Find the value of x such that the data set has the given mean.

102​, 120​, 103​, 112​, 110​, ​x; mean 108

Expressing this function as a piecewise function, we get;

y = -x + 1         for x< -5

y = -1/2x + 4    for x> 4

According to the question, we can see that the graph is a line for x < -5. We will find two points on this line to find out the slope.

( - 5,6) and ( -8,9)

The slope is m= ( y2-y1)/(x2-x1)

m = ( 9-6)/(-8 - -5) = 3/ ( -8+5) = 3/-3

The slope is -1

Using point-slope form, we will find the general equation of this line

y-y1 = m(x-x1)  and the point ( -8,9)

y -9 = -1(x - -8)

y -9 = -1(x +8)

y-9 =  -x - 8

y = -x + 1   for x< -5

The graph is a line for  x > 4

(4,2) and ( 6,1)

The slope is m= ( y2-y1)/(x2-x1)

m = ( 1 - 2)/(6 - 4) = -1/ (2) = -1/2

The slope is -1/2

Using point-slope form

y-y1 = m(x-x1)  and the point (6,1)

y -1 = -1/2(x - 6)

y-1 = -1/2 x  + 3

y = -1/2x + 4   for x> 4

Therefore, expressing this function as a piecewise function, we get;

y = -x + 1         for x< -5

y = -1/2x + 4    for x> 4

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The critical value is approximately 2.681. Since the absolute value of the test statistic (4.114) is greater than the critical value (2.681), we can reject the null hypothesis at the 0.01 significance level and conclude that there is evidence to support the claim that Praxor is effective at lowering cholesterol levels compared to a placebo.

Hypothesis testing is a statistical method used to determine whether there is enough evidence to support a claim about a population.

In this case, the claim being made is that people who take Praxor will experience a greater decrease in cholesterol levels compared to those taking a placebo.

The first step in hypothesis testing is to state the null and alternative hypotheses. The null hypothesis, denoted as H₀, is the assumption that there is no difference between the two populations being compared. The alternative hypothesis, denoted as H₁, is the claim being made, which is that there is a difference between the two populations.

In this case, the null hypothesis would be that there is no difference in the mean cholesterol level decrease between the two groups, while the alternative hypothesis would be that the mean cholesterol level decrease in the treatment group is greater than that in the control group.

Next, a significance level, denoted as α, is chosen. This represents the probability of making a Type I error, which is rejecting the null hypothesis when it is actually true. In this case, a significance level of 0.01 is chosen.

The next step is to calculate the test statistic, which is a value that measures how far the sample data deviates from what is expected under the null hypothesis. The test statistic used in this case is the two-sample t-test. This test assumes that the two populations being compared have normal distributions and that their variances are not equal.

The formula for the two-sample t-test is:

t = (x₁ - x₂) / √√(s₁²/n1 + s₂²/n₂)

Where x₁ and x₂ are the sample means, s₁ and s₂ are the sample standard deviations, and n₁ and n₂ are the sample sizes for the two groups being compared.

Substituting the values in the formula we get,

= (19.9 - 19.3) / √((3.9²/32) + (1.3²/36))

t ≈ 4.114

Finally, we compare the test statistic to a critical value from a t-distribution table with degrees of freedom equal to n₁ + n₂ - 2 and a significance level of 0.01. If the absolute value of the test statistic is greater than the critical value, we reject the null hypothesis in favor of the alternative hypothesis.

In this case, the critical value is approximately 2.681. Since the absolute value of the test statistic (4.114) is greater than the critical value (2.681), we can reject the null hypothesis at the 0.01 significance level and conclude that there is evidence to support the claim that Praxor is effective at lowering cholesterol levels compared to a placebo.

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Answer: 6,550.6666666666666666666666666667π

Step-by-step explanation:

Hope this helps! :)

Answer:Each of the shaded sections represents 25% of the total number of students in the class, and since we have evenly distributed the 12 students among them, each shaded section now represents 30% of the students (i.e., 25% + 5% = 30%).

Step-by-step explanation: To model this situation, we need to determine the total number of students in the class. We can use the given percentage to set up a proportion:

40% = 12 students / x total students

To solve for x, we can cross-multiply and simplify:

0.4x = 12

x = 12 / 0.4

x = 30

Therefore, there are 30 students in the class.

To evenly distribute the 12 students in the 4 shaded sections, we can divide 12 by 4 to get the number of students for each section:

12 students / 4 sections = 3 students per section

The task requires estimating the rate of change of atmospheric pressure with respect to altitude using the given data.

First, a table needs to be created to estimate the rate of change of pressure with respect to altitude. The rate of change will be the difference in pressure divided by the difference in altitude between two consecutive data points.

Second, two plots should be created: one illustrating the pressure depending on altitude, and another illustrating the estimated rate of change depending on altitude.

Third, a function should be constructed to model the pressure-altitude data. The function should be selected based on how well it fits the data points.

Fourth, the model function should be used to estimate the rate of change of atmospheric pressure with respect to altitude at different heights over the range from sea level to 10,000 ft.

Fifth, a comparison should be made between the rate of change information computed from the model function and the rate of change information estimated directly from the data. This comparison will be used to assess the accuracy of the model function.

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Answer:

0.80x400

Step-by-step explanation:

Answer:

21

Step-by-step explanation:

70 · .30 = 21

This is a linear equation in slope-intercept form, where the slope (m) is 50 and the y-intercept (b) is 62.

Since the milepost increases by a fixed amount of 50 for every hour that they drive, the most appropriate type of equation to describe this relationship is a linear equation.

A linear equation has the form y = mx + b, where m is the slope of the line and b is the y-intercept. In this case, the slope is 50, since the milepost increases by 50 for every hour of driving, and the y-intercept is 62, since they start at milepost 62.

Therefore, the equation that represents Abby's relationship between the milepost they pass, y, and the number of hours they drive, x, is:

y = 50x + 62

This is a linear equation in slope-intercept form, where the slope (m) is 50 and the y-intercept (b) is 62.

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To show that Harold is wrong about the cost of chocolate biscuits being $2 each, we can use the given information:

You bought 3 packets of plain biscuits and 5 packets of chocolate biscuits, and the total cost was $34.

Let's use the variables P for the cost of plain biscuits and C for the cost of chocolate biscuits.

We can write the equation:

3P + 5C = $34

Harold claims that the cost of chocolate biscuits is $2 each. So, let's substitute C = $2 into the equation:

3P + 5($2) = $34

Now, we can solve for P:
3P + $10 = $34
3P = $24
P = $8

So, the cost of plain biscuits is $8 each. This means you bought 3 packets of plain biscuits for $24 and 5 packets of chocolate biscuits for $10, which adds up to the total cost of $34.

Since the cost of plain biscuits came out to be a whole number, Harold's claim that chocolate biscuits cost $2 each is not necessarily wrong.

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The expected value of an original investment of 3000 that has a 10% chance of ending up with a value of 2000 is 2900. The expected value of the investment can be calculated by multiplying the probability of the investment ending up with a certain value by that value, and then summing up all the possible outcomes.

In this case, there is a 90% chance of the investment retaining its original value of 3000, and a 10% chance of it ending up with a value of 2000. To calculate the expected value, we can use the following formula:

Expected Value = (Probability of Outcome 1 × Value of Outcome 1) + (Probability of Outcome 2 × Value of Outcome 2)

Substituting the values,
Expected value = (0.9 x 3000) + (0.1 x 2000)
Expected value = 2700 + 200
Expected value = 2900

Therefore, the expected value of the original investment of 3000 is 2900.

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Answer:

250

Step-by-step explanation:

5 x 2= 10

25 x 10= 250

Cloud storage is the storage option that has the ability to update itself regularly.

Unlike internal hard drives and flash drives, which require manual updates and data transfers, cloud storage services automatically synchronize and update your files across multiple devices. This feature ensures that you always have access to the most recent version of your data, without needing to perform manual updates.

Cloud storage services operate on remote servers managed by service providers, allowing users to store, share, and access their data from any device with internet access. This not only provides convenience but also offers enhanced data security and protection against data loss due to hardware failure or damage.

On the other hand, internal hard drives and flash drives are physical storage devices that store data locally. While they offer a certain level of convenience and portability, they lack the ability to automatically update or sync across multiple devices, making them less versatile compared to cloud storage.

In summary, cloud storage is the storage option with the ability to update itself regularly, providing users with convenience, enhanced security, and the ability to access their data from multiple devices. Meanwhile, internal hard drives and flash drives require manual updates and are limited in their capacity to sync data across devices.

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The variables of interest are both non-parametric and measured on an ordinal scale, a suitable analysis for determining the relationship between them would be the Spearman rank correlation coefficient.

The Spearman rank correlation coefficient is a non-parametric measure of the strength and direction of association between two variables.

It is based on the rank order of observations for each variable, rather than their actual numerical values.

The coefficient can range from -1 perfect negative correlation to +1 perfect positive correlation.

And with a value of 0 indicating no correlation.

Use the Spearman rank correlation coefficient to determine the strength and direction of the relationship between CI and student satisfaction.

The coefficient would tell us if there is a significant correlation between the two variables, and whether the correlation is positive or negative.

Perform the analysis, first rank the observations for both variables and calculate the difference in ranks between each pair of observations.

Calculate the Spearman rank correlation coefficient using the formula,

ρ = 1 - (6Σd² / n(n² - 1))

where ρ is the Spearman rank correlation coefficient,

d is the difference in ranks for each pair of observations,

n is the sample size,

and n² is the sum of the squares of the ranks.

A value of ρ close to +1 would indicate a strong positive correlation between the two variables.

A value close to -1 would indicate a strong negative correlation.

A value close to 0 would indicate no significant correlation between the two variables.

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The quotient of the given division is 0.4082, under the condition that dividend is 4.082 and divisor is 10,000.

The count of zeros in 10,000 is 4, then we have to transfer the decimal point four places to the left to divide by 10,000. Here, we have to relie on the basic principles involved in division.

Then, in order to find the quotient of 4.082 and 10,000, we have to divide 4.082 by 10,000. To perform this, we expand the number by moving the decimal point forward of 4.082.

That is,

[tex] \frac{4.082 }{10000} [/tex]

= 0.4082

The quotient is 0.4082

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To reduce the quadratic form 2yz^2+2xz+2xy to canonical form, we need to complete the square.

First, we factor out the coefficient of z^2 from the yz^2 term:

2yz^2 = 2z(yz)

Next, we add and subtract the square of half the coefficient of z from the resulting expression:

2z(yz + (x/y)^2 - (x/y)^2)

= 2z((y + x/y)^2/4 - (x/y)^2)

= z(y + x/y)^2/2 - zx^2/y

Now, we can see that the quadratic form can be written in the canonical form:

q(x,y,z) = (y + x/y)^2/2 - x^2/y

To find the rank, we need to count the number of non-zero eigenvalues. In this case, we have two non-zero eigenvalues, so the rank is 2.

To find the index, we need to count the number of positive, negative, and zero eigenvalues. We can see that there is one positive eigenvalue and one negative eigenvalue, so the index is 1.

Finally, to find the signature, we subtract the index from the rank. In this case, the signature is 1.
To reduce the quadratic form 2yz^2 + 2xz + 2xy to canonical form by an orthogonal transformation, we first find the matrix representation of the form. The given quadratic form can be written as Q = [x, y, z] * A * [x, y, z]^T, where A is a symmetric matrix:

A = | 0  1  1 |
    | 1  0  1 |
    | 1  1  2 |

Now, we find the eigenvalues and eigenvectors of A. The eigenvalues are λ₁ = 3, λ₂ = -1, and λ₃ = 0, with corresponding eigenvectors:

v₁ = [1, 1, 1]
v₂ = [-1, 1, 0]
v₃ = [-1, -1, 2]

Normalize the eigenvectors to form an orthogonal matrix P:

P = |  1/√3   1/√2  -1/√6 |
    |  1/√3  -1/√2  -1/√6 |
    |  1/√3    0    2/√6 |

Now, we can transform A to its canonical form using the orthogonal matrix P:

D = P^T * A * P
D = | 3  0  0 |
    | 0 -1  0 |
    | 0  0  0 |

So, the canonical form of the quadratic form is:

Q canonical = 3x'^2 - y'^2

The rank of the quadratic form is the number of non-zero eigenvalues in the diagonal matrix D. In this case, the rank is 2.

The index of the quadratic form is the number of positive eigenvalues in D, which is 1 in this case.

The signature of the quadratic form is the difference between the number of positive and negative eigenvalues in D. In this case, the signature is 1 - 1 = 0.

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The  evaluated volume of the given  triangular prism is 956 cm³, considering that base is a form of isosceles triangle in which the equal sides are 12cm and the angle between them is 130 degrees.

The volume of a triangular prism can be calculated by multiplying the base area by the height of the prism. The base of the triangular prism is an isosceles triangle with equal sides of 12 cm and an angle between them of 130 degrees.

The area of an isosceles triangle can be calculated using the formula

(b/4) × √(4a² - b²),

here

a = length of the equal sides and b is the length of the third side.

For the given case,

a = 12 cm

b = 12 ×sin(65) cm

≈ 10.9 cm.

Hence,

the area of the base is

(10.9/4) × √(4× 12² - 10.9²) cm²

≈ 63.7 cm².

Hence, the height of the prism is 15 cm.  

Now,

15 × 63.7

= 956 cm³

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The complete question is

Find the volume of the triangular prism, whose base is an isosceles triangle where the equal sides are 12cm an the angle between them is 130 degrees. The height of the prism is 15cm. Round to 3 significant figures

Note that this graph only shows the behavior of the function for positive values of x, as the natural logarithm is not defined for x ≤ 0.

What is Function?

Function can be defined in which it relates an input to output.

To graph the function g(x) = ln(x)÷4, we can start by creating a table of values:

x g(x) = ln(x)÷4

1 0

2 0.173

10 0.575

100 0.921

1000 1.146

Next, we can plot these points on a coordinate plane and connect them to create a smooth curve:

Therefore, Note that this graph only shows the behavior of the function for positive values of x, as the natural logarithm is not defined for x ≤ 0.

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After performing an ANOVA test on the productivity data with a 0.05 level of significance, we reject the null hypothesis and conclude that the average productivity under different programs are not the same. Ahmadi should implement the most effective program and investigate the reasons for differences.

To analyze the productivity data and determine if there are significant differences between the four programs, we can use an ANOVA (Analysis of Variance) test. The null hypothesis is that the average productivity under different programs is the same, while the alternative hypothesis is that they are not the same.

After performing the ANOVA test at a 0.05 level of significance (α = 0.05) on the provided data, if the p-value is less than 0.05, we reject the null hypothesis and conclude that the average productivity under different programs are not the same. Therefore, the correct answer is: "by the f-test since we reject the null hypothesis (p-value<0.05), average productivity under different programs are not the same."

As the statistical consultant to Ahmadi, I would advise them to implement the program(s) that showed a statistically significant increase in productivity compared to the others, and to consider further investigation and analysis to identify the reasons behind the observed differences.

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The true statements are Numbers with same absolute value are opposites because they are same distance from each other and from 0 on the number line. The |7.1| = 7.1. So, correct options are B, C and E.

b) Numbers with the same absolute value are opposites because they are the same distance from each other. This is true because absolute value is the distance from a number to zero on the number line, and if two numbers have the same distance from zero, then they must be equidistant from zero and therefore, they are opposite in sign.

c) The |7.1| = 7.1 because the distance from 7.1 to 0 on the number line is 7.1 units. This is true because the absolute value of a number is always positive, and it represents the distance of that number from zero on the number line.

d) The |-8.4| = 8.4 because the distance from -8.4 to 8.4 on the number line is 0 units. This is false, as the distance between -8.4 and 8.4 on the number line is 16.8 units. The correct value of the absolute value of -8.4 is 8.4.

e) Numbers with the same absolute value are opposites because they are the same distance from 0 on the number line. This is true because 0 is the midpoint of the number line, and if two numbers have the same distance from 0, then they must be equidistant from zero and therefore, they are opposite in sign.

Therefore, the correct statements are b, c, and e.

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Answer:does anyone have the image

Step-by-step explanation:

a) The equation of the regression line is Travel Time = β₀ + β₁(Distance Traveled) + ɛ. b) The slope of the regression line indicates the increase in travel time and the intercept represents the estimated travel time. c) R₂ is 0.404. d) Regression equation will be used. e) Residual cannot be calculated. f) No, the given linear model is not appropriate to use.

a) The equation of the regression line for predicting travel time is

Travel Time = β₀ + β₁(Distance Traveled) + ɛ

where β₀ is the intercept, β₁ is the slope, Distance Traveled is the independent variable, and Travel Time is the dependent variable.

b) The slope of the regression line indicates the increase in travel time (in minutes) for every one-mile increase in distance traveled. The intercept represents the estimated travel time (in minutes) when the distance traveled is zero. In this context, the intercept is not meaningful since there cannot be a distance of zero between two stops.

c) To calculate R₂, we need to first calculate the correlation coefficient (r) between Travel Time and Distance Traveled

r = (covariance of Travel Time and Distance Traveled) / (standard deviation of Travel Time × standard deviation of Distance Traveled)

Using the given values, we have

r = (0.636 × 113 × 99) / (113 × 99) = 0.636

Then, we can calculate R₂ as

R₂ = r₂ = 0.6362 = 0.404

R₂ represents the proportion of variance in Travel Time that is explained by Distance Traveled. In this context, R₂=0.404 indicates that 40.4% of the variation in travel time from one stop to the next on the Coast Starlight can be explained by the distance traveled between those stops.

d) To estimate the time it takes for the Starlight to travel between Santa Barbara and Los Angeles, we need to use the regression equation

Travel Time = β₀ + β₁(Distance Traveled)

We know that the distance between Santa Barbara and Los Angeles is 103 miles. So, we plug this value into the equation

Travel Time = β₀ + β₁(103)

To solve for the travel time, we need to know the values of β₀ and β₁. We can use the given mean and standard deviation values to estimate these parameters using linear regression. However, we are not given this information in the question.

e) To calculate the residual, we need to first calculate the predicted travel time based on the regression equation

Travel Time = β₀ + β₁(Distance Traveled)

We are told that the distance between Santa Barbara and Los Angeles is 103 miles, so we can plug this value into the equation to get the predicted travel time

Predicted Travel Time = β₀ + β₁(103)

However, we are not given the values of β₀ and β₁, so we cannot calculate the predicted travel time.

The residual is the difference between the actual travel time and the predicted travel time. In this case, we are told that the actual travel time is 168 minutes, and we do not have the predicted travel time. Therefore, we cannot calculate the residual.

f) It would not be appropriate to use this linear model to predict the travel time from Los Angeles to a point 500 miles away from Los Angeles, because the linear relationship between travel time and distance traveled may not hold beyond the range of distances that were used to estimate the regression equation. The linear model assumes that the relationship between travel time and distance traveled is constant across all distances, which may not be true. Additionally, adding a stop at a point 500 miles away from Los Angeles may affect the relationship between travel time and distance traveled, since there may be other factors that influence travel time at that distance. Therefore, a new regression model would need to be estimated using data that includes stops at or beyond the 500-mile mark.

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The sequence (n){(1-2)/(3^n+1) + 3} is bounded and decreasing. The GLB is 3 and the LUB is 1.

To determine the boundedness and monotonicity of the sequence, we can look at the limit as n approaches infinity.

Taking the limit of the sequence, we have:

lim(n→∞) [(1-2)/(3^n+1) + 3] = 3

This means that the sequence approaches a finite value as n gets larger, so the sequence is bounded.

Next, to check the monotonicity of the sequence, we can take the first derivative of the sequence with respect to n:

d/dn [(1-2)/(3^n+1) + 3] = [(2-1)(-ln3)(3^n+1)]/[(3^n+1)^2]

Simplifying, we get:

d/dn [(1-2)/(3^n+1) + 3] = (-ln3)/(3^n+1)^2

Since the derivative is negative for all n, the sequence is decreasing.

To find the GLB and LUB, we can use the fact that the sequence is decreasing and bounded. Since the sequence approaches 3 as n approaches infinity, 3 is the lower bound.

To find the upper bound, we can use the fact that the sequence is decreasing and start with the second term, which is 2. Therefore, the upper bound is 2. Since 1 < 2, we can conclude that the LUB is 1.

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To find the height of the rocket after 2.5 seconds,

you'll need to plug in t = 2.5 into the given equation h(t) = 160t - 16t².

h(2.5) = 160(2.5) - 16(2.5)²
h(2.5) = 400 - 100
h(2.5) = 300 meters

The height of the rocket after 2.5 seconds is 300 meters.

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Answer:

h = 30 cm

Step-by-step explanation:

Given:

V (volume) = 69,120π cm^3

d (diameter) = 96 cm (r (radius) = 0,5 × 96 = 48 cm

Find: h (height) - ?

[tex]v = \frac{1}{3} \times \pi {r}^{2} \times h[/tex]

[tex] \frac{1}{3} \times \pi \times {48}^{2} \times h = 69120\pi[/tex]

Multiply the whole equation by 3 to eliminate the fraction:

[tex]2304\pi \times h = 69120\pi[/tex]

[tex]h = 30[/tex]

The correct equation that gives the population, a(x), of the town x years since 2005 is:

a(x) = 12,500 * (1 + 0.054)ˣ

The given problem states that the population of the town has been increasing by about 5.4% per year since 2005. To formulate the equation for the population, we need to use the initial population of 12,500 in 2005 and apply the growth rate of 5.4% per year.

The general formula for exponential growth is:

a(x) = a(0) * (1 + r)ˣ

Where:

a(x) is the population at a given time x years since the initial time,

a(0) is the initial population (12,500 in this case),

r is the growth rate (5.4% or 0.054 as a decimal),

x is the number of years since the initial time (2005 in this case).

Plugging in the values, we get:

a(x) = 12,500 * (1 + 0.054)ˣ

This equation calculates the population of the town x years since 2005.

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Step-by-step explanation:

A, 7^(x+3) = 823, 543

7^(x+3) = 823, 543

7^(x+3) = 7^7 ....... write in the power form which it's base must be 7 in order to equalify the power

x+3 = 7

x = 4

B, 4^ -4x = 4^-8

4 ^ -4x = 1/65, 536

4^ -4x = 1/4^8 ........ write in the power form

4^ -4x = 4^-8

-4x = -8 ..... write equality among the power cause it's base is same

x=2

C, 1/(6^(x-5) ) = 1296

1/(6^(x-5) ) = 1296

6^-(x-5) = 1296

6^-(x-5) = 6^4........ write in the power form

-(x-5) = 4

-x + 5 = 4

-x = -11

x = 1

D, 1/3^x+7 = 1/243

1/3^x+7 = 1/243

3 ^ -(x+7) = 3^-5 .... write in the power form

-(x+7) = -5

-x-7 = -5

-x = 2

x= -2

a) The percentage of men with a height less than or equal to 55.8 inches is approximately 0.00007 or 0.007%.

b) The door design is inadequate, but because the jet is relatively small and seats only six people, a much higher door would require major changes in the design and cost of the jet, making a larger height not practical.

Option (a) is correct.

a) To determine the percentage of adult men who can fit through the door without bending, we need to find the proportion of men whose height is less than or equal to the doorway height of 55.8 inches. We can use the normal distribution formula and standardize the variable:

Z = (X - μ) / σ

Where X is the doorway height, μ is the mean height of men, and σ is the standard deviation of men's heights.

Z = (55.8 - 67.8) / 3.1 = -3.87

Using a standard normal distribution table, we can find that the percentage of men with a height less than or equal to 55.8 inches is approximately 0.00007 or 0.007%.

Therefore, only a very small percentage of adult men can fit through the door without bending.

b)The door design is inadequate, but because the jet is relatively small and seats only six people, a much higher door would require major changes in the design and cost of the jet, making a larger height not practical.

While it is true that most women will be able to fit through the door without bending, it is not acceptable to design a door that does not accommodate all potential passengers. The door should be designed to allow all passengers to enter without any discomfort or difficulty.

However, in the case of this executive jet, increasing the height of the door to accommodate all potential male passengers would require major redesign and cost implications.

In summary, while the current door design is inadequate, it may not be practical or feasible to make significant changes due to design and cost constraints.

Therefore, the correct option is a.

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The area of the rhombus is 1140 square inches.

Let the side length of the rhombus be "a" and let the length of the other diagonal be "d".

Since a rhombus has all sides congruent, the perimeter is given by:

4a = 136

Simplifying, we get:

a = 34

We can use the formula for the area of a rhombus:

Area = (diagonal 1 x diagonal 2)/2

Substituting the given values:

Area = (60 x d)/2

Area = 30d

Now we can substitute the value of "a" in terms of "d" into the formula for the length of the diagonal:

d = √(a² + b²)

d = √(34² + b²)

d = √(1156 + b²)

We also know that the perimeter of the rhombus is given by:

4a = 136

Substituting the value of "a" we found earlier:

4(34) = 136

So the length of the other diagonal can be found by subtracting the length of the given diagonal from the perimeter, and dividing by 2:

d = (136 - 60)/2 = 38

Therefore, the length of the other diagonal is 38 inches.

To find the area, we can substitute the value we found for "d" into the formula we derived earlier:

Area = 30d = 30(38) = 1140

So the area of the rhombus is 1140 square inches.

To know more about rhombus refer here:

https://brainly.com/question/27870968

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