households spending more than $125 a week is less than 0.31.

Answer:

[tex]P(S&G) =0.7941[/tex]

Step-by-step explanation:

From the question we are told that:

Sample size [tex]n=16+18=>34[/tex]

N0 of  Large [tex]L=16[/tex]

N0 of Small [tex]S=18[/tex]

N0 large Green [tex]L_g=9[/tex]

N0 of small White [tex]S_w=3[/tex]

Therefore

Number of green marbles [tex]N0(G)=9+(18-3)[/tex]

Number of green marbles [tex]N0(G)=24[/tex]

Generally the Number of both small and green Marble is

[tex]N0 of (S&G)= 18 - 3 = 15[/tex]

Generally the  probability that it is small or green P(S&G) is mathematically given by

[tex]P(S&G) = \frac{(18 + 24 - 15)}{(18 + 16)}[/tex]

[tex]P(S&G) =0.7941[/tex]

Answer:

Increasing a number by 5% and then by 20% is the same as increasing the original number by 26%.

Step-by-step explanation:

Take a number, x.

Now increase it by 5%.

1.05x

Now increase it by 20%.

1.2 * 1.05x = 1.26x

1.26x = 126% of x = 100% of x + 26% of x

100% of x is the same as x, so it is the same as the original x.

The increase is 26% of the original number.

Increasing a number by 5% and then by 20% is the same as increasing the original number by 26%.

Answer:

Kindly check explanation

Step-by-step explanation:

Rounding each number to 4 significant figures and expressing in standard notation :

(a) 102.53070,

Since the number starts with a non-zero, the 4 digits are counted from the left ;

102.53070 = 102.5 (4 significant figures) = 1.025 * 10^2

(b) 656.980,

Since the number starts with a non-zero, the 4 digits are counted from the left ; the value after the 4th significant value is greater than 5, it is rounded to 1 and added to the significant figure.

656.980 = 657.0 (4 significant figures) = 6.57 * 10^2

(c) 0.008543210,

Since number starts at 0 ; the first significant figure is the first non - zero digit ;

0.008543210 = 0.008543 (4 significant figures) = 8.543 * 10^-3

(d) 0.000257870,

Since number starts at 0 ; the first significant figure is the first non - zero digit ;

0.000257870 = 0.0002579 (4 significant figures) = 2.579 * 10^-4

(e) -0.0357202,

Since number starts at 0 ; the first significant figure is the first non - zero digit ;

-0.0357202 = - 0.03572 (4 significant figures) = - 3.572* 10^-2

Answer:

4(a).

Expression of dy/dx :

[tex]{ \tt{ \frac{dy}{dx} = - 2(3 - 2x) {}^{2} + 24}}[/tex]

5(a).

[tex]{ \tt{ \frac{dy}{dx} = 54 - 2(2x - 7) {}^{2} }}[/tex]

Answer:

0.0475 = 4.75% probability that a randomly selected complaint takes more than 15 minutes to be settled.

Step-by-step explanation:

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score 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. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Mean of 10 minutes and a standard deviation of 3 minutes

This means that [tex]\mu = 10, \sigma = 3[/tex]

Find the probability that a randomly selected complaint takes more than 15 minutes to be settled.

This is 1 subtracted by the p-value of Z when X = 15, so:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]Z = \frac{15 - 10}{3}[/tex]

[tex]Z = 1.67[/tex]

[tex]Z = 1.67[/tex] has a p-value of 0.9525.

1 - 0.9525 = 0.0475.

0.0475 = 4.75% probability that a randomly selected complaint takes more than 15 minutes to be settled.

Answer:

p - 2q and p - 3q

Step-by-step explanation:

A Series is given to us and we need to find the next two terms of the series . The given series to us is ,

[tex]\rm\implies Series = p+q , p , p - q [/tex]

Note that when we subtract the consecutive terms we get the common difference as "-q" .

[tex]\rm\implies Common\ Difference = p - (p + q )= p - p - q =\boxed{\rm q}[/tex]

Therefore the series is Arithmetic Series .

Arithmetic Series:- The series in which a common number is added to obtain the next term of series .

And here the Common difference is -q .

Fourth term :-

[tex]\rm\implies 4th \ term = p - q - q = \boxed{\blue{\rm p - 2q}}[/tex]

Fifth term :-

[tex]\rm\implies 4th \ term = p - 2q - q = \boxed{\blue{\rm p - 3q}}[/tex]

Therefore the next two terms are ( p - 2q) and ( p - 3q ) .

Answer:

[tex]\mathbb{R} \backslash \displaystyle \left\lbrace \left. \frac{1}{23}\, \left(k\, \pi + \frac{\pi}{2}\right) \; \right| k \in \mathbb{Z} \right\rbrace[/tex].

In other words, the [tex]x[/tex] in [tex]f(x) = 3\, \tan(23\, x)[/tex] could be any real number as long as [tex]x \ne \displaystyle \frac{1}{23}\, \left(k\, \pi + \frac{\pi}{2}\right)[/tex] for all integer [tex]k[/tex] (including negative integers.)

Step-by-step explanation:

The tangent function [tex]y = \tan(x)[/tex] has a real value for real inputs [tex]x[/tex] as long as the input [tex]x \ne \displaystyle k\, \pi + \frac{\pi}{2}[/tex] for all integer [tex]k[/tex].

Hence, the domain of the original tangent function is [tex]\mathbb{R} \backslash \displaystyle \left\lbrace \left. \left(k\, \pi + \frac{\pi}{2}\right) \; \right| k \in \mathbb{Z} \right\rbrace[/tex].

On the other hand, in the function [tex]f(x) = 3\, \tan(23\, x)[/tex], the input to the tangent function is replaced with [tex](23\, x)[/tex].

The transformed tangent function [tex]\tan(23\, x)[/tex] would have a real value as long as its input [tex](23\, x)[/tex] ensures that [tex]23\, x\ne \displaystyle k\, \pi + \frac{\pi}{2}[/tex] for all integer [tex]k[/tex].

In other words, [tex]\tan(23\, x)[/tex] would have a real value as long as [tex]x\ne \displaystyle \frac{1}{23} \, \left(k\, \pi + \frac{\pi}{2}\right)[/tex].

Accordingly, the domain of [tex]f(x) = 3\, \tan(23\, x)[/tex] would be [tex]\mathbb{R} \backslash \displaystyle \left\lbrace \left. \frac{1}{23}\, \left(k\, \pi + \frac{\pi}{2}\right) \; \right| k \in \mathbb{Z} \right\rbrace[/tex].