An element with mass 570 grams decays by 18% per minute. How much of the element is remaining after 13 minutes, to the nearest 10th of a gram?

Given equation:

Where T = temperature in Fahrenheit and

V = wind speed in miles per hour

Conversion formulas:

Question (b)

We are required to convert -2 degree Celsius to Fahrenheit

Using the conversion formula:

Answer: 28.4 F

u²= s²+t²

= 4.3²+4.9²

= 42.5

u= V42.5

= V170 /2

≈6.52

Answer:

6.519 cm

Step-by-step explanation:

Mmkay, so, you have to use the Pythagorean Theorem to find the actual length, which is a^2 + b^2 = c^2

a = 4.9 cm

b = 4.3 cm

4.9^2 is 24.01

4.3^2 is 18.49

Now add the two together:

24.01 + 18.49 = 42.5

Finally, we need to find the square root of 42.5

sqrt(42.5) = 6.519 cm

(rounding to nearest thousandth cuz it said so right by the answer box lol)

Hope this helped :D

Answer:

Step-by-step explanation:

To determine the number of ways to select 3 men and 2 women for a committee from a union chapter consisting of 6 men and 4 women, we can use the concept of combinations.

The number of ways to select 3 men from 6 men is given by the combination formula: C(6, 3) = 6! / (3! * (6 - 3)!) = 20.

Similarly, the number of ways to select 2 women from 4 women is given by the combination formula: C(4, 2) = 4! / (2! * (4 - 2)!) = 6.

To obtain the total number of ways to select 3 men and 2 women for the committee, we multiply these two combinations together: 20 * 6 = 120.

Therefore, there are 120 ways to select 3 men and 2 women for a committee from the given union chapter.

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Area =

\( \frac{pq}{2} \)

where p and q are it's diagonal

so according to the rule.

\( \frac{12.8 \times 8.4}{2} \)

\( \frac{107.52}{2} \)

\(53.76 \\ \\ \)

is the answer.

hope understands

Answer:

third statement. is right

Answer:

I'm think the answer is

A) since none of the sides are congruent, it is not a right triangle.

Answer:

Darius had more turkey.

Step-by-step explanation:

Brett only has 84 ounces of turkey, but when converting pounds to ounces, (16 ounces per 1 pound) Darius has 160 ounces of turkey.

Answer:

Darius

Step-by-step explanation:

D=10 lbs

1lb=16oz

Brett: 84/16=5.25lbs

Answer:

72

Step-by-step explanation:

The smallest number that is divisible by two given numbers is called the Least Common Multiple (LCM) of those numbers.

What's the smallest number that is a multiple of 8 and also a multiple of 18?

One way to find out is to start making lists of multiples:

Multiples of 8:  8, 16, 24, 32, 40, 48, 56, 64, 72, 80, 88, 96, and so on,

Multiples of 18:  18, 36, 54, 72, 90, 108, and so on.

This method can be a bit tedious, but in this case, it's clear that 72 is the LCM of 8 and 18.

Another method is to use the prime factorization of the two numbers.

Write 8 and 18 as the product of prime numbers; each number has a unique prime factorization.

8 = 2 x 2 x 2 = 2^3

18 = 2 x 3 x 3 = 2^1 x 3^2

To form the LCM, build a product of primes using the highest exponent in either of the two numbers.

LCM = 2^3 x 3^2 = 8 x 9 = 72.

Answer:

9.144meters

Step-by-step explanation:

Given data

We are expected to perform unit conversion in this problem

2.54cm is equivalent to 1 inch

100cm equal to 1 meters

360 inches to cm  will be

=360*2.54

= 914.4cm

914.4cm to meters will be

=914.4/100

=9.144meters

The probability that demand during this period will exceed 25 gallons depends on the distribution of demand.

To calculate the probability of a stockout during the replenishment lead-time, we need to consider the distribution of demand during this period. If the demand follows a known probability distribution, such as the normal distribution, we can use statistical methods to estimate the probability.

First, we need to determine the parameters of the distribution, such as the mean and standard deviation of the demand during the lead-time. Once we have these parameters, we can calculate the probability of demand exceeding 25 gallons using the cumulative distribution function (CDF) of the chosen distribution.

For example, if the demand during lead-time follows a normal distribution with a mean of 20 gallons and a standard deviation of 5 gallons, we can use the normal distribution table or statistical software to find the probability of demand exceeding 25 gallons.

Alternatively, if we have historical data on demand during lead-time, we can use that data to estimate the probability. We can calculate the proportion of instances where the demand exceeded 25 gallons and use this as an estimate of the probability of a stockout during the lead-time.

Overall, the probability of a stockout during replenishment lead-time depends on the distribution of demand and can be determined using statistical techniques or historical data.

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a. The value of h'(3) is 45.

b. The value of H'(1) is 36.

The complete table is in the attachment. h' and H are derivates from function h(x) and H(x). Using the Chain Rules to derivate the function.

Calculate the h'(x) function

h(x) = f(g(x))

h'(x) = d/dx {f(g(x))}

h'(x) = f' (g(x)) × g'(x)

h'(3) = f' (g(3)) × g'(3)

h'(3) = f'(2) × 9

h'(3) = 5 × 9

h'(3) = 45

Calculate the H'(x) function

H(x) = g(f(x))

H'(x) = d/dx {g(f(x))}

H'(x) = g' (f(x)) × f'(x)

H'(1) = g' (f(1)) × f'(1)

H'(1) = g'(3) × 4

H'(1) = 9 × 4

H'(1) = 36

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The length of the rectangle is 74 yard.

The perimeter of a rectangle is the sum of the lengths of all four sides of the rectangle. It is calculated by adding twice the length and twice the width. The formula to calculate the perimeter of a rectangle is

P = 2(L + W), where P is the perimeter, L is the length and W is the width of the rectangle. In simpler terms, it is the total distance around the rectangle.

The perimeter of rectangle is given by  2 ( l + b)

where l is length of rectangle and b is width of the rectangle

given that perimeter of rectangle is 274

so 2 (l+b)= 274

=>  l+b= 137   ---(i)

so l = 137 -b

=> l = 137 - 63

=> 74

so the lenth of rectangle is 74 yard.

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Step-by-step explanation:

f(3) = -3(3)-2

=-9-2

=-11

Answer:

The answer is C.

Step-by-step explanation:

Answer:

C

Solution

For a complex number written in the form a + bi, a is called the real part of the complex number and b is called the imaginary part. The sum of two complex numbers, a + bi and c + di, is found by adding real parts and imaginary parts, respectively, that is, (a + bi) + (c + di) = (a + c) + (b + d)i. Therefore, the sum of 2 + 3i and 4 + 8i is (2 + 4) + (3 + 8)i = 6 + 11i.

Choice A is incorrect and is the result of disregarding i and adding all parts of the two complex numbers together, 2 + 3 + 4 + 8 = 17. Choice B is incorrect and is the result of adding all parts of the two complex numbers together and multiplying the sum by i. Choice D is incorrect and is the result of multiplying the real parts and imaginary parts of the two complex numbers, (2)(4) = 8 and (3)(8) = 24, instead of adding those parts together.

Answer:

x = 3

Step-by-step explanation:

Trigonometric Ratios

The ratios of the sides of a right triangle are called trigonometric ratios. The longest side of a right triangle is called the hypotenuse and the other two sides are the legs.

The tangent ratio relates the opposite leg with the adjacent leg. Please note the given side is the opposite leg to 60° and x is the adjacent leg to 60°, thus we apply the tangent ratio:

\(\displaystyle \tan\theta=\frac{\text{opposite leg}}{\text{adjacent leg}}\)

\(\displaystyle \tan 60^\circ=\frac{3\sqrt{3}}{x}\)

Solving for x:

\(\displaystyle x=\frac{3\sqrt{3}}{\tan 60^\circ}\)

Since:

\(\tan 60^\circ=\sqrt{3}:\)

\(\displaystyle x=\frac{3\sqrt{3}}{\sqrt{3}}\)

Simplifying:

x = 3

Answer:

4.75

Step-by-step explanation:

19 goes into 4 4 times, so we are left with 4 3/4. 3/4 is 0.75, so we have 4.75 as our answer.

Answer:

4.75

Step-by-step explanation:

20/4 = 5

19 is very close to twenty, so assume it is 4.75

or use calculator and know it is 4.75

Statements 14, 16, 17, 21, 23, 25, 26, 28, and 29 are incorrect or misleading.

The autoregressive conditional heteroskedasticity (ARCH) process is not necessarily a martingale difference sequence (MDS).

The parameters in the GARCH process are typically estimated using maximum likelihood estimation (MLE) rather than ordinary least squares (OLS) estimation.

ARCH process is indeed used to model time-varying volatility.

Even if the model is dynamically misspecified, the OLS residuals can still have a zero population mean.

The trend-stationary process is not considered a stationary process.

The process {Xt} = 1, collected from a Brownian motion, is not necessarily a stationary process.

Spurious regression refers to the phenomenon where two unrelated, non-stationary time series appear to be strongly correlated.

The Generalized autoregressive conditional heteroskedasticity (GARCH) process is typically considered a stationary process.

There is no mention of the CARCH process in the given statements, and thus, its properties are not discussed.

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Answer:

13 and 14

Step-by-step explanation:

the square root of 182 is 13.49 which would lie between 13 and 14

We get: v - h + k - s = Ce^(-s/2) or y - x - (h - k) = Ce^(-(x-h-s)/2).

This is the general solution to the original differential equation, in terms of h, k, and C.

To solve the differential equation

dy/dx = (x-y-1)/(x+y+1)

       dy/dx = dv/ds + k

       x - y - 1 = h + s - v - k - 1 = s - v + (h - k - 1)

        x + y + 1 = h + s + v + k + 1 = s + v + (h + k + 1)

        dv/ds + k = [(h + s - v - k - 1) - (s - v + (h - k - 1))] / [(h + s + v + k + 1) -

        (s + v + (h + k + 1))]

       dv/ds + k = [(2h - 2k - 2)s - 2v] / [-2]

       or

       dv/ds = (v - h + k - s) / 2

        dv/ds = du/ds

        and the equation becomes:

        du/ds = -u/2

        v - h + k - s = Ce^(-s/2)

        or

        y - x - (h - k) = Ce^(-(x-h-s)/2)

This is the general solution to the original differential equation, in terms of h, k, and C.

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In statistics, p hat is used as an estimator of the population proportion (p) of a categorical variable. It is the sample proportion of the variable, which is calculated as the number of occurrences of a particular category in the sample divided by the total sample size.

The reason why p hat is used is that it provides an estimate of the unknown population proportion based on a representative sample. By using p hat, we can draw inferences about the population proportion with a certain level of confidence. This is important in hypothesis testing and confidence interval estimation, where we want to make statements about the population based on the information gathered from a sample.

Using p hat as an estimator of p is also beneficial because it has desirable statistical properties, such as being an unbiased estimator, having a sampling distribution that approaches normality, and having a known standard error.

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From the data points given, the linear equation is obtained as y = 6x - 3.

What is a linear equation?

A linear equation is one that has a degree of 1 as its maximum value. No variable in a linear equation, thus, has an exponent greater than 1. A linear equation's graph will always be a straight line.

The data points given are -

X = 1, 2, 3, 4, 5

f(x) = 3, 9, 15, 21, 27

The slope of the line is given as m.

The slope can be deduced using the formula -

(y2 - y1) / (x2 - x1)

m = (9 - 3) / (2 - 1)

m = 6/1

m = 6

The slope-intercept form of a equation is y = mx + b

Substitute the values of x, y and m in the equation -

3 = 6(1) + b

3 = 6 + b

b = 3 - 6

b = -3

So, the equation becomes -

y = 6x - 3

This equation forms a straight line in the graph.

Therefore, y = 6x - 3 is a linear equation.

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The evaluated probability for chances of  randomly selecting an employee who will  have a starting salary of at least $31,000 is 11.51%. Here, we have to depend on the principles of standard normal distribution to find the percentage of probability,


Let us take  z-score for a starting salary of $31,000 as

z = (31000 - 25000) / 5000
= 1.2

Now after using a standard normal distribution table , the probability of a z-score of 1.2 or greater is approximately 0.1151
Converting it into percentage
0.1151 x 100
= 11.51%
The evaluated probability for chances of  randomly selecting an employee who will  have a starting salary of at least $31,000 is 11.51%.

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Answer:

42000*1.04^(n-1)

Step-by-step explanation:

4% is equal to 0.04, a raise is 1+0.04=1.04

1.04 is now the number we are multiplying by to get a new yearly salary for Harmony.

42000*1.04^(n-1) since n is how many years after she has the job you have to raise it to the power and subtract one.

The momentum magnitude observed in frame s' is √(15m^2c^4).

In special relativity, the relationship between energy (E) and momentum (p) is given by the equation:

E^2 = (pc)^2 + (mc^2)^2

where m is the rest mass of the particle, c is the speed of light, and p is the momentum of the particle.

In frame of reference s, the energy of the electron is given as 4mc^2. Plugging this into the equation, we have:

(4mc^2)^2 = (pc)^2 + (mc^2)^2

Simplifying this equation, we get:

16m^2c^4 = p^2c^2 + m^2c^4

Canceling out the common terms, we have:

15m^2c^4 = p^2c^2

Taking the square root of both sides, we get:

pc = √(15m^2c^4)

The momentum magnitude observed in frame s', denoted as p', is related to the momentum in frame s (p) by the relativistic velocity addition formula:

p' = γ(p - βE/c)

where γ is the Lorentz factor and β is the velocity of frame s' relative to frame s. Since the electron is moving along the x-axis, the velocity β is zero, and the Lorentz factor γ is equal to 1.

Therefore, the momentum magnitude observed in frame s' is the same as the momentum magnitude in frame s:

p' = p

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Answer:

16 < 24 < 25

Step-by-step explanation:

√16 = 4

√25 = 5

\((\stackrel{x_1}{-5}~,~\stackrel{y_1}{7})\qquad (\stackrel{x_2}{-2}~,~\stackrel{y_2}{4}) \\\\\\ \stackrel{slope}{m}\implies \cfrac{\stackrel{rise} {\stackrel{y_2}{4}-\stackrel{y1}{7}}}{\underset{run} {\underset{x_2}{-2}-\underset{x_1}{(-5)}}} \implies \cfrac{4 -7}{-2 +5}\implies \cfrac{-3}{3}\implies \text{\LARGE -1}\)

a) The average estimated time for Bill to drive to work when he leaves on time at 6:30 with no red lights and no trains to wait for is approximately -19.9166 minutes. b) The estimated coefficients of REDS and TRAINS in the regression model are 1.3353 (REDS). c) The absolute value of the calculated t-value (-1.7733) is less than the critical t-value (1.9719), we fail to reject the null hypothesis.

a) To find the average estimated time in minutes for Bill to drive to work when he leaves on time at 6:30 and there are no red lights and no trains at the crossroad to wait, we substitute the values into the regression model:

TIME = -19.9166 + 0.3692(DEPART) + 1.3353(REDS) + 2.7548(TRAINS)

Given:

DEPART = 0 (as he leaves on time at 6:30)

REDS = 0 (no red lights)

TRAINS = 0 (no trains to wait for)

Substituting these values:

TIME = -19.9166 + 0.3692(0) + 1.3353(0) + 2.7548(0)

    = -19.9166

Therefore, the average estimated time for Bill to drive to work when he leaves on time at 6:30 with no red lights and no trains to wait for is approximately -19.9166 minutes. However, it's important to note that negative values in this context may not make practical sense, so we should interpret this as Bill arriving approximately 19.92 minutes early to work.

b) The estimated coefficients of REDS and TRAINS in the regression model are:

1.3353 (REDS)

2.7548 (TRAINS)

Interpreting the coefficients:

- The coefficient of REDS (1.3353) suggests that for each additional red light, the estimated time to drive to work increases by approximately 1.3353 minutes, holding all other factors constant.

- The coefficient of TRAINS (2.7548) suggests that for each additional train Bill has to wait for at the crossing, the estimated time to drive to work increases by approximately 2.7548 minutes, holding all other factors constant.

c) To test the hypothesis that each train delays Bill by 3 minutes, we can conduct a hypothesis test.

Null hypothesis (H0): The coefficient of TRAINS is equal to 3 minutes.

Alternative hypothesis (Ha): The coefficient of TRAINS is not equal to 3 minutes.

We can use the t-test to test this hypothesis. The t-value is calculated as:

t-value = (coefficient of TRAINS - hypothesized value) / standard error of coefficient of TRAINS

Given:

Coefficient of TRAINS = 2.7548

Hypothesized value = 3

Standard error of coefficient of TRAINS = 0.1390

t-value = (2.7548 - 3) / 0.1390

       = -0.2465 / 0.1390

       ≈ -1.7733

Using a significance level of 5% (or alpha = 0.05) and looking up the critical value for a two-tailed test, the critical t-value for 230 degrees of freedom is approximately ±1.9719.

Since the absolute value of the calculated t-value (-1.7733) is less than the critical t-value (1.9719), we fail to reject the null hypothesis. This means that there is not enough evidence to conclude that each train delays Bill by 3 minutes.

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Answer:

i dont see the graph need more info

Step-by-step explanation:

Answer:

The statement is misleading as it does not provide any context for the comparison. It does not clarify what the 74% more calories is being compared to or what amount of calories is being burned by using the product. Additionally, the advertisement does not provide any evidence to back up the claim.