determine whether the following equations are second-order linear differential equations.(a)y'' = −3x(y')2

Answer:

Step-by-step explanation:

455

Answer:

36

Step-by-step explanation:

There are 30 red marbles and the ratio of black to yellow is 4/5, so 4/5=orange/green=orange/30.

30 is 6 times 5, so black=6 times 4=24. There are 24 black marbles.

Total of black and yellow=24+30=54.

40% of the marbles are green so 60% are black/yellow. Also 60% is 54 marbles.

60% is 60/100=3/5 so 3/5 of the total is 54 marbles, therefore 1/5 is 54/3=18 and 2/5 is the number of red marbles=2 times 18=36 red marbles.

to be honest i can't think of anything original for the visual thing, but i think the pi chart from the person above me would work well

Answer: 36

Step-by-step explanation: 2/5 of marbles are red, and 4:5 ratio is multiplied by 6 because there are 30 yellow marbles and so 3/5 of the marbles are 54 and 2/5 are 36. For visual model draw a pi chart with 40% red, 33% yellow, and 27% black.

Answer: I think B is the answer.

Step-by-step explanation:

Answer:not sure but

Step-by-step explanation: you can multiply each box, so lets say we have 20 times 7cm you multiply that and you get your answer, so put that a side

and once you multiply in each box add the numbers up and that should get your answer and make sure to add the "cm" at the end

Answer:

function 2

Step-by-step explanation:

i looked at the table, and since t (which is the x-coordinate in this case) was 0, that means that 5.25 is the y-coordinate and is greater than 5 in the first equation.

The second quartile for the numbers 231, 423, 521, 139, 347, 400, 345 is 347. The median value is the second quartile

. So, when the numbers are arranged in ascending order, 347 is in the middle.

The following measures of variability is dependent on every value in a Set of data:

Standard deviation is the measure of variability that is dependent on every value in a Set of data.

Standard deviation is a measure that is used to quantify the amount of variation or dispersion of a set of data values.

Among these statistics, the Interquartile range is unaffected by outliers. The IQR is the distance between the first quartile (Q1) and the third quartile (Q3), which represents the middle 50% of the data.

The interquartile range (IQR) is unaffected by outliers because it only uses the values of the data points located at the 25th and 75th percentile of the data set to measure variability.

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Answer:

13.93

Step-by-step explanation:

see attached for explanation

Answer:

Answer is Option A

Step-by-step explanation:

the things people do for points smh :/

The rectangular equation which represents the parametric equations; x = t^(¹/2) and y = 4t is; y = 4x2, for x ≥ 0.

From the task content, it follows that the parametric equations given are;

Hence, it follows that; t = x² and y= 4t

Ultimately, upon substitution of x² for t; the resulting rectangular equation is; y = 4t².

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Answer:

1. 3

2. 1

Step-by-step explanation:

Answer:

1.3. now mark brainlieet plsssssssssss like you said you would

Answer:

C

Step-by-step explanation:

(c + 1)(c+1) = c² + c + c + 1 = c² + 2c + 1

Answer: d. y= -2 2x+y= -3

Step-by-step explanation: Hope this help :D

Answer

672 meters²

Step-by-step explanation:

2×(18×12 + 18×4 + 12×4) = 672 meters²

hope this helps :))

The calculated p-value is 0.016, which is significant. However, it does not strongly suggest that the population standard deviation (sigma) is less than 12.1.

In hypothesis testing, the p-value is used to determine the strength of evidence against the null hypothesis. In this case, the null hypothesis is that the population standard deviation (sigma) is equal to 12.1. The alternative hypothesis would be that sigma is less than 12.1.

A p-value of 0.016 means that if the null hypothesis were true (sigma = 12.1), there is a 1.6% chance of obtaining a sample with a standard deviation of 10.394 or lower. Typically, a p-value below a chosen significance level (e.g., 0.05) is considered statistically significant. However, in this case, the p-value of 0.016 is still relatively close to the significance level, indicating a moderate level of evidence against the null hypothesis.

Therefore, based on the given information, we can conclude that the p-value of 0.016 is significant, but it does not strongly suggest that the population standard deviation is less than 12.1. Strong evidence would require a smaller p-value, further away from the significance level, to support the alternative hypothesis.

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a) The height of the ball after 2 seconds is 7.6 metres.

b) The given function is f(x) = (x - 2).

a) The inverse function of f(x) is g(x) = x + 2.

b) A farmer has 600 metres of fencing to enclose a rectangular area and divide it into 14 sections.

a) The total area enclosed can be expressed as a function of the length of the rectangle x as A(x) = 300x - x².

b) The domain of the area function is (0, 300) and its range is [0, ∞).

a) h(t) = -4.9t² + 13.1t + 1 When the time, t = 2 seconds;

the height of the ball, h(t) =h(2) = -4.9(2)² + 13.1(2) + 1= -4.9(4) + 26.2 + 1= -19.6 + 27.2= 7.6 metres

Therefore, the height of the ball after 2 seconds is 7.6 metres.

b) h(t) = -4.9t² + 13.1t + 1When the height of the ball, h(t) = 0.5 metres; we can write the equation as:

0.5 = -4.9t² + 13.1t + 1

Rearranging,4.9t² - 13.1t + 0.5 - 1 = 0i.e. 4.9t² - 13.1t - 0.5 = 0

Solving using the quadratic formula, t = [-(-13.1) ± √(13.1² - 4(4.9)(-0.5))]/(2(4.9))= [13.1 ± √(171.61)]/9.8≈ 0.138 and t ≈ 2.23

Thus, the ball reaches a height of 0.5 metres twice, at approximately 0.14 seconds and 2.23 seconds.

The given function is f(x) = (x - 2).

a) We can find the inverse of a function by interchanging x and y and then solving for y.

Here, f(x) = (x - 2) so we can write it as x = (y - 2)

Interchanging x and y: x = (y - 2)

Solving for y, we get: y = x + 2

Hence, the inverse function of f(x) is g(x) = x + 2.

b) Domain and range of the function and its inverse

The domain of f(x) is all real numbers. (i.e. -∞ < x < ∞)

The range of f(x) is all real numbers. (i.e. -∞ < f(x) < ∞)

The domain of g(x) is all real numbers. (i.e. -∞ < x < ∞)

The range of g(x) is all real numbers. (i.e. -∞ < g(x) < ∞)

The steps of the solution are given below:

Therefore, the inverse function of f(x) is g(x) = x + 2.

The domain of f(x) is all real numbers, and its range is all real numbers.

Similarly, the domain and range of g(x) is all real numbers.

A farmer has 600 metres of fencing to enclose a rectangular area and divide it into 14 sections.

Let x be the length and y be the width of the rectangle.

a) Write an equation to express the total area enclosed as a function of the length x.

Perimeter of the rectangle = Total fencing = 600 metres2(x + y) = 600i.e. x + y = 300

Solving for y, we get:

y = 300 - x

Thus, the area of the rectangle is A(x) = xy = x(300 - x) = 300x - x²

Therefore, the total area enclosed can be expressed as a function of the length of the rectangle x as A(x) = 300x - x².

b) Determine the domain and range of the area function.

The domain of the function is the set of all possible values of x, which in this case is the set of all positive real numbers. (i.e. 0 < x < 300)

The range of the function is the set of all possible values of A(x), which in this case is the set of all non-negative real numbers. (i.e. 0 ≤ A(x) < ∞)

Therefore, the domain of the area function is (0, 300) and its range is [0, ∞).

The steps of the solution are given below:

Therefore, the total area enclosed can be expressed as a function of the length of the rectangle x as A(x) = 300x - x². The domain of the area function is (0, 300) and its range is [0, ∞).

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Answer:

sorry but your question can't be solved any further because it doesn't have any like termsand you can't add40x and4y together it's impossible unless you multiply

Answer: y-11 = -3(x+2)

The given statement, "predictive modelling and lifetime value modelling are the same" is false. What is Predictive Modeling?

Predictive modeling is a technique for forecasting the probability of a certain event taking place in the future. It entails using current and past data to forecast the future events. In predictive modeling, you use known outcomes of historical data to determine whether specific patterns are likely to recur in the future. What is Lifetime Value Modeling? Lifetime Value Modeling is a method of forecasting the long-term earnings and profit of a business. It's a strategy for calculating the cumulative amount of profit generated by a customer over the life of their relationship with a company. Lifetime Value Modeling is used to decide the most effective ways to engage with consumers, such as personalized deals or special promotions, to maximize their lifetime value to the company by encouraging them to purchase more often and spend more during each transaction.

Predictive modeling and lifetime value modeling are distinct concepts that serve different purposes. Predictive modeling is used to forecast the future occurrence of specific events, whereas lifetime value modeling is used to calculate the long-term value of a customer to a company. So, the given statement is false.

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Answer:

y= -x+1

y=4x_14

solution

-x+1=4x-14

-x-4x= -14-1

-5x= -15

-5x/-5= -15/-5

x=3

while y=4x-14

y=4(3)-14

y=12-14

y= -2

Answer:

yes.

................................

You need help with anything??

a) Sample distribution follows normal distribution with mean( μ) = 1.10 kg,

and standard deviation σ = 0.081

b) Sample distribution follows normal distribution with mean( μ)  = 1.10 kg,

and standard deviation σ = 0.04

d) The percentage of all samples of three men that have mean brain weights within 0.1 kg of the population mean brain weight of 1.10 kg is 79.77%.

e) The percentage of all samples of twelve men that have mean brain weights within 0.1 kg of the population mean brain weight of 1.10 kg is 99.3%.

2) 68.26% of men in country A have brain weights between 1.48 kg and 1.72 kg.

Solution:

Population standard deviation is the measure of how spread out the population data is. It measures the difference of the individual items from the mean. A standard deviation is a statistic that measures the dispersion of a dataset relative to its mean. It is calculated as the square root of variance by determining the variation between each data point relative to the mean.

1)

Given mean = 1.10 kg, standard deviation = 0.14 kg

a) To find the sampling distribution of the sample mean for samples of size 3.

Standard error of mean = σ/√n

= 0.14/√3

=0.081

Sample distribution follows normal distribution with mean( μ) = 1.10 kg,

and standard deviation σ = 0.081

b) To find the sampling distribution of the sample mean for samples of size 12.

Standard error of mean = σ/√n

= 0.14/√12

= 0.04

Sample distribution follows normal distribution with mean( μ)  = 1.10 kg,

and

standard deviation σ = 0.04

d) Determine the percentage of all samples of three men that have mean brain weights within 0.1 kg of the population mean brain weight of 1.10 kg.

Sample distribution follows normal distribution with mean( μ)  = 1.10 kg,

and

standard deviation σ = 0.081

Z = (x - μ) / σZ

= (1.1 + 0.1 - 1.1) / 0.081

= 1.23

Z = (1.1 - 0.1 - 1.1) / 0.081

= -1.23

P ( -1.23 < Z < 1.23) = 0.7977

The percentage of all samples of three men that have mean brain weights within 0.1 kg of the population mean brain weight of 1.10 kg is 79.77%.

e) Determine the percentage of all samples of twelve men that have mean brain weights within 0.1 kg of the population mean brain weight of 1.10 kg.

Sample distribution follows normal distribution with mean( μ )= 1.10 kg,

and

standard deviation σ = 0.04

Z = (x - μ) / σ

Z = (1.1 + 0.1 - 1.1) / 0.04

= 2.5

Z = (1.1 - 0.1 - 1.1) / 0.04 = -2.5

P ( -2.5 < Z < 2.5) = 0.993

The percentage of all samples of twelve men that have mean brain weights within 0.1 kg of the population mean brain weight of 1.10 kg is 99.3%.

2)

Given mean = 1.60 kg,

standard deviation = 0.12 kg

68.26% of men in country A have brain weights between μ - σ and μ + σ

68.26% of men in country A have brain weights between 1.48 kg and 1.72 kg.

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Given a fixed vector b and a vector x is a solution to Qx = b, it is required to prove that every solution to the equation is in the form x = xh + xp where xh is a particular solution to Qx = b and xp is a solution to the equation Qxp = 0.

Let xh be a particular solution to Qx = b, so that Qxh = b.

Now consider the homogeneous equation Qx = 0.

This is an m × n system of homogeneous linear equations in the n unknowns x1, x2, ..., xn, whose coefficient matrix is Q.

Since xh is a solution to the equation Qx = b, it follows that the equation Q(x - xh) = Qx - Qxh = b - b = 0.

This means that x - xh is a solution to the homogeneous equation Qx = 0.

Now any solution to Qx = b is of the form x = xh + xp, where xp is any solution to the homogeneous equation Qxp = 0.

Thus, every solution to the equation is in the form x = xh + xp, as required.

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Answer:

the answer is A. 6 1/3 feet

Step-by-step explanation:

There are 12 inches in a foot. 12 x6=72 r of 4

there are 12 inches in a foot 12÷4=3. 1/3 of a foot

6 + 1/3= 6 1/3

The pair (6, 3) in R, (6, 4) in R, and (C, 3) in R couldn't be matched with any pair in S, so they are not included in the composition relation RS.

To find the composition relation RS of R with S, we need to combine the ordered pairs in R and S in a way that the second element of each pair in R matches the first element of the pair in S.

Let's perform the composition:

R = {(2, 1), (6, 3), (6, 4), (C, 3)}

S = {(1, y), (1, 2), (2, w), (3, z)}

To form RS, we match the second element of each pair in R with the first element of each pair in S:

(2, 1) in R matches with (1, y) in S, so we combine them to form (2, y).

(2, 1) in R matches with (1, 2) in S, so we combine them to form (2, 2).

(6, 3) in R doesn't match with any pair in S.

(6, 4) in R doesn't match with any pair in S.

(C, 3) in R doesn't match with any pair in S.

Therefore, the composition relation RS is: RS = {(2, y), (2, 2)}

The pair (6, 3) in R, (6, 4) in R, and (C, 3) in R couldn't be matched with any pair in S, so they are not included in the composition relation RS.

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Answer:

Step-by-step explanation:

You need to use vertex form of a quadratic to solve this.

Consider the vertex to be [tex](h,k)[/tex]

Another way of representing a quadratic is in "vertex form":

[tex]f(x) = a(x-h)^2+k[/tex]

Now all you have to do is solve for a.  You know that the vertex is [tex](0,2)[/tex] and you have know the point of [tex](1,8)[/tex].  Now, all you have to do is plug in these values and solve for a.

[tex]8 = a(1-0)^2+2\\8=a(1)^2+2\\8=a+2\\a=6[/tex]

Now you know the equation is [tex]f(x) = 6(x-0)^2+2[/tex] , but you need it in quadratic form.  All you have to do is solve is distribute the 6:

[tex]6x^2+2[/tex]

You get:

a = 6

b = 0

c = 2

Please mark this as brainliest if it satisfies your question

Answer:

A. 223 were not playing volleyball

B. 12 books on each shelf with 3 books left over..

C. 12.15$ a day

D. 12.15 miles per day.

Step-by-step explanation:

A. Subtract 20 from 243.

B. Since books cant be divided into fractions, you take 243 divided by 20, which is 12.15. However, we have to say 12 with 3 leftover because books isn't money, a distance measure, etc. and cannot be cut into pieces.

C. 243 / 20 is 12.15

D. 243 / 20 is 12.15

Answer:

Both solutions are correct

Step-by-step explanation:

Given

Expression:

[tex]14x - 2x +3 = 3(5x + 9)[/tex]

See attachment for Clare and Lins' solution

Required

Determine if they are correct or not

[tex]14x - 2x +3 = 3(5x + 9)[/tex]

Open bracket

[tex]14x - 2x + 3 = 15x + 27[/tex]

Collect like terms

[tex]14x - 2x -15x = -3 + 27[/tex]

[tex]-3x = 24[/tex]

Divide by -3

[tex]x = \frac{24}{-3}[/tex]

[tex]x = -8[/tex]

Both solutions are correct

Using a one-sample t-test, we cannot conclude that the mean time to spoil is significantly different when bananas are hung from the ceiling.

3.9, 4.9, 5.1, 3.9, 4, 5.8, 7, 5, 3.6, 4.3, 4.4, 6, 6.8, 6.7, 7.1, 5.2

We can calculate the sample mean and sample standard deviation:

Sample mean (x) = (3.9 + 4.9 + 5.1 + 3.9 + 4 + 5.8 + 7 + 5 + 3.6 + 4.3 + 4.4 + 6 + 6.8 + 6.7 + 7.1 + 5.2) / 16 = 5.3

Sample standard deviation (s) = √[(Σ(xi - x)²) / (n - 1)] = √[(Σ( - 5.3)²) / 15] ≈ 1.273

We will perform a one-sample t-test using the null hypothesis (H0) that the mean time to spoil is equal to 6.2 days, and the alternative hypothesis (H1) that the mean time to spoil is less than 6.2 days.

The test statistic is calculated as:

t = (x - μ) / (s / √n)

Where μ is the hypothesized mean (6.2), s is the sample standard deviation (1.273), and n is the sample size (16).

Plugging in the values:

t = (5.3 - 6.2) / (1.273 / √16) ≈ -0.887

To determine the critical t-value for a one-tailed test at α = 0.05 level of significance with 15 degrees of freedom (n - 1), we refer to the t-distribution table or use statistical software. The critical t-value is approximately -1.753.

Since the test statistic (-0.887) does not exceed the critical t-value (-1.753), we fail to reject the null hypothesis. This means that there is not enough evidence to conclude that the mean time to spoil is less when bananas are hung from the ceiling compared to the average time of 6.2 days, at the α = 0.05 level of significance.

Therefore, we cannot conclude that the mean time to spoil is significantly different when bananas are hung from the ceiling.

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Answer:

n/a

Step-by-step explanation:

how does it feel

Answer:

a part of the population that represents the entire population

Step-by-step explanation:

Answer:

I think it is the second option

I hope it helps you  

Answer:

y=6x+7

Step-by-step explanation: