If an oxygen bottle delivers 7 cubic feet of oxygen in 4 minutes at 27,000 feet and -65 degrees F. How much will the system deliver in 13 minutes

Answer:

\(\large\boxed{\tt x = 2}\)

Step-by-step explanation:

\(\textsf{We are asked to solve for x in the given equation.}\)

\(\textsf{We should know that x is cubed, meaning that it's multiplied by itself 3 times.}\)

\(\textsf{We should isolate x on the left side of the equation, then find x by cubic rooting}\)

\(\textsf{both sides of the equation.}\)

\(\large\underline{\textsf{How is this possible?}}\)

\(\textsf{To isolate variables, we use Properties of Equality to prove that expressions}\)

\(\textsf{are still equal once a constant has changed both sides of the equation. A Cubic}\)

\(\textsf{Root is exactly like a square root, but it's square rooting the term twice instead}\)

\(\textsf{of once.}\)

\(\large\underline{\textsf{For our problem;}}\)

\(\textsf{We should use the Subtraction Property of Equality to isolate x, then cubic root}\)

\(\textsf{both sides of the equation.}\)

\(\large\underline{\textsf{Solving;}}\)

\(\textsf{Subtract 1 from both sides of the equation keeping in mind the Subtraction}\)

\(\textsf{Property of Equality;}/tex]

\(\tt \not{1} - \not{1} - x^{3} = 9 - 1\)

\(\tt - x^{3} = 8\)

\(\textsf{Because x}^{3} \ \textsf{is negative, we should exponentiate both sides of the equation by}\)

\(\textsf{the reciprocal of 3, which is} \ \tt \frac{1}{3} .\)

\(\tt (- x^{3})^{\frac{1}{3}} = 8^{\frac{1}{3}}\)

\(\underline{\textsf{Evaluate;}}\)

\(\tt (- x^{3})^{\frac{1}{3}} \rightarrow -x^{3 \times \frac{1}{3} } \rightarrow \boxed{\tt -x}\)

\(\textsf{*Note;}\)

\(\boxed{\tt A^{\frac{1}{C}} = \sqrt[\tt C]{\tt A}}\)

\(\tt 8^{\frac{1}{3}} \rightarrow \sqrt[3]{8} \rightarrow 2^{1} \rightarrow \boxed{\tt 2}\)

\(\underline{\textsf{We should have;}}\)

\(\tt -x=2\)

\(\textsf{Use the Division Property of Equality to divide each side of the equation by -1;}\)

\(\large\boxed{\tt x = 2}\)

An expression for which subtracting 5 from an expression would isolate the variable is -9x + 5 = x + 2

Algebraic expressions are described as expressions that consists of coefficients, terms, variables, factors and constants.

These expressions are also known to consist of arithmetic operators, which includes;

From the information given, we have to subtract five from an expression to isolate the variable

Now, let's us the algebraic expression;

-9x + 5 = x + 2

Let's subtract 5 from both sides of the equation, we get;

-9x + 5 - 5 = x + 2 - 5

add and subtract the like terms

-9x + x = -3

-8x = -3

x = 3/8

Hence, the expression is -9x + 5 = x + 2

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The highest net income earned by General Electric (GE) over the given period can be calculated from the given information below:$$P(t)=-20t^2+6.6t+16$$Where P(t) is the net income earned by GE, and t is the time.

in years since 2005. The value of t is in the range 0 to 5, thus; \($$P'(t)=\frac{d}{dt} (-20t^2+6.6t+16)=-40t+6.6$$$$P'(t)=0\ rightarrow -40t+6.6=0$$$$t=\frac{6.6}{40}=0.165\approx0.17$$\)

To verify that this is a maximum, we can use the second derivative of P. \($$P''(t)=-40<0$$\). Thus, the highest net income earned by GE over the given period is attained at t = 0.17 and can be calculated as follows:\($$P(0.17)=-20(0.17)^2+6.6(0.17)+16$$$$P(0.17) \approx \boxed{18}$$\)

The highest net income earned by GE over the given period is approximately $18$ billion income .

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Answer:

d = 7

Step-by-step explanation:

In the circle shown, the radius is 3.5. The diameter is double the radius (d = 2r), so:

d = 2 (3.5)

d = 3.5 + 3.5

d = 7

Answer:

x=9

Step-by-step explanation:

55+5x=100. -subtract 55 from 100

5x=45. - divide 45 by 5

x=9

Where the above conditions exist,

The random variable T = L + C represents the total time it takes Lorelei and Chance to finish a randomly selected 3-layer wedding cake. Since L and C are independent and Normally distributed, T is also Normally distributed with mean:

Mu_T = Mu_L + Mu_C = 37 + 52 = 89

and variance:

Var(T) = Var(L) + Var(C) = 12^2 + 7^2 = 193

So the standard deviation of T is:

Sigma_T = sqrt(Var(T)) = sqrt(193) = 13.89

The shape of T is also Normally distributed, since it is a sum of two independent Normally distributed variables.

To find the probability that Lorelei and Chance finish a randomly selected 3-layer wedding cake in under 90 minutes, we need to calculate the z-score for this value and then find the corresponding probability from the z-table. The z-score is:

z = (90 - 89) / 13.89

= 0.072

From the z-table, we find that the probability of a Z-score less than or equal to 0.072 is 0.5287.

Therefore, the probability that Lorelei and Chance totally finish a randomly selected 3-layer wedding cake in under 90 minutes is 0.5287 or approximately 53%.

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False. The expected cell frequency in statistical analysis, specifically in the context of contingency tables and chi-square tests, is not based on the researcher's opinion. Instead, it is determined through mathematical calculations and statistical assumptions.

In contingency tables, the expected cell frequency refers to the expected number of observations that would fall into a particular cell if the null hypothesis of independence is true (i.e., if there is no relationship between the variables being studied). The expected cell frequency is calculated based on the marginal totals (row totals and column totals) and the overall sample size.

The expected cell frequency is computed using statistical formulas and is not influenced by the researcher's opinion or subjective judgment. It is a crucial component in determining whether the observed frequencies in the cells significantly deviate from what would be expected under the null hypothesis.

By comparing the observed cell frequencies with the expected cell frequencies, statistical tests like the chi-square test can assess the association or independence between categorical variables in a data set.

Thus, the statement "the expected cell frequency is based on the researcher's opinion" is false. The expected cell frequency is derived through statistical calculations and is not subject to the researcher's subjective input.

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- 2 1/3

Hi there !

6  2/9 : ( - 2 2/3) =

= (6*9+2)/9 : -(2*3+2)/3

= 56/9 : - 8/3

= 56/9 × - 3/8

simplify 56 - 8 ; 9 - 3

= 7/3 × - 1/1

= - 7/3

= - 2 1/3

Good luck !

Step-by-step explanation:

a) The test statistic is (4.4-4)/(1.3/sqrt(70)) = 2.83. The p-value is 0.0023. Since the p-value is less than 0.05, we reject the null hypothesis.

b) The test statistic is (5.3-4.4)/sqrt((1.4^2/106)+(1.3^2/70)) = 4.09. The p-value is less than 0.0001. Since the p-value is less than 0.05, we reject the null hypothesis.

Answer: 11 ft

Step-by-step explanation:

Given

The boy is standing 40 feet away from the tree

the angle of elevation for the tree is \(32^{\circ}\\\)

the angle of elevation for the bird is \(42^{\circ}\\\)

using figure

\(\frac{h+x}{40}=\tan 42^{\circ}\\h+x=40\tan 42^{\circ}\ldots (i)\\Now,\\\tan 32^{\circ}=\frac{h}{40}\\h=40\tan 32^{\circ}\)

Put the value of h in equation (i)

\(40\tan 32^{\circ}+x=40\tan 42^{\circ}\\x=40[\tan 42^{\circ}-\tan 32^{\circ}]\\x=40[0.9-0.624]=0.276\times 40=11.04\ ft\)

Answer:

4$ for one hotdog

Step-by-step explanation:

60/15 =

4.

One hotdog equal 4$

brainliest?

The rate of one hot dog is $4.

We are given that there are 15 hot dogs which cost $60.We have to calculate the amount of rate for one hot dog.

By the unitary method,

Amount of rate for one hot dog = is $60/15=$4

Hence one hot dog cost $4.

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Answer to 2a: The mean of Asset A is 0.235  and the variance is 0.0123

Answer to 2b: The correlation coefficient between Asset A and C is approximately\(\(-0.670\) (Boom), \(-0.187\) (Average), \(-0.670\)\)(Bust).

2a. Mean of Asset A (Expected Value):

The mean of Asset A (E(A)) can be calculated as:

\(\[E(A) = \sum_{i} (x_i \cdot P_i)\]\)

where \(\(x_i\)\) represents the return on Asset A in each state and\(v \(P_i\)\) represents the probability of that state.

Using the given information, we have:

Boom:

\(\(E(A) = (0.35 \cdot 0.30) + (0.20 \cdot 0.50) + (0.05 \cdot 0.20) = 0.235\)\)

Average:

\(\(E(A) = (0.35 \cdot 0.30) + (0.20 \cdot 0.50) + (0.05 \cdot 0.20) = 0.235\)\)

Bust:

\(\(E(A) = (0.35 \cdot 0.30) + (0.20 \cdot 0.50) + (0.05 \cdot 0.20) = 0.235\)\)

Therefore, the mean of Asset A is\(\(E(A) = 0.235\).\)

2b. Correlation Coefficient of A and C:

The correlation coefficient\((\(\rho\))\)between Asset A and C can be calculated using the formula:

\(\[\rho = \frac{{\text{{Cov}}(A, C)}}{{\sigma_A \cdot \sigma_C}}\]\)

where\(\(\text{{Cov}}(A, C)\)\) represents the covariance between Asset A and C, and \((\sigma_A\)\) and\(\(\sigma_C\)\)represent the standard deviations of Asset A and C, respectively.

Using the given information, we have:

Boom:

\(\(\text{{Cov}}(A, C) = (0.35 - 0.235) \cdot (0.10 - 0.25) = -0.017\)\)

Average:

\(\(\text{{Cov}}(A, C) = (0.20 - 0.235) \cdot (0.15 - 0.25) = -0.005\)\)

Bust:

\(\(\text{{Cov}}(A, C) = (0.05 - 0.235) \cdot (0.35 - 0.25) = -0.017\)\)

Now, we calculate the standard deviations of Assets A and C:

\(\(\sigma_A = \sqrt{{\text{{Var}}(A)}} = \sqrt{0.0123} \approx 0.1108\)\)

\(\(\sigma_C = \sqrt{{\text{{Var}}(C)}} = \sqrt{0.0517} \approx 0.2274\)\)

Finally, we can calculate the correlation coefficient:

Boom:

\(\(\rho = \frac{{-0.017}}{{0.1108 \cdot 0.2274}} \approx -0.670\)\)

Average:

\(\(\rho = \frac{{-0.005}}{{0.1108 \cdot 0.2274}} \approx -0.187\)\)

Bust:

\(\(\rho = \frac{{-0.017}}{{0.1108 \cdot 0.2274}} \approx -0.670\)\)

Therefore, the correlation coefficient between Asset A and C is approximately\(\(\rho \approx -0.670\) (Boom), \(\rho \approx -0.187\) (Average), and \(\rho \approx -0.670\) (Bust).\)

Answer to 2a: \(The mean of Asset A is \(0.235\) and the variance is \(0.0123\.\)

Answer to 2b: The correlation coefficient between Asset A and C is approximately\(\(-0.670\) (Boom), \(-0.187\) (Average), \(-0.670\)\)(Bust).

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The desired fuel efficiency of a car two years from now would ideally be improved compared to the current fuel efficiency.

There are several reasons why we would want the fuel efficiency of a car to be better in the future:

Environmental Concerns: Improving fuel efficiency helps reduce carbon emissions and minimize the environmental impact of vehicles. As the world becomes more conscious of climate change and the need to reduce greenhouse gas emissions, enhancing fuel efficiency plays a vital role in mitigating environmental damage.

Energy Conservation: Better fuel efficiency means using less fuel to travel the same distance. With finite energy resources and the need to conserve them, improving fuel efficiency helps reduce the overall energy consumption in transportation, leading to better resource management.

Cost Savings: Increasing fuel efficiency directly translates to lower fuel consumption and reduced expenses for car owners. With rising fuel prices, having a more fuel-efficient car can significantly cut down on fuel costs, saving money for individuals and businesses.

Technological Advancements: As technology progresses, advancements in engine design, aerodynamics, lightweight materials, and alternative energy sources enable the development of more fuel-efficient vehicles. Striving for improved fuel efficiency encourages innovation in the automotive industry, leading to the creation of more sustainable and eco-friendly transportation options.

Government Regulations: Many governments worldwide have implemented fuel efficiency standards and regulations to reduce fuel consumption and emissions. By meeting or exceeding these standards, car manufacturers contribute to a cleaner and more sustainable transportation sector.

Ultimately, aiming for improved fuel efficiency two years from now aligns with the global push for environmental sustainability, energy conservation, cost savings, technological advancements, and adherence to regulatory standards. It benefits both individuals and society as a whole by promoting a greener and more efficient approach to transportation.

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The amount of money in Iris's checking account can be modeled by a linear function of the form:

y = mt + b

where y is the amount of money in the account, t is the time (measured in years), m is the rate of interest, and b is the initial amount in the account.

In this case, we have m = 0.04 (since the interest rate is 4% per year) and b = 180 (since that's the initial amount in the account). Therefore, the linear function that models the amount of money in Iris's checking account at any time t is:

y = 0.04t + 180

For example, if t = 5 (years), then the amount of money in Iris's checking account is 0.04 * 5 + 180 = 198 dollars.

The equation that can be used to find f, the number of offices on each floor of this building, is,

18f = 396.

The correct option is b.

The division in mathematics is one kind of operation. In this process, we split the expressions or numbers into the same number of parts.

Given:

There are 18 floors in the building.

Each floor has the same number of offices.

Altogether, there are 396 offices in the building.

So, the equation that can be used to find f, the number of offices on each floors of this building

18f = 396

f = 22

Therefore, the required equation is 18f = 396.

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The linear equation in the two-point form using the points (2, 2) and (x2, y2) is y - y1 = m(x - x1).

To determine the slope (m), we can use the formula:

m = (y2 - y1) / (x2 - x1)

Given that (x1, y1) = (2, 2), let's substitute the values into the formula:

m = (y2 - 2) / (x2 - 2)

The slope (m) will be determined once we have the values for (x2, y2). If you provide the second point or any additional information, I can calculate the slope and provide the complete equation in the two-point form.

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Answer:

Step-by-step explanation:

Volume=4/3×πr³=4/3×π×6.5³=1098.5/3 ×π≈1150.35 km³

Answer:

-7

Step-by-step explanation:

Answer:

tour answer should be no they are not be parellel

Step-by-step explanation:

Answer:

tour answer should be no they are not be parellel

Step-by-step explanation:

Answer:

60 cubic units

Step-by-step explanation:

Answer:

5

Step-by-step explanation:

Answer:

The answer is simple

Step-by-step explanation:

The answer is B, on a line graph the order goes from 0, 1, 2, 3 and so on without this order you can't use negative terms without a equation  

Efficient convolution of a signal x(n) with a causal filter h(n) can be done using the overlap-add method, where the signal is split into blocks, each block is zero-padded, convolved with the filter, and then added together.

The given scenario describes a technique for efficiently convolving a signal with a causal filter by using the circular convolution property of the discrete Fourier transform. The technique involves breaking up the signal and filter into smaller chunks, performing the circular convolution of these chunks using the Fourier transform, and then reassembling the resulting chunks to obtain the final convolution output.

This approach reduces the computational complexity of the convolution operation and is commonly used in digital signal processing applications.

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Efficient convolution of a signal x(n) with a causal filter h(n) can be done using the overlap-add method, where the signal is split into blocks, each block is zero-padded, convolved with the filter, and then added together.

The given scenario describes a technique for efficiently convolving a signal with a causal filter by using the circular convolution property of the discrete Fourier transform. The technique involves breaking up the signal and filter into smaller chunks, performing the circular convolution of these chunks using the Fourier transform, and then reassembling the resulting chunks to obtain the final convolution output.

This approach reduces the computational complexity of the convolution operation and is commonly used in digital signal processing applications.

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The type of data collected by the marketing researcher is categorical data, specifically nominal data.

Categorical data, also known as categorical variables, are variables that represent categories or groups. Unlike numerical data, which consists of continuous or discrete values, categorical data consist of a limited number of possible values, which are categories or groups that the data can belong to.

Based on the given problem, the customers have been classified into mutually exclusive categories or groups, such as "extremely satisfied," "satisfied," and "indifferent or unsatisfied," without any order or ranking. The categories do not have any meaningful mathematical relationship to one another.

Categorical data can be ordinal data if the categories have a clear order or ranking, but in this case, the categories do not have a clear order, so the data is nominal.

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Answer:

B, C, D

Step-by-step explanation:

edge 2023

The stem-and-leaf display and dotplot were used to analyze the data set of the number of times 40 randomly selected first-year students from a university ate at fast food restaurants during a 14-day period.

In the stem-and-leaf display, the data was organized by separating the tens digit (stem) from the ones digit (leaves). The distribution appeared somewhat skewed to the right, with the majority of values concentrated towards the lower end and a few higher values spreading out towards the upper end. The dotplot provided a visual representation of individual data points, with each dot representing one observation. Clusters were observed around the values 4, 6, 12, 15, and 17, indicating higher frequencies of occurrence. An outlier was identified at the value 27, which was notably distant from the rest of the data points. The stem-and-leaf display allowed for a more detailed examination of the distribution, while the dotplot emphasized individual data points and their distribution. Both displays provided valuable insights into the data set, with the stem-and-leaf display offering a broader overview and the dotplot highlighting specific patterns and outliers.

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In this linear program, we aim to maximize the objective function ₁+₂+3 subject to a set of linear constraints. The 2-phase simplex algorithm is a method used to solve linear programming problems. It involves two phases:

the first phase finds an initial feasible solution, and the second phase optimizes the objective function. The specific details and steps of the 2-phase simplex algorithm need to be provided to fully solve the given linear program.

The given linear program involves maximizing the objective function ₁+₂+3 subject to the following constraints: a +3+4 -3, 2₁ +₂ +43 ≤ 2, and 20x₁+...To solve this linear program using the 2-phase simplex algorithm, we would follow a systematic approach. The algorithm has two phases:

Phase 1: Finding an initial feasible solution

In this phase, we introduce auxiliary variables and convert the problem into an equivalent minimization problem. We solve the modified problem using the simplex algorithm to find an initial feasible solution.

If the optimal value of the modified problem is zero, we proceed to phase 2. Otherwise, if it is non-zero, the original problem is infeasible.

Phase 2: Optimizing the objective function

In this phase, we drop the auxiliary variables introduced in phase 1 and solve the original problem using the simplex algorithm.

We iterate through the simplex algorithm until we reach an optimal solution, maximizing the objective function.

The 2-phase simplex algorithm involves several steps, such as selecting entering and leaving variables, pivot operations, and updating the basis. The specific steps and calculations depend on the given constraints and objective function coefficients.

Without the complete details of the constraints, objective function coefficients, and any additional information, it is not possible to provide a comprehensive solution using the 2-phase simplex algorithm for the given linear program. Additional information is required to determine the specific steps and perform the calculations necessary to solve the problem accurately.

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In other words, there are 24 different ways to get a full house of kings and fives when dealing 5 cards from a standard 52-card deck.

To calculate the number of hands with a full house of kings and fives, you need to consider the number of ways to choose 3 kings and 2 fives from a standard 52-card deck. There are 4 kings and 4 fives in the deck.

To choose 3 kings, use the combination formula: C(4,3) = 4! / (3!(4-3)!) = 4.
To choose 2 fives, use the combination formula: C(4,2) = 4! / (2!(4-2)!) = 6.

Now, multiply these results together to find the total number of hands with a full house of kings and fives: 4 * 6 = 24.

So, there are 24 possible hands with a full house of kings and fives when dealt from a standard 52-card deck.

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