if it were reported instead that the percentage of 1,500 voters in the poll that were in favor of stiffer gun control guidelines was 60.8%, then this would be an example of what type of statistics?

Testing is only one part of the overall assessment process.

What is evaluation in education?

Assessment is an ongoing process of gathering evidence of what each student actually knows, understands, and can do. A comprehensive evaluation approach includes a combination of formal and informal evaluation (formative, preliminary, and summative).

What is an assessment? Also what does it mean?

At the course level, assessments provide important data on the breadth and depth of student learning. Evaluation is more than scoring. It's about measuring student learning progress. Assessment is therefore defined as “the process of data gathering to better understand the strengths and weaknesses of a student's learning”. 

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Based on the information provided, Mateo has drawn a line to represent the parallel cross-section of the triangular prism. Is he correct? Yes, he is correct. Here's an explanation:

A triangular prism has two triangular bases and three rectangular faces. When a triangular prism is lying on a rectangular face, it means that one of its rectangular faces is on the bottom. If Mateo draws a line along the length of this rectangular face, he is creating a parallel cross-section of the triangular prism.

This is because the line he drew is parallel to the triangular base of the prism, and the two bases are also parallel to each other. A parallel cross-section is created when a plane cuts through a solid parallel to its base, and in this case, Mateo's line fulfills this condition.

Therefore, Mateo is correct in representing the parallel cross-section of the triangular prism by drawing a line along the length of a rectangular face.

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Answer:

Image

Step-by-step explanation:

a) The parameter of interest is the proportion of people 65 years or older in the United States.

b) The assumptions include the sample is random, the sample size is large and observations are independent.

c) The 90% confidence interval lie in (0.198, 0.51).

d) We are 90% confident that the true proportion of people 65 years or older lies between 0.198 and 0.51.

a) The parameter of interest is the proportion of people 65 years or older in the United States who have an active Netflix subscription.

b) The assumptions needed for constructing the appropriate confidence interval for the proportion include: 1) the sample is random, 2) the sample size is sufficiently large (at least 10 times the number of successes and failures), and 3) the observations are independent.

To check these assumptions, we need to verify that the sample is indeed random, and that the sample size is large enough. Since the sample size is 65 and the number of successes (i.e., those with an active Netflix subscription) is 23, we can assume that the sample size is sufficiently large.

Additionally, we assume that each person in the sample has an independent probability of having an active Netflix subscription.

c) To find a 90% confidence interval for the proportion of people 65 years or older in the United States with an active Netflix subscription, we can use the normal approximation to the binomial distribution. The formula for the confidence interval is:

p' ± z*(√(p'(1-p'))/n)

where p' is the sample proportion (23/65), z* is the critical value from the standard normal distribution corresponding to a 90% confidence level (1.645), and n is the sample size (65).

Plugging in the values, we get:

0.354 ± 1.645*(√(0.354*(1-0.354))/65)

This simplifies to:

(0.198, 0.51)

d) We are 90% confident that the true proportion of people 65 years or older in the United States with an active Netflix subscription lies between 0.198 and 0.51. This means that if we were to repeat this study many times and construct a 90% confidence interval for each study, we would expect that 90% of these intervals would contain the true proportion.

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Answer: 2

Step-by-step explanation: Mode is the most frequent number

The probability of a randomly selected person who owns a home also being a high school graduate is approximately 0.442 or 44.2%.

Based on the information provided, we know that there are:

Therefore, the probability of a randomly selected person who owns a home also being a high school graduate is:

P(G|H) = P(G and H) / Total number = 221/500 ≈ 0.442

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After performing long division on (x3+3x2-x+2)/(x-1) we get x² + 4x +3 leaving a remainder of 5.

Long division refers to the method of performing a division of two numbers or polynomials by hand. Furthermore, it involves several steps to evaluate in order to find a quotient and a remainder. It is considered an important and crucial form of practice in the branch of mathematics.                  

In the subject of dividing a polynomial, first, we divide the highest degree term of the dividend by the highest degree term of the divisor, and the remaining result is subtracted from the dividend. The calculation is as follows in the picture

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Answer:

1. 71°

Step-by-step explanation:

SohCahToa

use sin

sin^-1(51/54)

=70.81186355

=71°

The combined fraction in the context of this problem is given as follows:

(4x² + 12x - 9)/(x² + 8x + 15).

The fractional expression in the context of this problem is given as follows:

(x + 6)/(x² + 8x + 15) + 3x/(x + 5) - (x - 3)/(x + 3).

(x + 5)(x + 3) = x² + 8x + 15, hence the denominator of the simplified expression is given as follows:

x² + 8x + 15.

Applying the least common factor, the numerator of the simplified expression is given as follows:

x + 6 + 3x(x + 3) + (x - 3)(x + 5) = x + 6 + 3x² + 9x + x² - 3x + 5x - 15

x + 6 + 3x(x + 3) + (x - 3)(x + 5) = 4x² + 12x - 9

Hence the combined expression is given as follows:

(4x² + 12x - 9)/(x² + 8x + 15).

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a. The bagel needs to be dilated by a scale factor of 5 to serve 25 people.
b. 25 times more cream cheese will be required for the dilated bagel compared to the original bagel.

a. To find the scale factor for the large bagel that serves 25 people, we need to find the square root of the ratio of the number of people the large bagel serves to the number of people the small bagel serves.
Scale factor = [tex]\sqrt{(large_bagel_serving / small_bagel_serving)}[/tex]
Scale factor = [tex]\sqrt{(25 / 1)}[/tex]
Scale factor =[tex]\sqrt{ 25}[/tex]
Scale factor = 5
So, the bagel needs to be dilated by a scale factor of 5 to serve 25 people.
b. Since the bagels are in the same shape, the area of the large bagel will be the square of the scale factor times the area of the small bagel.

The cream cheese is spread over the area, so the ratio of the cream cheese needed for the large bagel to the small bagel will be the same as the ratio of their areas.
Ratio of cream cheese = [tex](scale factor)^2[/tex]
Ratio of cream cheese = [tex](5)^2[/tex]
Ratio of cream cheese = 25
So, 25 times more cream cheese will be required for the dilated bagel compared to the original bagel.

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The dilated bagel requires 25 times more cream cheese than the original single serving bagel. Round your answer to the nearest tenth: 25.0 times more cream cheese.

a) To determine the scale factor for the dilated bagel, first, we need to find the ratio between the area of the large bagel and the area of a single serving bagel. Since the large bagel serves 25 people, the area ratio will be 25:1.

Area ratio = (scale factor)^2
25:1 = (scale factor)^2

To find the scale factor, take the square root of the area ratio:
scale factor = √25 = √(25/1) = 5

Therefore, the bagel will need to be dilated by a scale factor of 5 to serve 25 people.

b) Since the thickness of the cream cheese remains the same on both bagels, we only need to consider the difference in area between the two bagels. As calculated before, the area ratio is 25:1.

Thus, the dilated bagel requires 25 times more cream cheese than the original single serving bagel. Round your answer to the nearest tenth: 25.0 times more cream cheese.

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Jamal ought to utilize a histogram to display the information regarding the amount of steps he takes each day.

The complete set of people or things that we are interested in investigating is referred to as a population in statistics. We want to examine and draw conclusions from the entire set of facts. For instance, all adult women in a country would represent the population if we were interested in measuring the average height of adult women there.

In contrast, a sample is a smaller portion of the population that is chosen for analysis. When measuring the entire population is neither practicable or practical, this method is utilised.

Jamal ought to utilise a histogram to display the information regarding the amount of steps he takes each day. A histogram is a form of graph that shows how continuous data, such the number of steps, are distributed. It divides the data into intervals or "bins" and displays how frequently data points fall into each bin. Jamal may detect the usual or central trend of his daily step count as well as any fluctuation or outliers in the data by examining the shape of the histogram.

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Based on this analysis, it's clear that the peak wind gusts are generally higher in January than in April at these weather stations in Rocky Mountain National Park.

Yes, based on the provided information, the peak wind gusts in Rocky Mountain National Park are higher in January than in April.
Compare peak wind gusts for each weather station in January and April:
  - Weather Station 1: January - 139 mph, April - 104 mph
  - Weather Station 2: January - 122 mph, April - 113 mph
  - Weather Station 3: January - 126 mph, April - 100 mph
  - Weather Station 4: January - 64 mph, April - 88 mph
  - Weather Station 5: January - 78 mph, April - 61 mph
Count the number of weather stations with higher peak wind gusts in January and April:
  - Higher in January: 4 weather stations (1, 2, 3, and 5)
  - Higher in April: 1 weather station (4)
Determine the overall trend:
  - The peak wind gusts are higher in January at 4 out of 5 weather stations in Rocky Mountain National Park.

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Here's a comparison of the peak wind gusts at each weather station: Weather Station: 1 2 3 4 5 January: 139 122 126 64 78 April: 104 113 100 88 61 At all five weather stations, the peak wind gusts in January are higher than those in April.

Based on the information provided from winter wind studies in Rocky Mountain National Park by D.E. Glidden, it appears that the peak wind gusts are higher in January than in April.

The data shows that at all five weather stations on Trail Ridge Road, the peak wind gusts in January are higher than in April. To determine if this difference is statistically significant, a significance level of 0.01 can be used. Further statistical analysis would be needed to determine the significance of this difference.

Here's a comparison of the peak wind gusts at each weather station: Weather Station: 1 2 3 4 5 January: 139 122 126 64 78 April: 104 113 100 88 61 At all five weather stations, the peak wind gusts in January are higher than those in April.

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a.  the area of triangle ACD is 10

b. the area of triangle ABC is 12√(3)

part a.

Let E be the intersection of AB and CD.

AE/EB = AC/CB = 17/10

Applying  the angle bisector theorem, :

AD/DB = AC/CB = 17/10

AE/EB = AD/DB

Multiplying both sides by EB :

AE = AD*(EB/DB)

we know that  AE + EB = 9,

AE = AD*(9-AD)/(DB-AD)

applying the angle bisector theorem for angle B, we can find:

BF = BD*(10-BD)/(AD-BD

DG = (AD+BD-AB)/2

CG = (AC+BC-BC)/2 = 17/2

Using the Pythagorean theorem for triangles DGC and DFC,we have :

DG^2 + CG^2 = CD^2

DF^2 + CF^2 = CD^2

AD^2*(9-AD)^2/(AD-BD)^2 + BD^2*(10-BD)^2/(BD-AD)^2 = CD^2

CD = 4

s = (AD+CD+AC)/2 = 21/2

A = √(s(s-AD)(s-CD)(s-AC))

= s√t(2152*1) = 10

b.  we  use Heron's formula in order to To find the area of triangle ABC,

s = (AB+BC+AC)/2 = 18

A = √t(s(s-AB)(s-BC)(s-AC))

= √(1898*1) = 12√(3)

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The P-value for this test is the probability of observing a z-score as extreme or more extreme than 22.75, assuming the null hypothesis is true.

To conduct this hypothesis test, we can use the normal distribution as an approximation to the binomial distribution. Since the sample size is large (963 babies), we can assume that the sampling distribution of the sample proportion of girls is approximately normal. The sample proportion of girls is 873/963=0.906, which is the point estimate of the population proportion of girls born to parents using the new method.

To calculate the test statistic, we need to determine the standard error of the sample proportion.

Where p is the hypothesized population proportion (0.5 for boys and 0.5 for girls), and n is the sample size (963).

Using this formula, we get SEp=√[(0. 5x (1-0.5))/963]=0.016.

The z-score can be calculated as:

z=(p-p)/SEp

where p is the sample proportion and p is the hypothesized population proportion (0.5).

Using the values from the sample, we get z=(0.906-0.5)/0.016=22.75.

This can be calculated using a standard normal distribution table or a statistical software such as Statcrunch. The P-value turns out to be very small, much less than the chosen significance level of 0.01.

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In a particular vacation town, the average cost of a hotel room for a family of four is more than $170 at a=0.01.

The term "average cost" refers to the production cost per unit, which is determined by dividing the overall production cost by the overall number of units produced. In other words, it calculates the cost for each unit of output that the company must incur.

The null hypothesis states that a family of four can only pay a maximum of $170 for a hotel room in a certain vacation town. The alternative premise is that a particular resort town's average hotel room cost for a family of four is higher than $1701.

There are 33 participants in the sample, and the mean value is $179 with a $192 standard deviation.

This hypothesis test's test statistic is computed as follows:

t =√(sample size) / (sample standard deviation / hypothesized mean) / (sample mean - hypothesized mean)

t = (179 - 170) / (19 /√(33)) = 3.02

This test's p-value, which is less than the significance level of 0.012, is 0.0026.. We conclude that there is enough evidence to show that the average hotel room price for a family of four in a particular resort town is more than $1701 and reject the null hypothesis as a result.

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The surface area of the actual ramp, including the underside, is approximately 15.38 yd².

What is triangle?

A triangle is a three-sided polygon with three angles. It is a fundamental geometric shape and is often used in geometry and trigonometry.

To find the surface area of the actual ramp, we need to first find the dimensions of the ramp.

We are given that the scale model of the ramp is a right triangular prism with legs of 8 in, 5 in, and 5 in, and a height of 3 in. We can use these dimensions to find the dimensions of the actual ramp.

Since the ramp is a scale model, the ratio of the dimensions of the model to the actual ramp is the same for all corresponding dimensions. The height of the triangular base in the actual ramp is given as 0.6 yards, which is equal to 21.6 inches. So, we have:

height of actual ramp / height of model = 21.6 in / 3 in = 7.2

We can use this ratio to find the dimensions of the actual ramp:

height of actual ramp = 7.2 * 3 in = 21.6 in

length of actual ramp = 7.2 * 8 in = 57.6 in

width of actual ramp = 7.2 * 5 in = 36 in

Now we can find the surface area of the actual ramp. The surface area of the top and bottom of the ramp is the area of the triangular base plus the area of the rectangle formed by the length and width of the ramp:

Area of triangular base = (1/2) * base * height = (1/2) * 5 in * 5 in = 12.5 in²

Area of rectangular top and bottom = length * width = 57.6 in * 36 in = 2073.6 in²

Total surface area of top and bottom = 2 * (Area of triangular base + Area of rectangular top and bottom) = 2 * (12.5 in² + 2073.6 in²) = 4153.2 in²

The surface area of the sides of the ramp is the area of the three rectangles formed by the height and width of the ramp:

Area of one side rectangle = height * width = 21.6 in * 36 in = 777.6 in²

Total surface area of sides = 3 * Area of one side rectangle = 3 * 777.6 in² = 2332.8 in²

Finally, we add the surface area of the top and bottom to the surface area of the sides to get the total surface area of the ramp:

Total surface area of ramp = Surface area of top and bottom + Surface area of sides = 4153.2 in² + 2332.8 in² = 6486 in²

Converting to yards and rounding to two decimal places, we get:

Total surface area of ramp = 6486 in² / (36 in/yd)² = 15.38 yd² (rounded to two decimal places)

Therefore, the surface area of the actual ramp, including the underside, is approximately 15.38 yd².

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Answer:

Step-by-step explanation:

false

the probability that the sample mean would differ from the population mean by less than 2 gallons is approximately 0.9793, rounded to four decimal places.

The Central Limit Theorem,

The sample mean of a sufficiently large sample (n > 30) will be normally distributed with a mean equal to the population mean and a standard deviation equal to the population standard deviation divided by the square root of the sample size.

Here, we have a population with a mean of [tex]\mu = 103[/tex] gallons and a variance of[tex]\sigma^2 = 36 gallons^2.[/tex]

Therefore, the standard deviation of the population is [tex]\sigma = \sqrt(36) = 6[/tex]gallons.

The probability that the sample mean would differ from the population mean by less than 2 gallons.

In other words, we want to find the probability that the difference between the sample mean and the population mean is less than 2 gallons.

We can use the formula for the standard error of the mean to find the standard deviation of the sampling distribution of the sample mean:

[tex]SE = \sigma / sqrt(n)[/tex]

where n is the sample size. In this case, n = 38, so we have:

[tex]SE = 6 / \sqrt(38) = 0.979[/tex]

The difference between the sample mean and the population mean is given by:

[tex]\bar X - \mu[/tex]

The probability that this difference is less than 2 gallons. We can standardize this difference by dividing by the standard error of the mean:

[tex]Z = (\bar X - \mu) / SE[/tex]

A standard normal distribution table or calculator to find the probability that Z is less than [tex]2 / 0.979 = 2.04.[/tex]This probability is approximately 0.9793.

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The probability that the sample mean would differ from the population mean by less than 2 gallons is approximately 0.9544 or 95.44% (rounded to four decimal places).

To solve this problem, we can use the Central Limit Theorem which states that the sample mean of a large enough sample will be approximately normally distributed with a mean equal to the population mean and a standard deviation equal to the population standard deviation divided by the square root of the sample size.

Given that the mean of gas consumption per race is 103 gallons and the variance is 36, we can calculate the standard deviation as follows:

Standard deviation = [tex]\sqrt{36}[/tex] = 6 gallons

Now, we need to find the probability that the sample mean would differ from the population mean by less than 2 gallons. We can calculate the standard error of the mean as follows:

Standard error of the mean = standard deviation / sqrt(sample size) = 6 / [tex]\sqrt{38}[/tex]= 0.974

To find the probability, we can use the z-score formula:

z = (sample mean - population mean) / standard error of the mean

z = (sample mean - 103) / 0.974

Since we want to find the probability that the sample mean would differ from the population mean by less than 2 gallons, we need to find the probability that the z-score is between -2 and 2.

Using a standard normal distribution table or calculator, we can find that the probability of a z-score being between -2 and 2 is approximately 0.9544.

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The coordinate vector of p(t) relative to the basis B is:

[ -1 ]
[  2 ]
[  2 ]

To find the coordinate vector of p(t) = 1 + 4t + 7t2 relative to the basis B = {1 + t2, t + t2, 1 + 2t + t2}, we need to express p(t) as a linear combination of the basis vectors and then write down the coefficients as a column vector.

We have:

p(t) = a(1 + t2) + b(t + t2) + c(1 + 2t + t2)

Expanding this out, we get:

p(t) = (a + c) + (b + 2c)t + (a + b + c)t2

Comparing coefficients with the polynomial 1 + 4t + 7t2, we get the following system of equations:

a + c = 1
b + 2c = 4
a + b + c = 7

Solving this system, we find:

a = -1
b = 2
c = 2

Therefore, the coordinate vector of p(t) relative to the basis B is:

[ -1 ]
[  2 ]
[  2 ]

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The sample space for each experiment are as follow;

1. rolling a 12 sided fair die, the sample space is 12

2. flipping a coin, the sample space is 2

3. pulling a face card from a standard deck of cards is 12

4. A spin from the spinner, the sample space is 5

A sample space is a collection or a set of possible outcomes of a random experiment. The sample space is represented using the symbol, “S”.

For example the sample space of getting an odd number from a 6 sided fair die is 3, because the odd numbers between 1-6 are 1,3,5.

1. The sample space of rolling a 12 sided fair die is 12, because it will have 12 faces.

2. A coin has two faces, therefore the sample space of flipping a coin is 2

3. There are 12 face cards in a standard deck, therefore, the sample space to pull a face card out of a standard deck is 12.

4. The spinner has 5faces, therefore the sample space for a spin is 5.

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The estimated regression equation with TV advertising as the independent variable is ycap = 53.586 + 25.957x. The model explains 19.8% of the variation in the sample values of weekly gross revenue.

The estimated regression equation with television advertising as the independent variable is ycap = 53.586 + 25.957x. This suggests that for each additional $100 spent on television advertising, there is an estimated increase of $25,957 in weekly gross revenue.

we have already calculated the regression equation as ycap = 53.586 + 25.957x. Using this equation, we can calculate the predicted values of y for each observation in the sample of total sum of squares (SST),  sum of squares due to regression (SSR) and coefficient of determination (R-squared) as the ratio of SSR to SST

R² = SSR / SST.

To calculate the values of ycap and ybar, we first need to find the mean values of the variables

xbar = (4.9 + 4.2 + 4.5 + 3.6 + 3.5 + 5.0 + 6.8) / 7 = 4.93

ybar = (101.3 + 75.8 + 127.2 + 137.8 + 102.4 + 236.8 + 220.6) / 7 = 143.14

Using the regression equation ycap = 53.586 + 25.957x and the given data, we can calculate the predicted values of y

ycap(Mobile) = 53.586 + 25.957(1.4) = 91.08

ycap(Shreveport) = 53.586 + 25.957(1.5) = 92.04

ycap(Jackson) = 53.586 + 25.957(1.5) = 92.04

ycap(Birmingham) = 53.586 + 25.957(4.3) = 167.16

ycap(Little Rock) = 53.586 + 25.957(4.0) = 158.48

ycap(Biloxi) = 53.586 + 25.957(2.3) = 111.35

ycap(New Orleans) = 53.586 + 25.957(8.4) = 261.32

ycap(Baton Rouge) = 53.586 + 25.957(5.9) = 219.13

Thus, the values of ycap are 91.08, 92.04, 92.04, 167.16, 158.48, 111.35, 261.32, and 219.13.

The sum of squared residuals (SSR) can be calculated as

SSR = Σ(ycap - ybar)² = (91.08 - 143.14)² + (92.04 - 143.14)² + (92.04 - 143.14)² + (167.16 - 143.14)² + (158.48 - 143.14)² + (111.35 - 143.14)² + (261.32 - 143.14)² + (219.13 - 143.14)²

= 214,767.63

The total sum of squares (SST) can be calculated as

SST = Σ(y - ybar)² = (101.3 - 143.14)² + (75.8 - 143.14)² + (127.2 - 143.14)² + (137.8 - 143.14)² + (102.4 - 143.14)² + (236.8 - 143.14)² + (220.6 - 143.14)²

= 1,082,685.88

Finally, the coefficient of determination (R-squared) is the ratio of SSR to SST

R² = SSR / SST = 214,767.63 / 1,082,685.88 = 0.198

Multiplying by 100 to convert to a percentage, we get R² = 19.8%.

The coefficient of determination (R-squared) for the model is 0.198, indicating that approximately 19.8% of the variation in the sample values of weekly gross revenue is explained by the variation in television advertising.

This implies that the model is a reasonably good fit for the data, but there may be other factors that also influence the weekly gross revenue that are not accounted for in this model.

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--The given question is incomplete, the complete question is given

" Data for a sample of eight markets for a recent week follow. Weekly Gross Revenue ($100s) Television Advertising Newspaper Advertising ($100s) ($100s) Market Mobile 101.3 4.9 1.4 52.9 3.1 3.2 Shreveport Jackson 75.8 4.2 1.5 Birmingham 127.2 4.5 4.3 Little Rock 137.8 3.6 4.0 Biloxi 102.4 3.5 2.3 New Orleans 236.8 5.0 8.4 Baton Rouge 220.6 6.8 5.9 (a) Use the data to develop an estimated regression equation with the amount of television advertising as the independent variable. Let x represent the amount of television advertising. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a + sign before the blank. (Example: -300) ycap= ____ . (b) how much of the variation in the sample values of weekly gross revenue does the model in part (a) explain? if required, round your answer to two decimal places."--

The relation that shows y as a function of x is an equation.

An equation is a mathematical statement that two or more algebraic expressions share equality or equivalence.

Equations are depicted using the equation symbol (=), unlike mathematical expressions, which combine variables, numbers, constants, and values with mathematical operands but without the symbol of equality.

Thus, the relation, y is the dependent variable while x is the independent variable.

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The availability of this repairable product is approximately 0.762, or 76.2%.

In order to find the availability of a repairable product, we need to consider its failure rate and mean time to repair. The formula for availability (A) is:

A = MTBF / (MTBF + MTTR)

Where MTBF is Mean Time Between Failures and MTTR is Mean Time To Repair.

Since we have a constant failure rate (λ), we can calculate the MTBF as the inverse of the failure rate:

MTBF = 1 / λ

In this case, the failure rate (λ) is 0.0078 failures per hour. Let's calculate the MTBF:

MTBF = 1 / 0.0078 = 128.205 hours

Now, we know the MTTR is 40 hours. We can use the availability formula to find the answer:

A = MTBF / (MTBF + MTTR)
A = 128.205 / (128.205 + 40)
A = 128.205 / 168.205
A ≈ 0.762

So, the availability of this repairable product is approximately 0.762, or 76.2%.

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The graphical representation that would be the best for this data would be a circle graph. That is option C.

A circle graph, which is also called a pie chart, is defined as a type of data representation where by the information concerning a data set is displayed in a circular form and in a way that the various information displayed is a percentage of the total data set involved.

Now, the number of students that were surveyed = 100 students.

The number of subjects that are preferred by the students would be represented as x,y,z.

Therefore to represent the number of students that preferred a particular subject on the circle graph the following is carried out;

For subject x = Number of X/100 × 360/1

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Check the picture below.

so the pebble will hit the ground when h(t) = 0.

It's noteworthy that the pebble is falliing off a cliff, so it was at rest, so its initial velocity is 0, so in essence is falling as fast as gravity can drop it.

[tex]~~~~~~\textit{initial velocity in feet} \\\\ h(t) = -16t^2+v_ot+h_o \quad \begin{cases} v_o=\textit{initial velocity}&0\\ \qquad \textit{of the object}\\ h_o=\textit{initial height}&256\\ \qquad \textit{of the object}\\ h=\textit{object's height}&\\ \qquad \textit{at "t" seconds} \end{cases} \\\\\\ h(t)=-16t^2+256\implies 0=-16t^2+256\implies 16t^2=256 \\\\\\ t^2=\cfrac{256}{16}\implies t^2=16\implies t=\sqrt{16}\implies t=4 ~~ seconds[/tex]

The general solution of the given higher-order differential equation is y(x) = c1e[tex].^{x/2}[/tex]cos((1/2)√5x) + c2e[tex].^{x/2}[/tex]sin((1/2)√5x) + c3eˣ + c4e⁻ˣ.

The given higher-order differential equation is:

16(d⁴y/dx⁴) + 40(d²y/dx²) + 25y = 0

To find the general solution of this differential equation, we can assume that y(x) has the form:

y(x) = e[tex].^{rx}[/tex]

where r is a constant to be determined.

Differentiating y(x) four times with respect to x, we get:

d⁴y/dx⁴ = r⁴e[tex].^{rx}[/tex]

Differentiating y(x) two times with respect to x, we get:

d²y/dx² = r²e[tex].^{rx}[/tex]

Substituting these derivatives and y(x) into the differential equation, we get:

16(r⁴e[tex].^{rx}[/tex]) + 40(r²e[tex].^{rx}[/tex]) + 25e[tex].^{rx}[/tex] = 0

Simplifying this equation by dividing through by e[tex].^{rx}[/tex], we get:

16r⁴ + 40r² + 25 = 0

This is a quadratic equation in r². Solving for r² using the quadratic formula, we get:

r² = [-40 ± √(40² - 4(16)(25))] / 2(16)

r² = [-40 ± √(3600)] / 32

r² = [-40 ± 60] / 32

We get two possible values for r²:

r² = 5/4 or r² = 1

Taking the square root of each value, we get:

r = ±(1/2)i√5 or r = ±1

Thus, the general solution of the given higher-order differential equation is:

y(x) = c1e[tex].^{x/2}[/tex]cos((1/2)√5x) + c2e[tex].^{x/2}[/tex]sin((1/2)√5x) + c3eˣ + c4e⁻ˣ

where c1, c2, c3, and c4 are constants determined by the initial or boundary conditions of the specific problem.

Learn more about differential equation :

https://brainly.com/question/14926307

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The complete question is :

find the general solution of the given higher-order differential equation : 16(d⁴y/dx⁴) + 40(d²y/dx²) + 25y = 0

Answer:

U' (5, 1 )

Step-by-step explanation:

under a reflection in the x- axis

a point (x, y ) → (x, - y ) , then

U (5, - 1 ) → U' (5, - (- 1) ) → U' (5, 1 )

Answer:

a

Step-by-step explanation:

to find the missing side x , subtract the sum of the 5 given sides from the given perimeter.

x = 137 - (39 + 37 + 12 + 10 + 13) = 137 - 111 = 26 m