A submarine began at sea level and descended toward the ocean floor at a rate of −0.015 km per minute. Its final depth was −0.3675 km. Estimate how long it took the submarine to reach its final depth by rounding the dividend and divisor to the nearest hundredth.



Estimate of the quotient:

Answer:

The very first one is decay and the rest are growth

Step-by-step explanation:

Im SO sorry if i got it wrong

I REALLY hope this helped

Best of luck

Answer:

36×18×18×27

Step-by-step explanation:

Assuming the picture is Figure A you would multiply value from figure A by 3 to get corresponding value for dilated figure.

So if figure A is

12 × 6 × 6 × 9

the dilated figure would be

36 × 18 × 18 × 27

Answer: 504. Multiple for : 18, 24 and 42. Factorize of the above numbers : 18 = 2 • 32 24 = 23 • 3. 42 = 2 • 3 • 7

Answer:

A.

it’s a because i just got it right on the test

Answer:

its A cause i got it right

Step-by-step explanation:

for the boys

The coefficient of determination (R²) for the fitted least squares line is 0.75.

To fit the least squares line through the given points and find the coefficient of determination (R²), we can follow these steps:

Let's perform these calculations:

Step 1: Calculate the mean values of x and y.

x' = (1 + 2 + 3) / 3 = 2

y' = (1 + 1 + 3) / 3 = 5/3 ≈ 1.6667

Step 2: Calculate the sums of squares: SSxx, SSyy, and SSxy.

SSxx = Σ((xi - x')²) = (1 - 2)² + (2 - 2)² + (3 - 2)² = 2

SSyy = Σ((yi - y')²) = (1 - 5/3)² + (1 - 5/3)² + (3 - 5/3)² = 8/3 ≈ 2.6667

SSxy = Σ((xi - x')(yi - y')) = (1 - 2)(1 - 5/3) + (2 - 2)(1 - 5/3) + (3 - 2)(3 - 5/3) = 4/3 ≈ 1.3333

Step 3: Calculate the slope (m) and y-intercept (b) of the least squares line.

m = SSxy / SSxx = 1.3333 / 2 = 2/3 ≈ 0.6667

b = y' - mx' = 5/3 - (2/3)(2) = 5/3 - 4/3 = 1/3 ≈ 0.3333

Therefore, the equation of the least squares line is y = 0.6667x + 0.3333.

Step 4: Calculate the predicted y-values (y_pred) using the least squares line equation.

For (1, 1):

y_pred = 0.6667 × 1 + 0.3333 = 0.6667 + 0.3333 = 1

For (2, 1):

y_pred = 0.6667 × 2 + 0.3333 = 1.3334 + 0.3333 ≈ 1.6667

For (3, 3):

y_pred = 0.6667 × 3 + 0.3333 = 2 + 0.3333 ≈ 2.3333

The predicted y-values are (1, 1), (2, 1.6667), and (3, 2.3333).

Step 5: Calculate the residual sum of squares (RSS) and the total sum of squares (TSS).

RSS = Σ((yi - y_pred)²) = (1 - 1)² + (1 - 1.6667)² + (3 - 2.3333)² ≈ 0.6667

TSS = SSyy = 8/3 ≈ 2.6667

Step 6: Calculate the coefficient of determination (R²) using the formula: R² = 1 - (RSS / TSS).

R² = 1 - (0.6667 / 2.6667) = 1 - 0.25 = 0.75

Therefore, the coefficient of determination (R²) for the fitted least squares line is 0.75.

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Answer: A

because It has 1 one 2 twos 3 threes 2 fours 1 five And 1 six

The meaurment of the ∠D= 40°, ∠A=140°, ∠B=130.

Given in the image we can see ∠C and ∠ D is an acute angle and the value of ∠C is 50° so ∠D must be 40° according to the image.

The sum of the angle on the same side of trapezoid is equal to 180°. so ∠A+D and ∠C+∠B= 180°. ∠A+40°=180°. after substracting the value ∠A will be 140° and by same method ∠B+50°=180°. we will get ∠B=130°.

Therefore ∠D= 40°, ∠A= 140°, ∠B= 130°.

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21400

The probability of detecting at most one defective component when all components of the three panels are examined is approximately 0.78136 or 78.14%.

To calculate the probability of detecting at most one defective component when all components of the three panels are examined, we need to consider the possible combinations of defective components in each panel.

Let's break down the problem step by step:

Panel 1:

- There are 5 components in Panel 1.

- The probability of a component being defective is 0.09.

- We want to calculate the probability of detecting at most one defective component.

The probability of detecting no defective components in Panel 1 is:

P(0 defective) = (1 - 0.09)^5 = 0.52201

The probability of detecting exactly one defective component in Panel 1 is:

P(1 defective) = 5 * 0.09 * (1 - 0.09)^4 = 0.40408

The probability of detecting at most one defective component in Panel 1 is:

P(at most 1 defective) = P(0 defective) + P(1 defective) = 0.52201 + 0.40408 = 0.92609

Panel 2 and Panel 3 have the same probabilities as Panel 1 since they also have 5 components and the same probability of a component being defective.

Now, to calculate the probability of detecting at most one defective component when examining all three panels, we multiply the probabilities of each panel:

P(at most 1 defective in all three panels) = P(at most 1 defective in Panel 1) * P(at most 1 defective in Panel 2) * P(at most 1 defective in Panel 3)

                                          = 0.92609 * 0.92609 * 0.92609

                                          = 0.78136

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Answer:

Hey I have the answer in a link

Look down For link!

Cmon half way there

jkjk

First part (tip amount)

$6.26

Second part (Total bill)

$41.04

Step-by-step explanation:

Well to find the percentage of a number, convert the percent into a decimal which is basically moving the decimal place 2 places to the left. THen you multiply that amount by the original number an din this case you would get 6.2604. You round that to the nearest penny (or hundreths) and you;d get $6.26. Thats the first part

The second part is simple, you add the tip with the total bill and you would get $41.04.

The y-intercept is -5 and as the x-values increase, the y-values also increase in this graph of the line. which is the correct answer would be options (A) and (D).

A graph can be defined as a pictorial representation or a diagram that represents data or values.

What is the equation of a line?

The general equation of a line is y = mx + c

where m is the slope of the line and c is the intercept.

A linear equation is defined as an equation in which the highest power of the variable is always one.

We have been given that function of the line as

y = 3x - 5

We need to determine the y-intercept.

The y-intercept is at x = 0, y = -5

And the x-intercept is at y = 0, x = 5/3

Here In this graph of the given function as the x-values increase, the y-values also increase.

Therefore, the correct answer would be options (A) and (D).

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Answer:

The 1st and 4th statements are true.

The compound will be completely used up in the reaction chamber after 60 minutes.

In the given chemical reaction, 20 units of a compound are injected into the reaction chamber every 30 minutes. Within that 30-minute period, 50% of the compound is used up in the chemical process. This means that after 30 minutes, half of the compound has reacted and only 10 units remain in the chamber.

After another 30 minutes, another 20 units are injected, making a total of 30 units in the chamber. However, within this 30-minute period, 50% of the compound is again used up. This results in 15 units being consumed, leaving only 15 units in the chamber.

Following this pattern, we can see that after each 30-minute interval, the number of units remaining in the chamber is halved. Starting with 20 units, after the first 30 minutes, we have 10 units, and after the second 30 minutes, we have 5 units.

Therefore, it can be inferred that after 60 minutes (two 30-minute intervals), the compound will be completely used up in the reaction chamber. No units of the compound will be left.

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Option (b) 2.8600 is the correct answer.

To find the number of rental trucks that a local U-Move moving truck rental company can expect to rent during a given week, we need to find the expected value of the probability distribution.

The expected value of a probability distribution is given by:

Expected Value = Sum of (Number of Rented Trucks × Probability)

Therefore, Expected Value = (0 × 0.23) + (1 × 0.18) + (4 × 0.27) + (5 × 0.32)

Expected Value = 0 + 0.18 + 1.08 + 1.6Expected Value = 2.86

Therefore, the company can expect to rent 2.86 rental trucks during a given week. Option (b) 2.8600 is the correct answer.

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(a) In step 3, the variable X will be entered into the model.

(b) The inclusion of all four variables in the final model does not guarantee their significance; further analysis is needed to determine their individual significance.

In step 3 of the forward selection procedure, the variable X will be entered into the model. This means that after step 2, the model includes variables X and X, and in step 3, the variable X is added.

No, the fact that all four independent variables are entered in the final model does not necessarily mean that all of them are significant. The forward selection procedure is a stepwise approach that adds variables to the model based on certain criteria, typically using a significance level or a criterion such as the increase in the adjusted R-squared.

However, the final model with all four variables entered does indicate that these variables have met the criteria for inclusion in the model based on the stepwise procedure. It suggests that each variable contributes to the prediction of the dependent variable Y, after accounting for the variables that were already in the model.

To determine the significance of each variable in the final model, further statistical analysis, such as hypothesis testing or examining the p-values of the coefficients, is required. These tests can assess the individual significance of each variable and help determine if they have a statistically significant relationship with the dependent variable.

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For the given first-order differential equation, we need to determine the largest interval on which a unique solution exists for each initial condition. The interval will depend on the specific initial condition and the behavior of the differential equation.

The first-order differential equation is given as:

t^et y' + y' + t^2 – 25yt - 99

To determine the largest interval on which a unique solution exists for each initial condition, we need to consider the behavior of the equation and any possible singularities or discontinuities.

For each initial condition, we can use standard techniques such as separation of variables or integrating factors to solve the differential equation and find the solution. The solution will depend on the initial condition and may have different behaviors based on the values of t and y.

It's important to note that the existence and uniqueness of solutions are generally guaranteed within a certain interval as long as the equation and initial condition satisfy certain conditions, such as Lipschitz continuity. However, without specific initial conditions, it is not possible to determine the exact intervals on which a unique solution exists.

Therefore, to determine the largest interval on which a unique solution exists for each initial condition, further analysis and specific initial conditions are required to assess the behavior of the equation and identify any constraints or limitations on the solution.

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The probability that the mean completion time of 4 projects falls between 16 and 19 months is approximately 0.6568 or 65.68%.

The Central Limit Theorem states that for a sufficiently large sample size, the distribution of sample means will approach a normal distribution regardless of the shape of the population distribution.

Specifically, if we have a random sample of n observations drawn from a population with mean μ and standard deviation σ, then the distribution of the sample means will have a mean equal to the population mean μ and a standard deviation equal to the population standard deviation σ divided by the square root of the sample size n.

In this case, the average time taken to complete a project in the real estate company is 18 months, with a standard deviation of 3 months.

Assuming that the project completion time approximately follows a normal distribution, we can use the Central Limit Theorem to find the probability that the mean completion time of 4 such projects falls between 16 and 19 months.

First, we need to calculate the standard deviation of the sample mean. Since we have 4 projects, the sample size is n = 4.

Therefore, the standard deviation of the sample mean is σ/√n = 3/√4 = 3/2 = 1.5 months.

Next, we can standardize the values of 16 and 19 months using the formula z = (x - μ) / (σ/√n), where x is the value, μ is the population mean, σ is the population standard deviation, and n is the sample size.

For 16 months: z1 = (16 - 18) / (1.5) = -2/1.5 = -1.33

For 19 months: z2 = (19 - 18) / (1.5) = 1/1.5 = 0.67

Using a standard normal distribution table, we can look up the probabilities corresponding to the z-scores -1.33 and 0.67.

The table provides the cumulative probabilities for values up to a certain z-score.

For -1.33, the cumulative probability is approximately 0.0918.

For 0.67, the cumulative probability is approximately 0.7486.

To find the probability between these two z-scores, we subtract the cumulative probability associated with -1.33 from the cumulative probability associated with 0.67:

P(-1.33 < Z < 0.67) = 0.7486 - 0.0918 = 0.6568

Therefore, the probability that the mean completion time of 4 projects falls between 16 and 19 months is approximately 0.6568 or 65.68%.

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Answer:

you can but dont touch anything inside i did when i was a kid and electrocuted myself.

Step-by-step explanation:

careful. i dont recomend using it though

Answer:

that happed to me i still use the outlet sometime but i wouldn't take any chances

Step-by-step explanation:

Answer:

28 and 12t

Step-by-step explanation:

4 x 7

4 x 3t

Answer:

28+12t

Step-by-step explanation:

Simplify the expression :)

btw you spelled please wrong

Answer:

a) 25/2 or 12.5

b) 78,125

c) 625

d) 30,517,578,125

Answer:

Step-by-step explanation:

Lets break the 2 boxes apart so you have 4*4*3 =48 and then you have 10*3*2 = 60

60 +48 = 108

108cm^3

Answer:

[tex]\theta=30.285^{\circ}[/tex]

Step-by-step explanation:

The range of a projectile is given by :

[tex]R=\dfrac{u^2\sin2\theta}{g}[/tex]

Put R = 20 m, u = 15 m/s and finding the value of angle of projection

So,

[tex]R=\dfrac{u^2\sin2\theta}{g}\\\\\sin2\theta=\dfrac{Rg}{u^2}\\\\\sin2\theta=\dfrac{20\times 9.8}{15^2}\\\\\sin2\theta=0.871\\\\2\theta=\sin^{-1}(0.871)\\\\2\theta=60.57\\\\\theta=30.285^{\circ}[/tex]

So, the required angle of projection is equal to [tex]30.285^{\circ}[/tex].

Answer:

Step-by-step explanation:

To be a function x can't repeat with a different y so in a every element of x is mapped to a different y so it is a function.

For choice B, -4 is paired with both 7 and 8 so it is not a function.

Choice C is a function since each x is paired with a different y.

Answer:

I will suppose that the actual question is:

Iodine-131 has a half-life of 8 days. How much would be left of an original g sample after x days?

Ok, a half-life means that after that time, the mass of the original sample is reduced to half.

So if we start it a quantity g of iodine-131, after 8 days, we will have g/2.

Also, remember that the decay is written as an exponential decay, then we will have:

A(x) = g*(r)^x

where:

A is the amount of the sample after x days, g is the initial amount of the material (such that A(0) = g) and r is the rate of decay.

We know that:

A(8) = g/2 = g*(r)^8

Now we can solve this for r:

g/2 = g*(r)^8

1/2 = r^8

(1/2)^(1/8) = r = 0.917

Then the amount of material after x days is given by:

A(x) = g*(0.917)^x

Answer:

I think the answer would be Y=-2X+5

Hope it helps you *^*

Answer:

A = 139.25 cm^2

Step-by-step explanation:

The composite shape is made up of a square with side 10 cm and a semicircle with diameter 10 cm. The area of the composite shape is the sum of the two areas. The diameter of the semicircle is the side of the square, and the radius of the circle is half of the diameter.

A = s^2 + (1/2)(pi)r^2

r = d/2 = s/2

A = (10 cm)^2 + (1/2)(3.14)(10 cm/2)^2

A = 100 cm^2 + (1/2)(3.14)(25 cm^2)

A = 139.25 cm^2

Answer:

y=2(x−4)²+3

Step-by-step explanation: