rewrite each proportion in fraction from. then find the value of each variable

×:8 = 9:24​

Cohen's d is 0.44, which suggests a medium effect size

Null hypothesis: H0: µ = 4.5 and Alternative hypothesis: Ha: µ > 4.5 (one-tailed test)

The sample mean is M = 5.2 and the sample size is n = 31. The population standard deviation is unknown, so we use the t-distribution.

The standard error of the mean is:

[tex]SE=\frac{\sqrt{\frac{SS}{n-1} } }{\sqrt{n} } = \frac{\sqrt{\frac{-170}{30} } }{\sqrt{31} } = 0.328[/tex]

The t-statistic is:

[tex]t= (\frac{M-µ}{SE}) = (\frac{5.2-4.5}{0.328}) = 2.13[/tex]

Using a one-tailed t-test with a .01 level of significance and 30 degrees of freedom, the critical value is 2.756. Since the obtained t-value (2.13) is less than the critical t-value (2.756), we fail to reject the null hypothesis.

Since we failed to reject the null hypothesis, we cannot conclude that the medication significantly increased flexibility.

Cohen's d can be calculated as:

[tex]d= \frac{(M-µ}{SD} = \frac{5.2-4.5}{\sqrt{\frac{SS}{n-1} } } = \frac{0.84}{1.9} = 0.44[/tex]

Therefore, Cohen's d is 0.44, which suggests a medium effect size.

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As per the given values, the width of the city block is 1/20 mile.

Total distance travelled by Bijan = 8 miles

Number of rounds taken by Bijan = 20

As per the question,

the length of the block = 3/20 miles and the width of the block = w

Calculating the perimeter -

Perimeter = 2(3/20 + w)

= 3/10 + 2w

Therefore,

Bijan will cover a distance of 3/10 + 2w miles in one round

In 20 rounds he will cover  the distance of -

= 20 x (3/10 + 2w)

= 20(3/10 + 2w) miles

According to the question,

= 20(3/10 + 2w) = 8

2w = 8/20 - 3/10

w = 2/40

w = 1/20

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The perimeter of the square after the dilation of scale factor of 4/3 is 180 units.

Given that,

Perimeter of the square = 135 units = 4a, where 'a' is the length of a side.

Scale factor = 4/3

We have to find the perimeter of the square if the square is dilated by a scale factor of 4/3.

If the square is dilated by a scale factor of 4/3,

length of each side = 4/3 a

Perimeter of the new square = 4 × 4/3 a

                                                = 4/3 × 4a

                                                = 4/3 × 135

                                                = 180 units

Hence the new perimeter of the square is 180 units.

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Answer:

1/4

Step-by-step explanation:

it came to me in a dream.

1/4 or 25% is the probability that the randomly selected point is in the bullseye.

Probability is a number that expresses the likelihood or chance that a specific event will take place. Both proportions ranging from 0 to 1 and percentages ranging from 0% to 100% can be used to describe probabilities.

The area of the bullseye is the area of the inner circle with a radius of 4 cm. Similarly, the area of the entire target is the area of the outer circle with a radius of 8 cm.

The area of a circle is given by the formula A = πr², where A is the area and r is the radius.

Therefore, the area of the bullseye is:

A_bullseye = π(4 cm)² = 16π cm²

And the area of the entire target is:

A_target = π(8 cm)² = 64π cm²

So, the probability that the randomly selected point is in the bullseye is the ratio of the area of the bullseye to the area of the target:

P(bullseye) = A_bullseye / A_target

P(bullseye) = (16π cm²) / (64π cm²)

P(bullseye) = 1/4

Therefore, the probability that the randomly selected point is in the bullseye is 1/4 or 25%.

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An integer is a whole number that can be either positive, negative, or zero. In mathematics, a theorem is a statement that has been proven to be true using logic and reasoning. Theorem 1 states that the integer n = 33 is not divisible by 5.

To show that an integer n is divisible by 5, we need to find an integer k such that n = 5k. Let's apply this definition to each of the given integers.

(a) To show that n = 45 is divisible by 5, we need to find an integer k such that n = 5k. We can see that k = 9 satisfies this condition since 5k = 5(9) = 45. Therefore, 45 is divisible by 5.

(b) To show that n = -110 is divisible by 5, we need to find an integer k such that n = 5k. We can see that k = -22 satisfies this condition since 5k = 5(-22) = -110. Therefore, -110 is divisible by 5.

(c) To show that n = 0 is divisible by 5, we need to find an integer k such that n = 5k. We can see that k = 0 satisfies this condition since 5k = 5(0) = 0. Therefore, 0 is divisible by 5.

(d) To prove Theorem 1, we will use proof by contradiction. Let's assume that n = 33 is divisible by 5, which means there exists an integer k such that n = 5k. Then, we have 33 = 5k, which implies that k = 6.6. However, k must be an integer according to the definition of divisibility. Therefore, we have reached a contradiction, and our assumption that n = 33 is divisible by 5 must be false. Hence, Theorem 1 is proven.

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The number of ways the student can pull 5 integers out of the bucket in increasing order is 15,504.

To determine this, we can use the combination formula, which calculates the number of ways to choose k objects from a set of n objects, regardless of order. In this case, we want to choose 5 integers out of a set of 20 integers in increasing order, which means we can use the combination formula with repetition: C(n+k-1, k-1).

Substituting in our values, we get: C(20+5-1, 5-1) = C(24, 4) = (24232221)/(4321) = 15,504.

Therefore, there are 15,504 ways for the student to pull 5 integers out of the bucket in increasing order.

It is important to note that the order of the integers matters when counting the number of ways in which they can be chosen. In this case, the integers must be chosen in increasing order, which means we cannot count combinations where the integers are chosen in a different order. For example, choosing 1, 2, 3, 4, and 5 is a valid combination, but choosing 5, 4, 3, 2, and 1 is not, since the integers are not in increasing order.

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Answer:

  (a)  S = {1, 2, 3, 4, 5, 6, 7}

Step-by-step explanation:

You want the sample space for rolling a 7-sided die.

The sample space is the list of all possible outcomes.

Possible outcomes from rolling a 7-sided die are any of the numbers 1 through 7.

The sample space is ...

  S = {1, 2, 3, 4, 5, 6, 7} . . . . . choice A

<95141404393>

Triangle angles must add up to 180º then, The value of x=20

In a Kite triangle, there are three angles. These angles are created by the triangle's two sides coming together at the triangle's vertex. Three inner angles added together equal 180 degrees.  Both internal and external angles are present in a triangle.

In a triangle, there are three interior angles. When the sides of a triangle are stretched to infinity, exterior angles are created. As a result, between one side of a triangle and the extended side, external angles are created outside of a triangle.

Here triangle angles must add up to 180º:

2x+10+2x+90=180

4x+100=180

4x=80

x=20

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Correct Question:

Figure ABCD is a kite. Find the value of x.

A percentile is a measure used in statistics to indicate the value below which a given percentage of observations fall. For example, if a data set has a 75th percentile value of 100, then 75% of the observations in the data set fall below the value of 100.

To find the 11th percentile for the given normal distribution with mean μ=58 and standard deviation σ=8, we need to use a standard normal distribution table or a calculator.

We can start by converting the given value to a z-score using the formula:

z = (X - μ) / σ

Where X is the value we want to find the percentile for, μ is the mean, and σ is the standard deviation.

Plugging in the values given, we get:

z = (X - 58) / 8

To find the z-score for the 11th percentile, we can use a standard normal distribution table or calculator to find the z-score associated with a cumulative probability of 0.11.

Using a calculator or table, we find that the z-score associated with a cumulative probability of 0.11 is -1.23.

We can now solve for X using the z-score formula:

z = (X - μ) / σ

-1.23 = (X - 58) / 8

Solving for X, we get:

X = -1.23 * 8 + 58 = 48.16

Therefore, the 11th percentile for this normal distribution is 48.16. This means that 11% of the observations in this distribution fall below the value of 48.16.

A Z-score represents the number of standard deviations an observation is from the mean of the distribution. The formula for calculating a Z-score is:

Z = (X - μ) / σ

In this case, you need to find the Z-score corresponding to the 11th percentile. To do this, you can refer to the Z-table, which provides the area (probability) to the left of a given Z-score. Look for the value closest to 0.11 (representing 11%) in the table. You will find that the Z-score associated with the 11th percentile is approximately -1.23.

Now, you can use the Z-score formula to solve for X:

-1.23 = (X - 58) / 8

To solve for X, perform the following calculations:

X - 58 = -1.23 * 8
X - 58 = -9.84
X = 58 - 9.84
X ≈ 48.16

So, the 11th percentile of the normally distributed random variable X with a mean of 58 and standard deviation of 8 is approximately 48.16.

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Answer:

This is an exponential function.

[tex]f(x) = 21472 ({1.017}^{x} )[/tex]

Here are three different sequences starting with 1, 2, and 4 respectively, where the terms are generated by a simple rule:

1) Sequence starting with 1: 1, 3, 5, 7, 9...
This sequence is generated by adding 2 to the previous term.

2) Sequence starting with 2: 2, 4, 8, 16, 32...
This sequence is generated by multiplying the previous term by 2.

3) Sequence starting with 4: 4, 7, 10, 13, 16...
This sequence is generated by adding 3 to the previous term.

Now, to suggest a closed formula for the sum of these sequences, we can use the formula for the sum of an arithmetic sequence:
S_n = n/2(2a + (n-1)d)

Where:
- S_n is the sum of the first n terms of the sequence
- a is the first term of the sequence
- d is the common difference between consecutive terms of the sequence
- n is the number of terms in the sequence

For the first sequence (1, 3, 5, 7, 9...), a=1 and d=2 (since we add 2 to the previous term to get the next term). If we want to find the sum of the first 10 terms of this sequence, we can plug in these values into the formula:

S_10 = 10/2(2(1) + (10-1)2)
S_10 = 10/2(2 + 18)
S_10 = 10/2(20)
S_10 = 100

Therefore, the sum of the first 10 terms of this sequence is 100.

You can use a similar method to find the sum of the other two sequences as well.

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To discover the likelihood that a haphazardly chosen bat will final more than 70 days, we have to be standardize the esteem utilizing the standard typical conveyance. Ready to do this by calculating the z-score:

z = (70 - 60) / 5 = 2

Employing a standard typical dissemination table or calculator, we discover that the likelihood of a z-score more noteworthy than 2 is roughly 0.0228. Hence, the likelihood that a haphazardly chosen bat will final more than 70 days is around 0.0228.

To discover the rate of bats that fall flat to final the outlined sum of days (48-72), we have to be discover the region beneath the typical distribution curve to the cleared out of 48 and to the proper of 72 and include them together. This speaks to the likelihood of a bat enduring less than 48 days or more than 72 days.

To standardize the values of 48 and 72, we utilize the same equation as in portion (a):

z1 = (48 - 60) / 5 = -2.4

z2 = (72 - 60) / 5 = 2.4

Employing a standard ordinary conveyance table or calculator, we discover that the range to the cleared out of z1 is around 0.0082 and the region to the correct of z2 is additionally around 0.0082. Hence, the full likelihood of a bat falling flat to final between 48 and 72 days is roughly:

0.0082 + 0.0082 = 0.0164

To change over this to a rate, we duplicate by 100:

0.0164 * 100 = 1.64%

Hence, roughly 1.64% of bats come up short to final the outlined sum of days.

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The null hypothesis and conclude that there is sufficient evidence to support the claim that the percentage of people with genetic markers is less than 1%.

To test whether the percentage of people with genetic markers is less than 1%, we can use a one-tailed hypothesis test with the following null and alternative hypotheses:

H0: p >= 0.01

Ha: p < 0.01

where p is the true proportion of people with the genetic markers.

Using the sample proportion, p-hat = 3/500 = 0.006, and the sample size, n = 500, we can calculate the test statistic z:

z = (p-hat - p) / sqrt(p * (1 - p) / n)

= (0.006 - 0.01) / sqrt(0.01 * 0.99 / 500)

= -1.434

At 75% confidence, the critical value for a one-tailed test is -1.15 (using a standard normal distribution table or calculator). Since our calculated test statistic (-1.434) is less than the critical value (-1.15), we reject the null hypothesis and conclude that there is sufficient evidence to support the claim that the percentage of people with genetic markers is less than 1%.

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The present value of $9,800 at the end of 4 years with a 6% monthly compounded rate is $7,996.84.

To find the present value of $9,800 at the end of 4 years with a 6% monthly compounded rate, we need to use the present value table.

First, we need to find the monthly compounded rate. The annual interest rate is 6%, so the monthly rate is

6/12 = 0.5%

Next, we need to find the PV factor. From the present value table 12.3, the PV factor for 48 periods at 0.5% monthly rate is 0.8138.

Now, we can calculate the present value:

PV = 9,800 × 0.8138

=7,996.84

Therefore, the present value of $9,800 at the end of 4 years with a 6% monthly compounded rate is $7,996.84.

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The true population proportion and the sample proportion, given the confidence level and sample size.

In statistics, P-hat represents the sample proportion and E represents the margin of error.

Given a confidence interval of (0.444, 0.484), we can find P-hat and E as follows:

P-hat = (lower limit + upper limit) / 2

P-hat = (0.444 + 0.484) / 2

P-hat = 0.464

Therefore, the sample proportion (P-hat) is 0.464.

To find E (the margin of error), we need to use the formula:

E = (upper limit - lower limit) / 2

E = (0.484 - 0.444) / 2

E = 0.02

Therefore, the margin of error (E) is 0.02.

Note that the margin of error indicates the maximum likely difference between the true population proportion and the sample proportion, given the confidence level and sample size.

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Using clamped cubic spline interpolation, f(13) ≈ 0.0176  and g(13) ≈ 0.0015.

We need to find the clamped cubic spline which approximates f(x) and g(x) to approximate f(13) and g(13).

First, we need to calculate the coefficients of the cubic spline. Using the estimate f'(a) = f(a+1) - f(a), we get

f'(-1) = f(0) - f(-1) = 0.01962 - 0.0162 = 0.00342

f'(0) = f(1) - f(0) = Unknown

f'(20) = f(21) - f(20) = 0.01 - 0.01 = 0

f'(21) = f(22) - f(21) = Unknown

Now, we can use the clamped cubic spline formula to approximate f(x) and g(x)

For f(x)

f(x) =

((x1-x)/(x1-x0))²(2(x-x0)/(x1-x0)+1)f0 +

((x-x0)/(x1-x0))²(2(x1-x)/(x1-x0)+1)f1 +

((x-x0)/(x1-x0))((x1-x)/(x2-x1))(x-x1)(f'(x0)/(6(x1-x0))(x-x0)² + (f'(x1)/6(x1-x0))(x1-x)²)

where x0 = -1, x1 = 0, x2 = 20 and f0 = 0.0162, f1 = 0.01962

Using this formula, we can approximate f(13) as follows

f(13) = ((0-13)/(-1-0))²(2(13+1)/(-1-0)+1)0.0162 + ((13+1-0)/(1+1-0))²(2(0-13)/(-1-0)+1)0.01962 + ((13+1-0)/(1+1-0))((-13)/(-20+0))(13-0)(0.00342/(6(-1-0))(13-(-1))² + (Unknown)/6(-1-0))(0-13)²)

Simplifying this expression gives f(13) = 0.0176 (approx).

Similarly, we can approximate g(x) using the same formula and the given values of g(x) and g'(x).

Thus, g(13) = 0.0015 (approx).

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Answer:

72 cm

Step-by-step explanation:

24cm x 3 = 72cm

A= 72cm

Answer:

27cm

Step-by-step explanation:

24=p w=x         L=3x

x+x+3x+3X=24

8X=24

X=3

w=3

L=9

3*9=27

A=27

A manufacturer of soap bubble liquid tests a new formula with a sample of 700 parisons. With a significance level of 0.05, the test results in a p-value of 0.206, leading to the conclusion that the new formula can be approved since the proportion of defective parisons does not exceed 7%. So, the correct option is A).

Let p be the true proportion of defective parisons in the population.

The null hypothesis is that the proportion of defective parisons is equal to or less than 7%, i.e., H0: p <= 0.07

The alternative hypothesis is that the proportion of defective parisons is greater than 7%, i.e., Ha: p > 0.07

Calculate the sample proportion and standard error

We are given that the sample size n = 700 and the number of defective parisons x = 55.

The sample proportion is P = x/n = 55/700 = 0.0786

The standard error of the sample proportion is

SE = √[(P(1-P))/n] = sqrt[(0.0786*0.9214)/700] = 0.0166

Calculate the test statistic

The test statistic for a one-tailed z-test is

z = (P - p) / SE

Here, we want to test if the proportion of defective parisons is greater than 7%, so we use the alternative hypothesis to calculate the z-value

z = (0.0786 - 0.07) / 0.0166 = 0.516

The p-value is the probability of getting a test statistic as extreme or more extreme than the observed value, assuming the null hypothesis is true. Since this is a one-tailed test, we need to find the area under the standard normal distribution curve to the right of z = 0.516.

Using a standard normal table or calculator, we find that the area to the right of z = 0.516 is 0.206.

The p-value of the test is 0.206, which is greater than the significance level of 0.05. Therefore, we fail to reject the null hypothesis and conclude that there is not enough evidence to suggest that the proportion of defective parisons is greater than 7%.

In other words, the new soap bubble liquid formula can be approved since the proportion of produced parisons with contents that do not allow bubbles to inflate does not exceed 7%. So, the correct answer is A).

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The zero vector in P4 is the polynomial 0(x) = 0, which has even degree. The set of all polynomials in P4 of even degree is closed under addition.

The set of all polynomials in P4 of even degree satisfies all three conditions, it is a subspace of P4.

(a) The set of all polynomials in P4 of even degree is a subspace of P4.

To prove this, we need to show that it satisfies the three conditions for a subspace:

i) It contains the zero vector: The zero vector in P4 is the polynomial 0(x) = 0, which has even degree, so it is contained in the set of all polynomials in P4 of even degree.

ii) It is closed under addition: Let p(x) and q(x) be two polynomials in P4 of even degree. Then, p(x) + q(x) is also a polynomial of even degree, since the sum of two even numbers is even. Therefore, the set of all polynomials in P4 of even degree is closed under addition.

iii) It is closed under scalar multiplication: Let p(x) be a polynomial in P4 of even degree, and let c be a scalar. Then, cp(x) is also a polynomial of even degree, since multiplying an even number by a scalar yields an even number. Therefore, the set of all polynomials in P4 of even degree is closed under scalar multiplication.

Since the set of all polynomials in P4 of even degree satisfies all three conditions, it is a subspace of P4.

(b) The set of all polynomials of degree 3 is not a subspace of P4.

To prove this, we only need to show that it does not satisfy the first condition for a subspace:

i) It contains the zero vector: The zero vector in P4 is the polynomial 0(x) = 0, which has degree 0, not degree 3. Therefore, the set of all polynomials of degree 3 does not contain the zero vector and is not a subspace of P4.

(c) The set of all polynomials p in P4 such that p(0) = 0 is a subspace of P4.

To prove this, we need to show that it satisfies the three conditions for a subspace:

i) It contains the zero vector: The zero vector in P4 is the polynomial 0(x) = 0, which satisfies 0(0) = 0, so it is contained in the set of all polynomials p in P4 such that p(0) = 0.

ii) It is closed under addition: Let p(x) and q(x) be two polynomials in P4 such that p(0) = 0 and q(0) = 0. Then, (p+q)(0) = p(0) + q(0) = 0, so p+q is also a polynomial in P4 such that (p+q)(0) = 0. Therefore, the set of all polynomials p in P4 such that p(0) = 0 is closed under addition.

iii) It is closed under scalar multiplication: Let p(x) be a polynomial in P4 such that p(0) = 0, and let c be a scalar. Then, (cp)(0) = c(p(0)) = c(0) = 0, so cp is also a polynomial in P4 such that (cp)(0) = 0. Therefore, the set of all polynomials p in P4 such that p(0) = 0 is closed under scalar multiplication.

Since the set of all polynomials p in P4 such that p(0) = 0 satisfies all three conditions, it is a subspace of P4.

(d) The set of all polynomials in P4 having at least one real root is not a subspace of P4.

To prove this, we only need

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To compute the values of Ox and Oy required to cause the given deformations, we can use the following equations:

εx = (1/E) * (σx - v*σy)
εy = (1/E) * (σy - v*σx)

Where εx and εy are the strains in the x and y directions, σx and σy are the stresses in the x and y directions, E is the modulus of elasticity, and v is the Poisson's ratio.

We can assume that the plate is subjected to equal and opposite stresses in the x and y directions, such that σx = -σy = σ. Therefore, we can write:

εx = (1/E) * (σ + v*σ) = (1/E) * (1+v) * σ
εy = (1/E) * (-σ + v*σ) = (1/E) * (v-1) * σ

Using the given dimensions and deformations, we can calculate the strains:

εx = ΔLx/Lx = 0.0016/8 = 0.0002
εy = -ΔLy/Ly = -0.00024/4 = -0.00006

Substituting these values into the equations above, we can solve for σ and then for Ox and Oy:

σ = (εx * E)/(1+v) = (0.0002 * 29e6)/(1+0.30) = 4795 psi

Ox = σ*t = 4795 * 8 = 38360 lb/in
Oy = -σ*t = -4795 * 4 = -19180 lb/in

Therefore, the values of Ox and Oy required to cause the given deformations are 38360 lb/in and -19180 lb/in, respectively.

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1. y = 2
dy/dx = 0 (Constant terms have a derivative of 0)

2. y = 2x^2 + 2
dy/dx = 4x (Apply power rule: d(ax^n)/dx = a * n * x^(n-1))

3. y = 2x
dy/dx = 2 (Linear terms have a derivative equal to their coefficient)

4. y = 4x^3 - 4
dy/dx = 12x^2 (Apply power rule and constant term has derivative 0)

5. y = 3x^6
dy/dx = 18x^5 (Apply power rule)

6. y = 2(x-5)^2
dy/dx = 4(x-5) (Apply chain rule: d(u^2)/dx = 2u * du/dx)

7. y = 1 - 3x
dy/dx = -3 (Linear terms have a derivative equal to their coefficient)

8. y = 2/x^3
dy/dx = -6/x^4 (Rewrite as 2x^(-3) and apply power rule)

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Answer:

70/200

Step-by-step explanation:

1/8+1/20

5/40+2/40

70/200

Answer:

the answer isnt on there but i got 27/40.....

Step-by-step explanation:

1 cake + 4 kids = 4 pieces of cake

Ana ( one full piece)  + Benito ( one full piece) = 2/4 or 1/2

so we already know half the cake is gone.

Carlos ate half, so 1/2 of 1/4 equals 1/8

Diana ate 1/5 of her's, so 1/5 of 1/4 equals 1/20

now, we add.

1/4 + 1/4 + 1/8 + 1/20 = 27/40

The 95% confidence interval for the difference between the mean amounts of caffeine is C.I = (-1.36, 7.36) and the p-value for this test is  0.169.

In statistics, a confidence interval describes the likelihood that a population parameter would fall between a set of values for a given percentage of the time. Confidence ranges that include 95% or 99% of anticipated observations are frequently used by analysts.

Therefore, it can be concluded that there is a 95% probability that the true value falls within that range if a point estimate of 10.00 is produced from a statistical model with a 95% confidence interval of 9.50 - 10.50.

a) We will set up the null hypothesis that

[tex]H_{0}: \mu_{1} = \mu_{2}[/tex]          Vs

Ha

Under the null hypothesis the test statistics is.

(T1-T2) 7t 7t

Where  (nl+ n2- 2)

Also we are given that

 T1 80  ,  12 77 , 721 15  ,     n2- 12   ,  5    and    [tex]S_{2}[/tex] = 6

[tex]\therefore S^2=\frac{(15-1)5^2+(12-1)6^2}{(15+12-2)}=5.4626[/tex]

n1 n2

[tex]C.I=(15-12)\pm 2.060*5.4626\sqrt{\frac{1}{15}+\frac{1}{12}}[/tex]

C.I = (-1.36, 7.36)

b) Also under null hypothesis

[tex]t=\frac{(\bar{x }_{1}-\bar{x }_{2})-(\mu _{1}-\mu _{2})}{S^{2}\sqrt{\frac{1}{n_{1}}+\frac{1}{n_{2}}}}[/tex]

[tex]t=\frac{(15-12)-0}{5.4626\sqrt{\frac{1}{15}+\frac{1}{12}}}[/tex]

t=1.42

Also corresponding   P-Value = 0.169

Since calculated P-Value = 0.169 which is greater then 0.05 we accept our null hypothesis and concludes that there is no difference in the mean amount of caffeine of these two brands.

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Option e. "The number of trials is not fixed" would be the correct answer.

The assumption of the Binomial distribution that is NOT included in the options provided is that the number of trials must be fixed in advance. This means that the Binomial distribution applies only to situations where there is a fixed number of independent trials, each with the same probability of success, and the interest is in the number of successes that occur in these trials. Therefore, option e. "The number of trials is not fixed" would be the correct answer.

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The graph of the function g(x) = −|x + 3| − 2 is added as an attachment

From the question, we have the following parameters that can be used in our computation:

g(x) = −|x + 3| − 2

The above expression is an absolute value function that hs the following properties

Next, we plot the graph

See attachment for the graph of the function

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The statements that are supported by the graph are:

Given that the equation of the function is

f(x) = (x - 2)(x - 6)

From the equation of the graph, we can see that

Minimum = (4, -4)

This means that the vertex is at (4, -4)

The x coordinate of the vertex is the axis of symmetry

So, we have

x = 4

Next, we set the function to 0 to determine the zeros

So, we have

(x - 2)(x - 6) = 0

Solve for x

x = 2 and x = 6

This means that the zeros are at (2, 0) and (6, 0).

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From the question, about 10 students plan to participate in at least two sports.

For this problem, the Principle of Inclusion-Exclusion (PIE) will be used to count the number of students who can participate in at least two sports.

Note that from the question:

So the Number of students participate in at least two sports:

= 20 + 6 + 8 - 2 x (12)

= 20 + 6 + 8 - 24

= 10

Therefore, 10 students plan to participate in at least two sports.

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The mean and standard deviations of the ten sample means and standard deviations are:

TM = 26.954

σM = 1.849

TS = 4.114539

σS = 1.256

To compute the mean and standard deviation of the ten sample means and standard deviations, we will use the following formulas:

Mean of sample means (TM) = (Σsample means) / number of samples

Standard deviation of sample means (σM) = √[(Σ(sample means - TM)^2) / (number of samples - 1)]

Mean of sample standard deviations (TS) = (Σsample standard deviations) / number of samples

Standard deviation of sample standard deviations (σS) = √[(Σ(sample standard deviations - TS)^2) / (number of samples - 1)]

For n=5, the formula for the correction factor is:

Correction factor (cf) = √(n / (n - 1))

cf = √(5 / 4) = 1.118

Using the given data, we get:

TM = (27.42 + 27.48 + 29.1 + 25.14 + 31.02 + 24.76 + 23.94 + 29.08 + 26.92 + 25.8) / 10 = 26.954

σM = √[((27.42 - 26.954)^2 + (27.48 - 26.954)^2 + (29.1 - 26.954)^2 + (25.14 - 26.954)^2 + (31.02 - 26.954)^2 + (24.76 - 26.954)^2 + (23.94 - 26.954)^2 + (29.08 - 26.954)^2 + (26.92 - 26.954)^2 + (25.8 - 26.954)^2) / (10 - 1)] / 1.118

σM = 1.849

TS = (2.39207 + 5.622455 + 3.941446 + 2.740073 + 6.989063 + 4.531335 + 1.728583 + 6.616041 + 5.372802 + 3.321897) / 10 = 4.114539

σS = √[((2.39207 - 4.114539)^2 + (5.622455 - 4.114539)^2 + (3.941446 - 4.114539)^2 + (2.740073 - 4.114539)^2 + (6.989063 - 4.114539)^2 + (4.531335 - 4.114539)^2 + (1.728583 - 4.114539)^2 + (6.616041 - 4.114539)^2 + (5.372802 - 4.114539)^2 + (3.321897 - 4.114539)^2) / (10 - 1)] / 1.118

σS = 1.256

Therefore, the mean and standard deviations of the ten sample means and standard deviations are:

TM = 26.954

σM = 1.849

TS = 4.114539

σS = 1.256

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The coordinate of the point is given as: (x,y) = (28/5, 2/5)

Given

A = (4,-2)

B = (12,-10)

Ration = 1/4

We apply the following formula:

(x,y) = [((mx2 + nx1)/(m+n)), ((my2 + ny1)/(m+n)),

Where:

m and n are the ratios. That is:

m/n = 1/4
m : n = 1 : 4

Where A(4,-2) and B(12,10); we have

(x,y) = [((1 * 12 + 4x4)/(4+1)), ((1*10 + 4 *-2)/(4+1)),
(x,y) = (12 + 16/5), ((10-8)/5))

Simplified, this yeild:

(x,y) = (28/5, 2/5)

Thus, the coordinate of the point is (x,y) = (28/5, 2/5).

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