20t- (8t+ 50s + 200)

Answer:

Step-by-step explanation:

h

The derivative of the function P(x) = 7x - ln(7x) is P'(x) = 7 - (1/x).

To evaluate the derivative of the function P(x) = 7x - ln(7x), we need to apply the rules of differentiation.

The derivative of a function represents the rate at which the function is changing with respect to its independent variable.

For the given function, we can differentiate each term separately using the rules of differentiation:

The derivative of 7x with respect to x is simply 7, since the derivative of a constant times x is the constant itself.

The derivative of ln(7x) with respect to x involves the chain rule.

The chain rule states that if we have a composite function, such as ln(g(x)), then its derivative is given by (1/g(x)) \(\times\) g'(x).

Applying the chain rule to the second term, we have:

d/dx [ln(7x)] = (1/(7x)) \(\times\) d/dx [7x]

Since the derivative of 7x is 7, we can simplify this further:

d/dx [ln(7x)] = (1/(7x)) \(\times\) 7 = 1/x

Now, adding up the derivatives of the individual terms, we have:

P'(x) = 7 - (1/x)

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Answer:

it can be use in equation

An irrational number is a number that cannot be expressed as a fraction for any integers and. . Irrational numbers have decimal expansions that neither terminate nor become periodic.

The odds ratio for people who are afraid of heights being afraid of flying can be calculated using a case-control study design. In this design, individuals with and without a fear of flying are compared to determine the odds of having a fear of flying if someone already has a fear of heights. The odds ratio can be calculated by dividing the odds of having a fear of flying among those who are afraid of heights by the odds of having a fear of flying among those who are not afraid of heights. A higher odds ratio indicates a stronger association between the two fears.

Odds ratio is a measure of the strength of association between two variables. In this case, we are interested in the association between a fear of heights and a fear of flying. By calculating the odds ratio, we can determine if there is a higher likelihood of having a fear of flying if someone already has a fear of heights.

In conclusion, the odds ratio for people afraid of heights being afraid of flying can be calculated using a case-control study design. The higher the odds ratio, the stronger the association between the two fears. By understanding this relationship, we can better understand how different fears may be related and how they can impact our lives.

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The correlation coefficient that represents the strongest relationship between two variables is -0.75.

In correlation coefficients, the absolute value indicates the strength of the relationship between variables. The strength of the association increases with the absolute value's proximity to 1.

The maximum absolute value in this instance is -0.75, which denotes a significant negative correlation. The relevance of the reverse correlation value of -0.75 is demonstrated by the noteworthy unfavorable correlation between the two variables.

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Answer:

Use a model to find the sum of two fractions with the same denominator

Add fractions with a common denominator without a model

Add fractions with a common denominator that contain a variable h

Step-by-step explanation:

h

The residual standard error is a useful measure of the precision and accuracy of a regression model's predictions, and it helps to assess the goodness of fit of the model.

The measure that indicates how precise a prediction of y is based on x or how inaccurate the prediction might be is called the residual standard error (RSE).

RSE is a measure of the variation or dispersion of the errors (or residuals) in a regression model. It is calculated by taking the square root of the sum of the squared residuals divided by the degrees of freedom.

The RSE provides an estimate of the standard deviation of the errors, and it is expressed in the same units as the response variable y.

In other words, the RSE measures the average distance that the observed values deviate from the predicted values in the regression model.

A smaller RSE indicates that the model is better at predicting the response variable, while a larger RSE indicates that the model has higher prediction error and may not be as accurate.

In summary, the residual standard error is a useful measure of the precision and accuracy of a regression model's predictions, and it helps to assess the goodness of fit of the model.

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The measure that indicates how precise a prediction of y is based on x, or conversely, how inaccurate the prediction might be, is called the residual standard error (RSE). The RSE is a measure of the average distance that the observed values fall from the predicted values, and it is typically expressed in the same units as the response variable (y). A smaller RSE indicates a better fit of the model to the data, and a larger RSE indicates a poorer fit.

The cost to make 19 pounds of fudge is, $80.75

Multiplication means to add number to itself a particular number of times. Multiply will be viewed as a process of repeated addition.

Given that;

Each pound of fudge costs $4.25 to make.

Here, Brandon is planning to make fudge.

Hence, The cost to make 19 pounds of fudge is,

⇒ 19 × $4.25

⇒ $80.75

Thus, The cost to make 19 pounds of fudge is, $80.75

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Answer:

$2.25 + 4% = $2.34

It increased by 9 cents

Step-by-step explanation:

Answer:

8

Step-by-step explanation:

Substitute x = 1 and y = 3 into the expression

(y - x)³

= (3 - 1)³

= 2³

= 8

5 - 17

x is adding multiples of 3 to get y

example: 2+3=5, 3+6=9 4+9=13, 5+12=17 and so on.

So, there are (n!)^2 ways to arrange n men and n women in a row if they alternate genders.

We need to use the principle of multiplication. We first choose the position of the first person in the row, which can be any of the n men or n women. Without loss of generality, let's say we choose a man. Then, for the next position, we need to choose a woman since we are alternating genders. There are n women to choose from. For the third position, we need to choose another man, and there are n-1 men left to choose from (since we already used one). For the fourth position, we need to choose another woman, and there are n-1 women left to choose from. We continue this pattern until all n men and n women are placed in the row.

Using the principle of multiplication, we can find the total number of ways to arrange the people by multiplying the number of choices at each step. Therefore, the total number of ways to arrange the people in a row if the men and women alternate is:

n * n-1 * n * n-1 * ... * 2 * 1

This can be simplified to:

(n!)^2

So, there are (n!)^2 ways to arrange n men and n women in a row if they alternate genders.

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Answer:

(f - g)(x) = 9x + 1

Step-by-step explanation:

Step 1: Write out functions

f(x) = 3x + 10x = 13x

g(x) = 4x - 1

Step 2: Find (f - g)(x)

(f - g)(x) = 13x - (4x - 1)

(f - g)(x) = 13x - 4x + 1

(f - g)(x) = 9x + 1

Answer:

how many dose she have

Step-by-step explanation:

Answer: 18 strawberries

Maria puts 6 strawberries in each smoothie she makes. She makes 3 smoothies altogether how many strawberries does Maria use in the smoothies? (i’m guessing is the real question)

Well she needs to put 6 strawberries in EACH of the 3 smoothies. The easiest way to find the answer is to multiply! 6 • 3 = 18! So, I hope this helps!

The function (fof)(x) can be expressed as (fof)(x) = 2 for 0 < x < 1. Using mathematical induction, it can be shown that for any positive integer n, the function F₁(x) = \(2^n\)(2 - 1) holds true for 0 ≤ x ≤ 1.

a. To find the expression for (fof)(x), we need to compute the composition of the function f with itself. Since f(x) = 2 for 0 < x < 1, applying f twice results in f(f(x)) = f(2) = 2 for 0 < x < 1. Therefore, the expression for (fof)(x) is (fof)(x) = 2 for 0 < x < 1.

b. To prove the given statement using mathematical induction, we need to establish a base case and an inductive step.

Base Case: For n = 1, the function F₁(x) =\(2^1\)(2 - 1) = 2 holds true for 0 ≤ x ≤ 1.

Inductive Step: Assume that for some positive integer k, the function Fₖ(x) = \(2^k\)(2 - 1) holds true for 0 ≤ x ≤ 1. We need to prove that Fₖ₊₁(x) = \(2^{k+1}\)(2 - 1) also holds true.

Starting with Fₖ₊₁(x), we have Fₖ₊₁(x) = Fₖ(F₁(x)) = \(2^k\)(2 - 1)(2 - 1) = \(2^{k+1}\)(2 - 1). This shows that if the statement holds for Fₖ(x), it also holds for Fₖ₊₁(x).

Therefore, by mathematical induction, we can conclude that for any positive integer n, the function F₁(x) = \(2^n\)(2 - 1) holds true for 0 ≤ x ≤ 1.

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The effect of eliminating a redundant constraint from a linear programming model depends on the specifics of the model and the constraint in question. It is important to analyze the model carefully to determine the effect that eliminating a constraint would have on the optimal solution.

No effect: If the constraint was indeed redundant, meaning that it did not affect the optimal solution, then eliminating it would have no effect on the optimal solution.

Improved solution: If the constraint was affecting the optimal solution, then eliminating it might result in a better solution. For example, if the constraint was limiting the feasible region of the solution, then eliminating it might expand the feasible region and result in a better solution.

Different solution: If the constraint was affecting the optimal solution, then eliminating it might result in a different solution. For example, if the constraint was forcing the optimal solution to go through a particular point, then eliminating it might result in a different solution.

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Answer:

Skewed Left

Step-by-step explanation:

Answer:

Step-by-step explanation:

\(Slope =\dfrac{y_{2}-y_{1}}{x_{2}-x_{1}}\\\\=\dfrac{-1-1}{-6-[-10]}=\dfrac{-2}{-6+10}\\\\\\=\dfrac{-2}{4}\\\\\\=\dfrac{-1}{2}\)

The value of x that makes 25x^2 + 70x + c a perfect square trinomial is c = 1225.

To make the quadratic expression 25x^2 + 70x + c a perfect square trinomial, we need to determine the value of c.

A perfect square trinomial can be written in the form (ax + b)^2, where a is the coefficient of the x^2 term and b is half the coefficient of the x term.

In this case, a = 25, so b = (1/2)(70) = 35.

Expanding (ax + b)^2, we have:

(25x + 35)^2 = 25x^2 + 2(25)(35)x + 35^2

= 25x^2 + 70x + 1225.

Comparing this with the given quadratic expression 25x^2 + 70x + c, we can see that c = 1225.

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Answer:

D

Step-by-step explanation:

Answer:

(A) The unshaded octagon is a reflection because it is a flip over a diagonal line.

Step-by-step explanation: Trust, rust, and pixie dust

Answer:

A is correct

The unshaded octagon is a reflection because it is a flip over a diagonal line.

i took the test

a) The velocity at time t can be calculated using function v(t) = t² + 3t - 4.

b) The distance traveled during the time interval [0, 3] is approximately 30.5 meters.

To find the velocity function v(t), we need to integrate the acceleration function a(t) with respect to time:

a(t) = 2t + 3

∫a(t) dt = ∫(2t + 3) dt

v(t) = ∫(2t + 3) dt = t² + 3t + C

We need to find the constant C using the initial velocity v(0) = -4:

v(0) = 0² + 3(0) + C = C = -4

So the velocity function is:

v(t) = t² + 3t - 4

To find the distance traveled during the time interval [0, 3], we need to integrate the absolute value of the velocity function:

d(t) = ∫|v(t)| dt = ∫|t² + 3t - 4| dt

The velocity changes sign at t = -4 and t = 1, so we need to break the integral into three parts:

d(t) = ∫(-t² - 3t + 4) dt for 0 ≤ t ≤ 1

+ ∫(t² + 3t - 4) dt for 1 ≤ t ≤ 3

+ ∫(-t² - 3t + 4) dt for -4 ≤ t ≤ 0

Evaluating each integral, we get:

d(t) = [-1/3t³ - 3/2t² + 4t] for 0 ≤ t ≤ 1

+ [1/3t³ + 3/2t² - 4t + 11] for 1 ≤ t ≤ 3

+ [1/3t³ + 3/2t² + 4t] for -4 ≤ t ≤ 0

Now we can calculate the distance traveled by subtracting the distance traveled in the negative time interval from the distance traveled in the positive time interval:

d(3) - d(0) = [1/33³ + 3/23² - 43 + 11] - [-1/30³ - 3/20² + 40]

= 30.5

So the distance traveled during the time interval [0, 3] is approximately 30.5 meters.

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Answer:

i hope this helps

Step-by-step explanation:

Answer:

15%

Step-by-step explanation:

1335-1200=135

9 months=9/12

135=1200 x r x 9/12

135=900r

divide each by 900

135/900       900r/900

0.15=r

0.15=15%

answer: the answer is 18!!

Answer:

18

Step-by-step explanation:

rearrange the equation by subtracting what is to the right of the equal sign from both sides of the equation.

Answer:

X=58

Step-by-step explanation:

Good luck .

Hope this helps u ;)

Standardizing 10 and 12 gives us Z = (10 - 11) / 1.50 = -0.6667 and Z = (12 - 11) / 1.50 = 0.6667, respectively. Using the standard normal curve table or SALT, we find P(-0.6667 ≤ Z ≤ 0.6667) = 0.4972. Therefore, P(|X - 11| ≤ 1) = 0.4972.

(a) P(X ≤ 11) 0.5000The given normal distribution has a mean value of μ=11 kips and a standard deviation of σ=1.50 kips. To standardize X, we use the formula

Z = (X - μ) / σ = (X - 11) / 1.50.(a) P(X ≤ 11)

represents the probability that X is less than or equal to 11. The Z-score corresponding to

X = 11 is Z = (11 - 11) / 1.50 = 0.

Hence,

P(X ≤ 11) = P(Z ≤ 0) = 0.5000. (b) P(X ≤ 12.5) 0.8413(b) P(X ≤ 12.5)

represents the probability that X is less than or equal to 12.5. The Z-score corresponding to

X = 12.5 is Z = (12.5 - 11) / 1.50 = 0.8333

Using the standard normal curve table or SALT, we find

P(Z ≤ 0.8333) = 0.7977.

Therefore

, P(X ≤ 12.5) = 0.7977. (c) P(X ≥ 3.5) 1(c) P(X ≥ 3.5)

represents the probability that X is greater than or equal to 3.5. Any value less than 3.5 would be many standard deviations away from the mean. Therefore,

P(X ≥ 3.5) = 1, or 100%. (d) P(9 ≤ x ≤ 14) 0.8855(d) P(9 ≤ X ≤ 14)

represents the probability that X is between 9 and 14 (inclusive). To standardize 9 and 14, we use the formula

Z = (X - μ) / σ.

The Z-score corresponding to

X = 9 is Z = (9 - 11) / 1.50 = -1.3333.

The Z-score corresponding to

X = 14 is Z = (14 - 11) / 1.50 = 2.

This gives us P(-1.3333 ≤ Z ≤ 2) = 0.8855 using the standard normal curve table or SALT.

(e) P(|X-11| ≤ 1) 0.4972(e) P(|X - 11| ≤ 1)

represents the probability that X is within 1 kip of the mean value 11 kips. We can write this as P(10 ≤ X ≤ 12). Standardizing 10 and 12 gives us

Z = (10 - 11) / 1.50 = -0.6667 and Z = (12 - 11) / 1.50 = 0.6667

, respectively. Using the standard normal curve table or SALT, we find

P(-0.6667 ≤ Z ≤ 0.6667) = 0.4972.

Therefore,

P(|X - 11| ≤ 1) = 0.4972.

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