A quantitative data set has mean 25 and standard deviation 2. At least what percentage of the observations lie between 19 and 31 ​?

Answer:

12 is the right answer

Step-by-step explanation:

The comparison between A and B is as follows:A < B.

We are given that:120 % of A is equal to 150 => (120/100)A = 150

Divide both sides by 120/100: A = 150 × 100/120 = 125

And, 105 % of B is equal to 165 => (105/100)B = 165

Divide both sides by 105/100: B = 165 × 100/105 = 157.14

Therefore, A = 125 and B = 157.14

Compare A and B:It can be seen that B is greater than A. Therefore, B > A. Hence, the comparison between A and B is as follows:A < B.

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Using the Poisson distribution, there is a 0.8335 = 83.35% probability that 2 or fewer will be stolen.

In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by:

\(P(X = x) = \frac{e^{-\mu}\mu^{x}}{(x)!}\)

The parameters are:

The probability that a rental car will be stolen is 0.0004, hence, for 3500 cars, the mean is:

\(\mu = 3500 \times 0.0004 = 1.4\)

The probability that 2 or fewer cars will be stolen is:

\(P(X \leq 2) = P(X = 0) + P(X = 1) + P(X = 2)\)

In which:

\(P(X = x) = \frac{e^{-\mu}\mu^{x}}{(x)!}\)

\(P(X = 0) = \frac{e^{-1.4}1.4^{0}}{(0)!} = 0.2466\)

\(P(X = 1) = \frac{e^{-1.4}1.4^{1}}{(1)!} = 0.3452\)

\(P(X = 2) = \frac{e^{-1.4}1.4^{2}}{(2)!} = 0.2417\)

Then:

\(P(X \leq 2) = P(X = 0) + P(X = 1) + P(X = 2) = 0.2466 + 0.3452 + 0.2417 = 0.8335\)

0.8335 = 83.35% probability that 2 or fewer will be stolen.

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Answer:

there is 21

Step-by-step explanation:

you have to times six by three and then add three to that and there is your answer

The range of f(x) = 2x -3 include the following: {-7, -3, -2, 7}.

In Mathematics and Geometry, a domain is the set of all real numbers for which a particular function is defined.

When the domain is -2, the range of this function can be calculated as follows;

f(x) = 2x - 3

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

f(-2) = -7.

When the domain is 0, the range of this function can be calculated as follows;

f(x) = 2x - 3

f(0) = 2(0) - 3

f(0) = -3.

When the domain is 1/2, the range of this function can be calculated as follows;

f(x) = 2x - 3

f(1/2) = 2(1/2) - 3

f(1/2) = -2.

When the domain is 5, the range of this function can be calculated as follows;

f(x) = 2x - 3

f(5) = 2(5) - 3

f(5) = 7.

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Answer:

3,470,000 pls mark me branilest

Answer:

The answer is 3,470,000

=》The answer is 3.

Steps are in the attachment.

______

Hope it helps :)) ⚜

Answer:

The answer is 3

Step-by-step explanation:

By using PEMDAS, calculate the parenthesis first.

10-(5-(4-(8-2))

10-(5-(4-6)

10-(5-(-2)

10-7

= 3

d!

john (y) is (2.5) times as big as his brother sam (x)

hope this helps

The given expression can be simplified using trigonometric identities. By using the identity cos(a-b) = cos(a)cos(b) + sin(a)sin(b), we get:

cos(pi/4-x) = cos(pi/4)cos(x) + sin(pi/4)sin(x)

Substituting the given values of cos(x) and sin(x), we get:

cos(pi/4-x) = (1/sqrt(2))(-1/2) + (1/sqrt(2))(sqrt(3)/2)

Simplifying this expression, we get:

cos(pi/4-x) = -sqrt(2)/4 + sqrt(6)/4

The given expression involves the cosine of the difference between two angles. By using the identity cos(a-b) = cos(a)cos(b) + sin(a)sin(b), we can simplify the expression in terms of the cosine and sine of the individual angles. We are given the value of cos(x) and we can use the identity sin^2(x) + cos^2(x) = 1 to find the value of sin(x). Once we have the values of sin(x) and cos(x), we can substitute them in the above identity to get the simplified expression.

In this particular problem, we are given the value of cos(x) and the fact that x is in the second quadrant, which implies that sin(x) is positive. Using these values, we can simplify the expression to get the final answer. It is important to note that the answer is requested in exact form as a fraction, and not as a decimal approximation.

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The complex exponential Fourier series of a signal can be determined by computing the coefficients A₀ and Aₙ.

For (i), the complex exponential Fourier series is given by:

X(ω) = A₀ + ∑[Ancos(nωt + φn) ], where

A₀ = 1/2

Aₙ = (1/2)[cos(2nπ/8) + cos(2nπ/8 + π/2)]

For (ii), the complex exponential Fourier series is given by:

X(ω) = A₀ + ∑[Ancos(nωt + φn) ], where

A₀ = 1

Aₙ = (2/2)[sin(nπ/3) + 3cos(nπ/3 + π/3)]

In conclusion, the complex exponential Fourier series of a signal can be determined by computing the coefficients A₀ and Aₙ. This technique can be used to analyze any periodic signal or system and is invaluable in signal processing, communications, and control engineering.

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Answer:

16 i think

Step-by-step explanation:

(a) The sample size needed is approximately 424.

(b) The nearest whole number, the required sample size is 1068.

To determine the sample size needed for estimating the difference in proportions with a desired margin of error and confidence level, we can use the formula:

n = (Z^2 * p * q) / E^2

Where:

n is the required sample size

Z is the Z-score corresponding to the desired confidence level (in this case, 90% confidence corresponds to a Z-score of approximately 1.645)

p is the estimated proportion of the population

q is 1 - p

E is the desired margin of error

(a) Using the estimates of 22.6% male and 19.9% female, we can take the average proportion (p) as (0.226 + 0.199) / 2 = 0.2125. Therefore, p = 0.2125 and q = 1 - 0.2125 = 0.7875. Assuming a desired margin of error (E) of 0.02, and substituting these values into the formula, we get:

n = (1.645^2 * 0.2125 * 0.7875) / 0.02^2 ≈ 424

Rounding up to the nearest whole number, the sample size needed is approximately 424.

(b) If no prior estimates are used, we typically assume a conservative estimate of p = q = 0.5 since it provides the maximum required sample size. Using the same margin of error (E = 0.02) and calculating the sample size:

n = (1.645^2) * (0.5^2) / (0.02^2)

n ≈ 1067.89

Rounding up to the nearest whole number, the required sample size is 1068.

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Answer:

7.12

Step-by-step explanation:

5 * COS(29) = 4.373

4.373 + 2.75 = 7.123

If two samples are selected from the same population, the two samples have exactly the same t statistics if the samples are same size and have the same variance and mean

The t-statistic is the ratio of the departure of the estimated value of a parameter from its hypothesized value to its standard error.

Variance is the expectation of the squared deviation of a random variable from its population mean or sample mean.

Mean is the average of the given numbers and is calculated by dividing the sum of given numbers by the total number of numbers

Hence, If two samples are selected from the same population, the two samples have exactly the same t statistics if the samples are same size and have the same variance and mean

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Answer:

Less

Step-by-step explanation:

Answer:

1.9

Step-by-step explanation:

7.6/4= 1.9

1.9*1= 1.9

ans is 1.9 pints

These equations describe the rate of change of the probabilities of each state over time. We could solve them using various methods, such as matrix exponentiation or numerical simulation.

The Kolmogorov backward equations describe the probability of transitioning from one state to another in a stochastic process. In this case, we are interested in the probability of the two machines being in a certain state, given the mean lifetime and the rate at which the repairman can service them.

Let X1 and X2 represent the state of machines 1 and 2, respectively. We can define the states as follows:

- X1 = 0: Machine 1 is working
- X1 = 1: Machine 1 is broken
- X2 = 0: Machine 2 is working
- X2 = 1: Machine 2 is broken

The probability of transitioning from one state to another depends on the current state and the rates at which the machines fail and the repairman can fix them. Specifically, the rates of transition are:

- λ: The rate at which each machine fails (exponentially distributed with mean 1/λ)
- μ: The rate at which the repairman can fix a broken machine (exponentially distributed with rate μ)

Using these rates, we can set up the Kolmogorov backward equations as follows:

dP(X1=0,X2=0)/dt = -λP(X1=0,X2=0) + μ[P(X1=1,X2=0) + P(X1=0,X2=1)]

dP(X1=1,X2=0)/dt = λP(X1=0,X2=0) - (λ+μ)P(X1=1,X2=0) + μP(X1=0,X2=0)

dP(X1=0,X2=1)/dt = λP(X1=0,X2=0) - (λ+μ)P(X1=0,X2=1) + μP(X1=1,X2=0)

dP(X1=1,X2=1)/dt = (λ+μ)P(X1=1,X2=0) + (λ+μ)P(X1=0,X2=1) - 2μP(X1=1,X2=1)

These equations describe the rate of change of the probabilities of each state over time. We could solve them using various methods, such as matrix exponentiation or numerical simulation.

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Answer:

Step-by-step explanation:

Answer:

x = ±10 i.e. -10 or +10

Step-by-step explanation:

Given that,

x² = 100

Solution:

Let's take square root to the RHS.

Solving √100 , we can obtain,

Further

Hence, the value of x can be -10,or +10.

The inflection points of the given function are at x = 0 only. The answer is D.

To find the inflection points of the given function, we need to find the second derivative of the function and set it equal to zero.

y = 5x^4 - x^5

y' = 20x^3 - 5x^4

y'' = 60x^2 - 20x^3

Setting y'' = 0, we get:

60x^2 - 20x^3 = 0

20x^2(3 - x) = 0

x = 0 or x = 3

Now, we need to determine whether these values of x correspond to inflection points. To do this, we can examine the sign of the second derivative in the intervals around each value of x.

For x < 0, y'' is positive (since both terms are positive), so there is a local minimum at x = -3.

For 0 < x < 3, y'' is negative (since 60x^2 < 20x^3), so there is a point of inflection at x = 0.

For x > 3, y'' is positive (since both terms are positive), so there is a local minimum at x = 3.

Therefore, the inflection points of the given function are at x = 0 only. The answer is D.

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Answer:

115.75 as a decimal and fraction 463/4000

Step-by-step explanation:

True: Regression calculations are typically done on a computer because the calculations can be quite tedious and lengthy.

A regression is a statistical technique that relates a dependent variable to one or more independent (explanatory) variables. A regression model is able to show whether changes observed in the dependent variable are associated with changes in one or more of the explanatory variables

True. Regression calculations involve complex mathematical computations and analyzing large datasets, which can be time-consuming and prone to errors if done manually. Using a computer with specialized software can automate the process, making it faster, more accurate, and efficient.

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Answer:

$29.70

Step-by-step explanation:

1. First, we have to find how much 10% of 33 is!

2. Okay, now that we know 3.3 is 10% of 33, we need to subtract 3.3 from 33 to get the amount Jen will pay for the dress.

Therefore, Jen will pay $29.70 for the dress.

Answer:

$29.70

Step-by-step explanation:

So, 10% of 33, which= 3.3

33- 3.3= 29.70

Answer:

m=18/3

Step-by-step explanation:

m=-7-11/-6-(-1)

Wilbur's flight took about 43.7 seconds.

Let x be the rate of Orville in feet per second and 2x be the rate of Wilbur in feet per second. Let t be the time it took for Orville to complete the flight and t - 6 be the time it took for Wilbur to complete the flight.

We know that the distance traveled by both brothers is the same, which we can express with the equation:

distance = rate × time

For Orville:

distance = x * t

For Wilbur:

distance = 2x * (t - 6)

Since the distance is the same for both brothers, we can set the two equations equal to each other:

x * t = 2x * (t - 6)

Expanding and simplifying the right-hand side:

xt = 2xt - 12x

12x = xt

x = t/12

So, Orville's rate is x = t/12 feet per second.

Substituting this into one of the equations for distance, we can solve for t:

distance = x * t

852 = (t/12) * t

852 = t² / 12

t² = 12 * 852

t² = 10224

t ≈ 101.1 seconds (rounded to the nearest tenth)

So, Orville's flight took about 101.1 seconds.

Now we can use the equation for Wilbur's distance to find his rate:

distance = 2x * (t - 6)

852 = 2(2x) * (101.1 - 6)

852 = 4x * 95.1

x ≈ 5.64 feet per second (rounded to the nearest hundredth)

So, Orville's rate is about 5.64 feet per second, and Wilbur's rate is twice that or about 11.28 feet per second.

To find Wilbur's time, we can use the equation for distance again:

distance = 2x * (t - 6)

852 = 2(11.28) * (t - 6)

852 = 22.56t - 135.36

22.56t = 987.36

t ≈ 43.7 seconds (rounded to the nearest tenth)

So, Wilbur's flight took about 43.7 seconds.

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