I would really appreciate it if y’all would help me on this question asap please and thank you

Answer:

Step-by-step explanation:

Substitute the values of a and b

Answer:

Step-by-step explanation:

| 2 - 4a | - 2(b - 7)

let a = 3, b = -5

substitute a = 3, b = -5 into the equation:

| 2 - 4a | - 2(b - 7)

= | 2 - 4(3) | - 2(-5 - 7)

= | 2 - 12 | - 2(-12)

= | -10 | + 24

= 10 + 24

= 34

The answer fam is.... They are equivalent

19/3

19/3 ..since 3 isnt a factor of 19..it cant be split further

Answer:

Step-by-step explanation:

Solve 20x + 5y =  for y

20x + 5y = 0

subtract 20x both sides

5y = -20x

simplify:

y = -20x

        5

finally

y = -4x

Answer:

-23/4 =c

Step-by-step explanation:

21+30=-4c+28​

Combine like terms

51 = -4c+28

Subtract 28 from each side

51 = -4c+28

Subtract 28 from each side

51-28 = -4c+28-28

23 = -4c

Divide each side by -4

23/-4 = -4c/-4

-23/4 =c

Answer: [tex]-\frac{23}{4}[/tex] or 5.75

Step-by-step explanation:

Step 1. Simplify 21 + 30 to 51

51 = −4c + 28

Step 2. Subtract 28 from both sides

51 - 28 = -4c

Step 3. Simplify 51 - 28 to 23

23 = -4c

Step 4. Divide both sides by -4

[tex]-\frac{23}{4}[/tex] = c

Step 5. Switch sides

c = [tex]-\frac{23}{4}[/tex]

Decimal Form Answer: -5.75

I hope this helps you out.

Answer: 3 units to the left of three because the answer would be -3

Step-by-step-explanation: If we subtract 6 from 3, we get -3. Pretend these are dolars. So we have 3

How many dolars do you have left?

Well, we pay them the three we have, but then we owe them $3, because they still need $6 total.

We owe them 3 dolars, or we have -3 dollars.

Now let's just put a dot where -3 is on a number line.

Another way to look at this would be we started with 3 (blue dot) and we subtract 6, or move 6 to the left to get our red dot...which is -3

Either way you do it, -3 (which is the red dot) is your answer.

Answer:

3 units to the left of 3

Step-by-step explanation:

Answer:

Well, I can't see the graph but the y-intercept is the point on the line to where if you are on 0 either go up or down and the point the line is on is the y-intercept.

Answer:

.75

Step-by-step explanation:

trust meeeeee

Complete question :

Physics students drop a ball from the top of a 100 foot high building and model its height as a function time with the equation h(t) = 100 - 16t^2.The height, h, is measured in feet and time, t, is measured is seconds.

Find the value of h(0). Include proper units. What does this output represent?

Answer:

Kindly check explanation

Step-by-step explanation:

The model given :

Height, h as a function of time :

h(t) = 100 - 16t^2

To find h(0): substitute 0 for t in the model defined ;

h(0) = 100 - 16(0)²

h(0) = 100 - 0

h(0) = 100

The output gives the height at which the ball was before it was dropped, it depicts the height when the travel time of the ball is 0

a) Based on the given data, we can conjecture that the set of dogs will have a larger mean, median, and standard deviation compared to the set of cats. This is because the weights of the dogs are generally higher and more spread out than the weights of the cats.

Dogs and cats typically have different average weights, with dogs being larger and heavier on average compared to cats. From the given data, the weights of the dogs range from 13 to 102 pounds, while the weights of the cats range from 4 to 22 pounds.

Considering the mean, the larger weights of the dogs will contribute to a higher mean compared to the weights of the cats. Since the mean is influenced by extreme values, the presence of larger dogs with weights such as 76 and 102 will tend to increase the mean for the dog set.

Moving on to the median, which represents the middle value of a dataset, the dogs are likely to have a larger median because their weights are generally higher. The median is less affected by extreme values, so even though there are a few heavier dogs, they won't significantly impact the overall position of the median for the dog set.

Lastly, the standard deviation measures the dispersion or spread of the data. Since the weights of the dogs exhibit a wider range, including both lighter and heavier dogs, the dog set is expected to have a larger standard deviation compared to the cat set, where the weights are more concentrated within a smaller range.

In summary, based on the general characteristics of dogs and cats, we can conjecture that the set of dogs will have a larger mean, median, and standard deviation compared to the set of cats, given the provided weights.

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Answer:

Step-by-step explanation:

g(-2)=8(-2)-2

g(-2)=-16-2

g(-2)=-18

g(4)=8(4)-2

g(4)=32-2

g(4)=30

g(-2)<g(4)

The value of g(-2) is smaller than the value of g(4).

Answer:

56% ≤ p ≤ 70%

Step-by-step explanation:

Given the following :

Predicted % of votes to win for candidate A= 63%

Margin of Error in prediction = ±7%

Which inequality represents the predicted possible percent of votes, x, for candidate A?

Let the interval = p

Hence,

|p - prediction| = margin of error

|p - 63%| = ±7%

Hence,

Upper boundary : p = +7% + 63% = 70%

Lower boundary : p = - 7% + 63% = 56%

Hence,

Lower boundary ≤ p ≤ upper boundary

56% ≤ p ≤ 70%

Answer:

Heyhey!!! How ya doing?

Step-by-step explanation:

I can feel it on my skin

It's coming down on me

teardrops on my face

Water like misery

Let it wash away my sins

It's coming down on me

Answer:

I) the value of X is 60

60=1×_

2×30

3×20

4×15

5×12

6×12

6×10 = 60

ii) 2 and 3 you also can put 5

Hope this helps

The Probability of pulling a white marble from the bag is 2/5.

To find the probability of selecting a white marble from the bag, we need to determine the number of favorable outcomes (white marbles) and the total number of possible outcomes (all marbles).

The bag contains a total of 20 marbles, of which 8 are white. Therefore, the number of favorable outcomes is 8 (white marbles).

The total number of possible outcomes is the sum of all marbles in the bag, which is 20.

The probability of selecting a white marble can be calculated as:

Probability (White Marble) = Number of Favorable Outcomes / Total Number of Possible Outcomes

Probability (White Marble) = 8 / 2

To simplify the fraction, we can divide both the numerator and denominator by their greatest common divisor, which is 4:

Probability (White Marble) = 2 / 5

Therefore, the probability of selecting a white marble from the bag is 2/5.

In conclusion, the probability of pulling a white marble from the bag is 2/5.

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Answer:

try D

Step-by-step explanation:

it's the closest I could get on Desmos

Answer:

D.

Step-by-step explanation:

Step-by-step explanation:

number of boys=25

number of girls =16

ratio of boys to girl is 25:16

and the fraction is =25/16

Answer:

B

Step-by-step explanation:

The equation of a line in point- slope form is

y - b = m(x - a)

where m is the slope and (a, b) a point on the line

f'(3) = - 4 ← is the slope of the line at x = 3

and f(3) = 2 is the point (3, 2 ) thus

y - 2 = - 4(x - 3) ← add 2 to both sides

y = - 4(x - 3) + 2 → B

Answer: (y-4) = -2(x-3)

Step-by-step explanation:

(y-y1) = m(x-x1)

y1 = 4

x1 = 3

m = -2

The sample size required is 29.

To find the sample size, we need to use the concept of Acceptable Quality Level (AQL) and Lot Tolerance Percent Defective (LTPD) along with the consumer's risk and producer's risk.

The AQL is the maximum percentage of defective items that the company is willing to accept from the LSI manufacture department, which is specified as 6%. On the other hand, the LTPD is the maximum percentage of defective items that the assembly department is willing to accept, which is specified as 39%.

To calculate the sample size, we can use the formula for the sample size in attribute sampling plans:

n = ([tex]Z^{2}[/tex] * p * q) / [tex]E^{2}[/tex]

Where:

n = sample size

Z = Z-value corresponding to the desired level of confidence (for consumer's risk of 10% and producer's risk of 5%, we can use Z = 1.65)

p = expected proportion of defective items (maximum between AQL and LTPD)

q = 1 - p

E = precision or tolerable error (difference between AQL and LTPD)

In this case, we want to determine the sample size, assuming the worst-case scenario. Therefore, we choose p as the maximum between AQL and LTPD, which is 39%. Hence, q is 1 - p, which is 61%. The precision or tolerable error (E) is the difference between AQL and LTPD, which is 39% - 6% = 33%.

Substituting these values into the formula, we have:

n = ([tex]1.65^{2}[/tex] * 0.39 * 0.61) / ([tex]0.33^{2}[/tex])

n ≈ 28.74

Since the sample size should be a whole number, we round up to the nearest whole number.

Therefore, the sample size required is approximately 29.

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Answer:

[tex]\boxed {x = \frac{10}{c}}[/tex]

Step-by-step explanation:

Solve for the value of [tex]x[/tex]:

[tex]3(cx - 7) = 9[/tex]

-Divide [tex]9[/tex] by [tex]3[/tex]:

[tex]cx - 7 = \frac{9}{3}[/tex]

[tex]cx - 7 = 3[/tex]

-Add [tex]7[/tex] to both sides:

[tex]cx - 7 + 7 = 3 + 7[/tex]

[tex]cx = 10[/tex]

-Take [tex]c[/tex] and divide it on both sides:

[tex]\frac{cx}{c} = \frac{10}{c}[/tex]

[tex]\boxed {x = \frac{10}{c}}[/tex]

Therefore, the value of [tex]x[/tex] is [tex]\frac{10}{c}[/tex].

Answer:

That would be nice.

Step-by-step explanation:

If you could :)

The percentage increase in volume required to offset a 10% price reduction when the firm's contribution margin is 30% can be calculated using the following formula:Percentage increase in volume = (Price reduction percentage ÷ Contribution margin percentage) × 100= (10 ÷ 30) × 100= 33.33%

Therefore, there needs to be a 33.33% increase in volume to offset a 10% price reduction when the firm's contribution margin is 30%. A company's contribution margin indicates the portion of each sales dollar that goes towards the company's fixed expenses and profits. To know whether or not a firm will be able to withstand a price reduction, the contribution margin percentage must be considered. The calculation of the percentage increase in volume required to offset a 10% price reduction is done by dividing the price reduction percentage by the contribution margin percentage, and then multiplying by 100. In this particular scenario, a 33.33% increase in volume would be needed to offset a 10% price reduction when the company's contribution margin is 30%.The breakeven level is the level at which the total costs of a company are equal to its total sales. To calculate the percentage contribution margin required to offset a 10% increase in price associated with a 14.3% decrease in volume (the breakeven level), the following formula can be used:Contribution margin percentage = (Price increase percentage ÷ Volume decrease percentage) × 100= (10 ÷ 14.3) × 100= 70.0%Thus, a 70.0% contribution margin percentage would be needed to offset a 10% increase in price associated with a 14.3% decrease in volume (the breakeven level).To offset a 12.5% price reduction in a 60% contribution margin situation, the elasticity can be calculated using the following formula:Elasticity = (Price change percentage ÷ Quantity change percentage) × (1 ÷ Contribution margin percentage)= (12.5 ÷ 12.5) × (1 ÷ 60)= 0.0167Thus, an elasticity of 0.0167 would be needed to offset a 12.5% price reduction in a 60% contribution margin situation.

The percentage increase in volume required to offset a 10% price reduction when the firm's contribution margin is 30% is 33.33%. A 70.0% contribution margin percentage would be needed to offset a 10% increase in price associated with a 14.3% decrease in volume (the breakeven level). An elasticity of 0.0167 would be needed to offset a 12.5% price reduction in a 60% contribution margin situation.

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Answer:

C. 5x10^-10

Step-by-step explanation:

That equations answer is 5e-7, or 0.00000005, and C is equal to 0.000000005.

The random variable is the number of brown MOM's in a package of 50 MOM's. The given numbers are n = 50 and p = 0.13. The probabilities of exactly none, exactly 44, at least 43, and at most 45 MOM's being brown can be calculated using the binomial probability formula.

a) The random variable in this scenario is the number of brown MOM's in a package of 50 MOM's.

b) The given numbers with correct symbols are:

n = 50 (number of MOM's in the package)

p = 0.13 (proportion of brown MEM's)

c) This is a binomial experiment because the following conditions are met:

- There are only two outcomes for each MOM: brown or not brown.

- The number of MOM's is fixed at 50.

- The probability of selecting a brown MOM remains constant at 13% for each randomly selected MOM.

- The selection of one MOM being brown does not affect the probability of another MOM being brown.

d) The probability that exactly none of the MOM's are brown can be calculated using the binomial probability formula as P(X = 0) = C(50, 0) * (0.13)^0 * (1 - 0.13)^(50 - 0).

e) The probability that exactly 44 MOM's are brown can be calculated using the binomial probability formula as P(X = 44) = C(50, 44) * (0.13)^44 * (1 - 0.13)^(50 - 44).

f) The probability that at least 43 MOM's are brown can be calculated by summing the individual probabilities of having 43, 44, 45, ..., 50 MOM's brown. This can be calculated as P(X ≥ 43) = P(X = 43) + P(X = 44) + ... + P(X = 50).

g) The probability that at most 45 MOM's are brown can be calculated by summing the individual probabilities of having 0, 1, 2, ..., 45 MOM's brown. This can be calculated as P(X ≤ 45) = P(X = 0) + P(X = 1) + ... + P(X = 45).

By substituting the appropriate values into the binomial probability formula and performing the calculations, we can find the probabilities (d), (e), (f), and (g) to 4 decimal places.

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To determine the number of solutions of the given equation, let's simplify it first:

(x^2 + 1)^2 + 2(x^2 + 1) - 3 = 0

Let's substitute a new variable, let's say u = x^2 + 1, to simplify the equation further:

u^2 + 2u - 3 = 0

Now, we have a quadratic equation in terms of u. To find the solutions for u, we can factorize the equation:

(u + 3)(u - 1) = 0

This equation will be true if either (u + 3) equals zero or (u - 1) equals zero.

For (u + 3) = 0, we have u = -3.

For (u - 1) = 0, we have u = 1.

Now, let's substitute back u = x^2 + 1:

For u = -3:

x^2 + 1 = -3

x^2 = -4

This equation has no real solutions because the square of any real number cannot be negative.

For u = 1:

x^2 + 1 = 1

x^2 = 0

This equation has a single solution: x = 0.

Therefore, the given equation has only one solution, x = 0.

The correct answer is A. 1.

[tex]\huge{\mathfrak{\colorbox{black}{\textcolor{lime}{I\:hope\:this\:helps\:!\:\:}}}}[/tex]

♥️ [tex]\large{\textcolor{red}{\underline{\mathcal{SUMIT\:\:ROY\:\:(:\:\:}}}}[/tex]

Answer:

2

Step-by-step explanation:

simplify the equation to

[tex]2{x}^{2} + 2 + 2 {x}^{2} + 2 - 3 = 0[/tex]

simplify again by combining lIke terms to get

[tex]4 {x}^{2} + 1 = 0[/tex]

since x 2 can mean that x can be both a positive and negative number so there can be 2 solutions. they will both involve imaginary numbers because 4x 2 is guaranteed to be positive

To find the population density in terms of people per square mile, we need to determine the area within a 15-mile radius and divide the population by that area.

To calculate the population density, we first need to find the area within a 15-mile radius. The formula for the area of a circle is A = πr², where A is the area and r is the radius. In this case, the radius is 15 miles.

Using the formula, we can find the area within the 15-mile radius:

A = π(15)² = 225π square miles

Next, we divide the given population of 40,000 by the area to find the population density:

Population density = 40,000 / (225π) people per square mile

To simplify the calculation, we can approximate the value of π to 3.14:

Population density ≈ 40,000 / (225 * 3.14) people per square mile

Simplifying further:

Population density ≈ 40,000 / 706.5 people per square mile

Using a calculator, we can find the approximate value:

Population density ≈ 56.7 people per square mile

Therefore, the population density within a 15-mile radius is approximately 56.7 people per square mile.

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Answer:

The slope of this linear equation is -5/2x.

The formula for the variance of the MLE estimator of β₀ is:

Var(β₀) = {σ²}{n} [ 1 + x²} / {∑{i=1}ⁿ (x_i - x²}

For the simple linear regression model, we have:

[tex]y_{i} = \beta_{0} + \beta _{1} x_{i} + epsilon_{i}[/tex]

where y(i) is the response variable, x (i) is the predictor variable, β₀ and β₁ are the intercept and slope parameters, and ∈(i) is the error term.

To find the variance of the MLE estimators of β₀ and β₁, we first need to derive the MLEs for these parameters:

β₁= {sum{i=1}ⁿ (xi - {x})(y_i - {y})}/{{i=1}ⁿ (x_i - {x})²}

β₀ = {y} -  β₁x

where x and y are the sample means of the predictor and response variables, respectively.

Next, we need to find the variances of these estimators. The formula for the variance of the MLE estimator of β₁ is:

$Var( β₁) = σ²∑{i=1}ⁿ (x_i - x²)

where , σ² is the variance of the error term.

And, the formula for the variance of the MLE estimator of β₀ is:

Var(β₀) = {σ²}{n} [ 1 + x²} / {∑{i=1}ⁿ (x_i - x²}

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