Pls help I’ve been stuck for days

Answer:

$22560

step 1

$270 × 4month

=$1880 for a month

step 2

$1880×12months

= $22560

Answer:

40

Step-by-step explanation:

137+143=280

280/7= 40

Answer:

Division/dividing/divide

Step-by-step explanation:

If Justin has 280 baseball cards, and if each page will only hold 7 cards per page, then by dividing 280 by 7 (280÷7) would equal to 40 pages.

Answer:

Step-by-step explanation:

(h×2)=(2×2)-(5×2)+7

2h=4-10+7

2h=-6+7

2h=1

2h/2=1/2

∴ h=1/2

Answer:

D 18%

Step-by-step explanation:

18/100 = 18%so D is the answer

The Cov(X,Y) = E(XY) - E(X)E(Y) = 1.26 - 0.76(1.70) = 0.02h) Find ρX,Y.To find the correlation coefficient of X and Y, we use the formula ρX,Y = Cov(X,Y) / (σXσY). We already calculated Cov(X,Y) to be 0.02. Now we need to calculate σX and σY. We calculated σX to be 0.638. We could not calculate σY because the variance was negative. Therefore, we cannot find the correlation coefficient of X and Y.

Find the marginal probability mass function pX(x). Round the answers to two decimal places.a.1) Px(0)a.2) Px(1)a.3) Px(2)We can use the following formula to find the marginal probability mass function: Px(x) = Σy P(x, y) where Σy is the sum of all the values of y for each value of x.

The table shows the joint probability mass function of the random variables X and Y.X/Y|0 |1 |2 |P(X=x)0 |0.12 |0.16 |0.280.6 |1 |0.18 |0.14 |0.320.64 |2 |0.10 |0.12 |0.22Let's now use the formula to find Px(0):Px(0) = Σy P(0, y) = P(0,0) + P(0,1) + P(0,2) = 0.12 + 0.16 + 0.28 = 0.56Now we'll find Px(1):Px(1) = Σy P(1, y) = P(1,0) + P(1,1) + P(1,2) = 0.18 + 0.14 = 0.32Lastly, we'll find Px(2):Px(2) = Σy P(2, y) = P(2,0) + P(2,1) + P(2,2) = 0.10 + 0.12 = 0.22b)

Find the marginal probability mass function pY(y). Round the answers to two decimal places.b.1) Py(0)b.2) Py(1)b.3) Py(2)We can use the following formula to find the marginal probability mass function: Py(y) = Σx P(x, y) where Σx is the sum of all the values of x for each value of y. The table shows the joint probability mass function of the random variables X and Y.X/Y|0 |1 |2 |P(X=x)0 |0.12 |0.16 |0.280.6 |1 |0.18 |0.14 |0.320.64 |2 |0.10 |0.12 |0.22

Let's now use the formula to find Py(0):Py(0) = Σx P(x, 0) = P(0,0) + P(1,0) + P(2,0) = 0.12 + 0.18 + 0.10 = 0.40Now we'll find Py(1):Py(1) = Σx P(x, 1) = P(0,1) + P(1,1) + P(2,1) = 0.16 + 0.14 + 0.12 = 0.42Lastly, we'll find Py(2):Py(2) = Σx P(x, 2) = P(0,2) + P(1,2) + P(2,2) = 0.28 + 0.14 + 0.22 = 0.64c) Find µXTo find µX, we use the formula µX = E(X) = Σx xP(X = x).

We can calculate the expected value of X by using the marginal probability mass function Px(x) that we previously calculated. The formula is: E(X) = Σx xPx(x) = 0(0.56) + 1(0.32) + 2(0.22) = 0 + 0.32 + 0.44 = 0.76Therefore, µX = 0.76d) Find μY.

Round the answer to two decimal places.To find µY, we use the formula µY = E(Y) = Σy yP(Y = y). We can calculate the expected value of Y by using the marginal probability mass function Py(y) that we previously calculated. The formula is: E(Y) = Σy yPy(y) = 0(0.40) + 1(0.42) + 2(0.64) = 0 + 0.42 + 1.28 = 1.70Therefore, µY = 1.70e) Find σX.To find the standard deviation of X, we can use the formula σX = sqrt(V(X)) where V(X) is the variance of X. To find the variance of X, we use the formula V(X) = E(X²) - [E(X)]². We already calculated E(X) to be 0.76. Now we need to calculate E(X²):E(X²) = Σx x²P(X = x) = 0²(0.56) + 1²(0.32) + 2²(0.22) = 0 + 0.32 + 0.88 = 1.20

Therefore, V(X) = E(X²) - [E(X)]² = 1.20 - 0.76² = 0.4064σX = sqrt(V(X)) = sqrt(0.4064) = 0.638f) Find σY.To find the standard deviation of Y, we can use the formula σY = sqrt(V(Y)) where V(Y) is the variance of Y. To find the variance of Y, we use the formula V(Y) = E(Y²) - [E(Y)]².

We already calculated E(Y) to be 1.70. Now we need to calculate E(Y²):E(Y²) = Σy y²P(Y = y) = 0²(0.40) + 1²(0.42) + 2²(0.64) = 0 + 0.42 + 1.28 = 1.70Therefore, V(Y) = E(Y²) - [E(Y)]² = 1.70 - 1.70² = -0.29σY = sqrt(V(Y)) = sqrt(-0.29)This is an invalid result, since the variance cannot be negative. Therefore, there may be an error in the calculations or in the values provided in the table.

We cannot find the standard deviation of Y.g) Find Cov(X, Y).To find the covariance of X and Y, we use the formula Cov(X,Y) = E(XY) - E(X)E(Y). We already calculated E(X) and E(Y) to be 0.76 and 1.70 respectively. Now we need to calculate E(XY):E(XY) = Σx Σy xyP(X = x, Y = y) = 0(0)(0.12) + 0(1)(0.16) + 0(2)(0.28) + 1(0)(0.18) + 1(1)(0.14) + 1(2)(0.00) + 2(0)(0.10) + 2(1)(0.12) + 2(2)(0.22) = 0 + 0 + 0 + 0 + 0.14 + 0 + 0 + 0.24 + 0.88 = 1.26

Therefore, Cov(X,Y) = E(XY) - E(X)E(Y) = 1.26 - 0.76(1.70) = 0.02h) Find ρX,Y.To find the correlation coefficient of X and Y, we use the formula ρX,Y = Cov(X,Y) / (σXσY). We already calculated Cov(X,Y) to be 0.02. Now we need to calculate σX and σY. We calculated σX to be 0.638. We could not calculate σY because the variance was negative. Therefore, we cannot find the correlation coefficient of X and Y.

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The working of T critical value calculator is explained

What is t test?

t test is the test used  if the sample standard deviation is known and population standard deviation is unknown.

t test is used if the sample standard deviation is known and population standard deviation is unknown.

Here, t value is calculated by the formula

\(t = \frac{\bar{x} - \mu}{\frac{s}{\sqrt{n}}}\)

\(\bar{x}\) = mean of the sample

\(\mu\) = mean of the population

s = standard deviation of sample

n = Number of samples

Now, with the help of degree of freedom (n - 1) and the level of significance, the critical value of t is to be noted from the t table. Let it be \(t_{critical}\)

if the value of t lies between \(-t_{critical}\) and \(+t_{critical}\) then the null hypothesis is accepted, otherwise the null hypothesis is rejected.

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Answer:

deepest part of dive is 2.5 feets below sea level ;

-2.5 feets

Step-by-step explanation:

Given :

Initial Position = 5.8 feets above sea level = +5.8

Deepest part of dive = x

Change in elevation between initial position and deepest part of dive = 8.3 feets

Position relative to sea level at deepest part of dive :

x = change in elevation - Initial position

x = 8.3 feets - 5.8 feets

x = 2.5 feets

Hence, deepest part of dive is 2.5 feets below sea level

The a = 0.01 critical value for the chi - square statistic with 13 degrees of freedom is given by 27.688.

Hence the correct option is (A).

Here given distribution is Chi - squared distribution.

two parameters of chi - squared distribution are given by ' a ' and ' d ' where d is degree of freedom.

The critical value against chi squared distribution changes according to the change of the values of a and d.

The table chi squared distribution is given by,

Here we have to find the critical value for the chi - squared statistic with 13 degrees of freedom when a = 0.01.

Therefore, a = 0.01 and d = 13

From the given table we can see that when a = 0.01 and d = 13 the critical value is given by 27.688.

Hence the correct option is (A).

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Answer:

63

Step-by-step explanation:

28/4 = 7 windows per hour

7 × 9 = 63 windows in 9 hours

Answer:

B) 666.6 miles per hour

Step-by-step explanation:

To solve this question, divide the 4000 miles with the 6 hours to get an answer in units of X miles per hour.

4000 miles/6 hours = 666.6 miles per hour

Answer:

For the middle one 20 /9  or 2 and 2/9

Step-by-step explanation:

20 /9  or 2 and 2/9

Do you need help with the rest or no?

To determine if the given function is linear or exponential or neither, we have to look for a common ratio or difference between any two consecutive terms. If the difference between any two consecutive terms is constant, then the function is linear.

If the ratio of any two consecutive terms is constant, then the function is exponential. If neither is true, then the function is neither linear nor exponential.

Given:

X 3 6 9 15 21 f(x) 100 103.4 106.916 114.309 122.215,

Now, let's calculate the difference between each pair of consecutive terms to see if it is constant:

f(3) - f(X) = 100 - f(X)f(6) - f(3) = 103.4 - 100 = 3.4f(9) - f(6) = 106.916 - 103.4 = 3.516f(15) - f(9) = 114.309 - 106.916 = 7.393f(21) - f(15) = 122.215 - 114.309 = 7.906;

We can see that the differences are not constant.

Therefore, the given function is neither linear nor exponential. Hence, the formula of the function cannot be determined. Therefore, the answer is NONE.

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Answer:

Eight times ten plus six times one plus two times one-tenth plus seven times one-thousandth.

Step-by-step explanation:

(8 x 10) = eight times ten

(6 x 1) = six times one

(2 x 0.1) = two times one-tenth

(7 x 0.001) = seven times one-thousandth

I am not always the best with the equations to words stuff, so please comment if I am wrong!

The probability of getting a poker hand (5 cards) containing 3 cards of one denomination and 2 cards of a second denomination or full house is 0.00144 or about 0.14%.

To calculate the probability of getting a full house, we need to first determine the total number of possible 5-card hands. This can be done using the formula for combinations:

C(52, 5) = 2,598,960

There are 2,598,960 possible 5-card hands from a standard deck of 52 cards.

Next, we need to count the number of ways to get a full house. To do this, we first choose the denomination for the 3-of-a-kind (there are 13 options), then choose which 3 of the 4 cards of that denomination to include (there are C(4,3) ways to do this), and finally choose the denomination for the pair (there are 12 remaining denominations to choose from), and which 2 of the 4 cards of that denomination to include (there are C(4,2) ways to do this). So the total number of full houses is:

13 * C(4,3) * 12 * C(4,2) = 3,744

Therefore, the probability of getting a full house is:

P(full house) = 3,744 / 2,598,960

≈ 0.00144

So the probability of getting a full house is approximately 0.00144 or about 0.14%.

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False. The statement is incorrect. Both dynamic games and static games can be represented in either extensive form or normal form, depending on the nature of the game and the level of detail required.

The extensive form is typically used to represent dynamic games, where players make sequential decisions over time, taking into account the actions and decisions of other players. This form includes a timeline or game tree that visually depicts the sequence of moves and information sets available to each player.

On the other hand, the normal form is commonly used to represent static games, where players make simultaneous decisions without knowledge of the other players' choices. The normal form presents the game in a matrix or tabular format, specifying the players' strategies and the associated payoffs.

While it is true that dynamic games are often represented in the extensive form and static games in the normal form, it is not a strict requirement. Both forms can be used to represent games of either type, depending on the specific context and requirements.

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the probability is 1/6 or approximately 0.1667, which can also be expressed as 16.67%

To find the probability that Melinda can make an integer between 10 and 20 (inclusive) by forming a two-digit number from the rolls of two standard six-sided dice, we need to determine the number of favorable outcomes and the total number of possible outcomes.

Let's list the favorable outcomes, which are the two-digit numbers between 10 and 20:

11, 12, 13, 14, 15, 16

There are 6 favorable outcomes.

Next, let's determine the total number of possible outcomes when rolling two dice. Since each die has 6 sides, there are 6 * 6 = 36 possible outcomes.

Therefore, the probability that Melinda can make an integer between 10 and 20 is:

Probability = (Number of favorable outcomes) / (Total number of possible outcomes)

          = 6 / 36

          = 1 / 6

So, the probability is 1/6 or approximately 0.1667, which can also be expressed as 16.67%.

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Answer:  -11

Step-by-step explanation:

y²+7y+1​

(-3)^2 +7*(-3)+1

9 -21 + 1 = -11

The cost to you of attending the game instead of going to work is 85$

They are the set of numbers and symbols that are related by the different mathematical operation signs such as addition, subtraction, multiplication, division among others.

To solve this problem we must perform the following algebraic operations with the given information

Information about the problem:

Calculating how much will cost attending the game:

Total cost = (time of the game*Hours paid for work) + Transportation cost

Total cost = (12*5) + 25

Total cost = 85$

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The probability of winning $1000 a day for life is approximately 5.245 x 10^-11 and the probability of winning $1000 a week for life is approximately 1.07 x 10^-8. The probability of winning the jackpot ($1000 a day for life) is 1/(60^5 * 4), while the probability of winning $1000 a week for life is 1/(60^5).

In the Florida Lottery Cash4Life game, a player must select five numbers from 1 to 60 and then one Cash Ball number from 1 to 4. The jackpot prize is $1000 a day for life if all five numbers and the Cash Ball match the winning numbers drawn on Monday nights. If just all five numbers match the winning numbers, the player will win $1000 a week for life.
To determine the probability of winning $1000 a day for life, we can use the formula for the probability of independent events: P(A and B) = P(A) x P(B)

(a) To win the jackpot of $1000 a day for life, the player needs to match all five numbers and the Cash Ball. There are 60 options for each of the five numbers and 4 options for the Cash Ball. The total number of possible outcomes is 60^5 (60 choices for each of the five numbers) times 4 (for the Cash Ball). So the probability of winning the jackpot is 1/(60^5 * 4). (b) To win $1000 a week for life, the player needs to match only the five numbers, without considering the Cash Ball. The total number of possible outcomes for this scenario is 60^5. Therefore, the probability of winning $1000 a week for life is 1/(60^5).

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Answer:

38.5 is the volume

Step-by-step explanation:

3.5x4=14

14x5.5=77

now you divide by two because it's a triangle

Answer:

234

Step-by-step explanation:

Answer:

You add the powers, so (X^3)(x^-17)=x^n n= (3+-17) Meaning n=-14

Step-by-step explanation:

Answer:

b. To find the probability a customer who ordered pancakes came to thediner late, we need to look at the intersection of the "pancakes" row and the "late" column. This gives us a probability of 0.1, or 10%

c. To determine whether breakfast choice and meal time are independent, we need to see if the probability of one event changes based on the occurrence of the other event. In this case, it seems that breakfast choice and meal time are not independent, as the probability of being late seems to differ based on what breakfast item the customer chose. For example, the probability of being late is higher for customers who ordered pancakes compared to those who ordered cereal. Therefore, the choice of breakfast item appears to be related to the probability of being late, and so breakfast choice and meal time are not independent.

Step-by-step explanation:

Answer:

B

Step-by-step explanation:

because there's one square on the bottom and four triangles on the sides

The general solution of the system of differential equation is given by x₂ = c₁(r₁\(e^{(r_{1} t)}\)) + c₂(r₂\(e^{(r_{2} t)}\)) where c₁ and c₂ are constants.

System of equations are ,

x₁' = X₁ + X₂ ,

x₂ = 4x₁+ x₂.

To decouple the given system of differential equations,

Eliminate one variable at a time.

Expressing x₂ in terms of x₁.

From the second equation, we have,

x₂ = 4x₁ + x₂

Rearranging this equation, we get,

⇒ x₂ - x₂ = 4x₁

⇒ 0 = 4x₁

⇒x₁ = 0

Now, let us substitute this value of x₁ into the first equation,

x₁' = x₁ + x₂

Since x₁ = 0, we have,

⇒x₁' = 0 + x₂

⇒ x₁' = x₂

Now, decoupled the system into two separate equations,

x₁' = x₂

x₂' = 4x₁ + x₂

To solve these equations, differentiate the first equation with respect to time,

x₁'' = x₂'

Substituting the value of x₂' from the second equation, we get,

x₁'' = 4x₁ + x₂

Since x₂ = x₁', we can rewrite the equation as,

⇒x₁'' = 4x₁ + x₁'

This is a second-order linear homogeneous differential equation.

Solve it by assuming a solution of the form x₁ = \(e^{(rt)}\), where r is a constant.

Differentiating x₁ twice, we get,

x₁'' = r²\(e^{(rt)}\)

Substituting this back into the differential equation, we have,

⇒r²\(e^{(rt)}\) = 4\(e^{(rt)}\) + r\(e^{(rt)}\)

Dividing both sides by \(e^{(rt)}\), we obtain,

⇒r² = 4 + r

Rearranging the equation, we have,

⇒r² - r - 4 = 0

To find the values of r, solve this quadratic equation.

Using the quadratic formula, we get,

r = (1 ± √(1 - 4(-4))) / 2

r = (1 ± √(1 + 16)) / 2

r = (1 ± √17) / 2

The solutions for r are,

r₁ = (1 + √17) / 2

r₂ = (1 - √17) / 2

The general solution for x₁ is given by,

x₁ = c₁\(e^{(r_{1} t)}\) + c₂\(e^{(r_{2} t)}\)

where c₁ and c₂ are constants.

Now, let us find x₂ using the first equation,

x₂ = x₁'

Differentiating the general solution of x₁ with respect to time, we have,

x₂ = c₁(r₁\(e^{(r_{1} t)}\)) + c₂(r₂\(e^{(r_{2} t)}\))

Therefore, the general solution for x₂ of the differential equation is equal to x₂ = c₁(r₁\(e^{(r_{1} t)}\)) + c₂(r₂\(e^{(r_{2} t)}\)) where c₁ and c₂ are constants.

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The above question is incomplete , the complete question is:

Find the general solution of the following system of differential equations by decoupling: x₁' = X₁ + X₂ , x₂ = 4x₁+ x₂.

Based on the given information and performing a one-sample t-test, the conclusion is that if the population mean (μ) is greater than 30.8294 km per litre, we reject the null hypothesis.

Given:

Sample mean (x') = 30 km per litre

Sample standard deviation (s) = 3.5 km per litre

Sample size (n) = 50

Significance level (α) = 0.05 (5%)

Null hypothesis \((H_0)\): The mean petrol consumption of the new car is equal to or higher than that of the existing car.

Alternative hypothesis \((H_1)\): The mean petrol consumption of the new car is lower than that of the existing car.

We'll calculate the test statistic (t-value) and compare it with the critical t-value.

The formula for the t-value is:

t = (x' - μ) / (s / √n)

where μ is the population mean (mean petrol consumption of the existing car).

First, we need to calculate the critical t-value from the t-distribution table. Since we have a significance level of 0.05 and (50 - 1) degrees of freedom, the critical t-value for a one-tailed test is approximately -1.677.

Now, let's calculate the t-value:

t = (30 - μ) / (3.5 / √50)

To reject the null hypothesis, the t-value should be less than the critical t-value.

Simplifying the equation:

t = (30 - μ) / (0.495)

To find the critical value, we compare it with the calculated t-value:

-1.677 > (30 - μ) / (0.495)

Multiplying both sides of the inequality by 0.495:

-0.8294 > 30 - μ

Rearranging the inequality:

μ > 30 + 0.8294

μ > 30.8294

Therefore, if the population mean (μ) is greater than 30.8294 km per litre, we reject the null hypothesis in favor of the alternative hypothesis, concluding that the mean petrol consumption of the new car is lower than that of the existing car.

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Answer:

  $22

Step-by-step explanation:

Given a table of popcorn volumes and prices, you want to know a reasonable price for 60 ounces of popcorn.

Plotting the given sizes and costs on a graph, we see that the relationship is linear. Using the two points (size, cost) = (10, 6) and (20, 8), we find the relation to be ...

  m = (y2 -y1)/(x2 -x1) = (8 -6)/(20 -10) = 2/10 = 0.2 . . . . slope

  b = y1 -m(x1) = 6 -0.2(10) = 4 . . . . . . y-intercept

Then the equation of the line is ...

  y = mx +b

  y = 0.2x +4

Using x=60, we find the corresponding price is ...

  y = 0.2(60) +4 = 12 +4 = 16

A consistent price is $16 for a 60-ounce container of popcorn.

__

Additional comment

The price equation suggests a fixed cost ($4) and a volume-related cost ($0.20 per ounce).