(5x - 4)²
plsss givee the solutionnn.​

a. the mean of the sampling distribution of the sample proportion is 0.46

b. the standard deviation of the sampling distribution of the sample proportion is 0.0498

c. he sample size is 100 in this case, we can assume that the sampling distribution of p^ is approximately normal.

d. the probability of having a z-score greater than 2.811 is equal to 1 - 0.9974 = 0.0026, or 0.26%.

e. the standard deviation of the sampling distribution by a factor is 0.0704

a. The mean of the sampling distribution of the sample proportion, denoted as μp^, is equal to the population proportion, which in this case is 46%.

μp^ = p = 0.46

the mean of the sampling distribution of the sample proportion is 0.46

b. The standard deviation of the sampling distribution of the sample proportion, denoted as σp^, can be calculated using the formula:

σp^ = √((p * (1 - p)) / n)

Where p is the population proportion (0.46) and n is the sample size (100).

σp^ = √((0.46 * (1 - 0.46)) / 100) = 0.0498

the standard deviation of the sampling distribution of the sample proportion is 0.0498

c. The sampling distribution of p^ is approximately normal due to the Central Limit Theorem (CLT). According to the CLT, when the sample size is sufficiently large (typically n ≥ 30), the sampling distribution of the sample proportion will be approximately normal, regardless of the shape of the population distribution. Since the sample size is 100 in this case, we can assume that the sampling distribution of p^ is approximately normal.

d. To find the probability that more than 60 households will own VCRs, we need to calculate the probability of getting a sample proportion greater than 0.6. We can standardize this value using the z-score formula:

z = (x - μp^) / σp^

Substituting the values, we have:

z = (0.6 - 0.46) / 0.0498 = 2.811

the probability of having a z-score greater than 2.811 is equal to 1 - 0.9974 = 0.0026, or 0.26%.

e. If the sample size is decreased from 100 to 50, the standard deviation of the sampling distribution of the sample proportion (σp^) would be multiplied by a factor of √(2), which is approximately 1.414. Therefore, the standard deviation would become:

New σp^ = σp^ * √(2) = 0.0498 * 1.414 = 0.0704

the standard deviation of the sampling distribution by a factor is 0.0704

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The mean of the sampling distribution of the sample proportion is 0.46. The standard deviation of the sampling distribution of the sample proportion is approximately 0.0498. The sampling distribution of p^ is approximately normal when the sample size is large enough. The probability that more than 60 households will own VCRs is approximately 0.0024. If the sample size is decreased from 100 to 50, the standard deviation of the sampling distribution would be multiplied by a factor of approximately 1.4142.

In statistics, a sampling distribution is the probability distribution of a given statistic based on a random sample. The sampling distribution of the sample proportion, denoted as p^, is the distribution of the proportions obtained from all possible samples of the same size taken from a population.

The mean of the sampling distribution of the sample proportion is equal to the population proportion. In this case, the population proportion is 46% or 0.46. Therefore, the mean of the sampling distribution of the sample proportion, denoted as μp^, is also 0.46.

The standard deviation of the sampling distribution of the sample proportion, denoted as σp^, is determined by the population proportion and the sample size. It can be calculated using the formula:

σp^ = √((p * (1 - p)) / n)

where p is the population proportion and n is the sample size. In this case, p = 0.46 and n = 100. Plugging in these values, we get:

σp^ = √((0.46 * (1 - 0.46)) / 100) = √((0.46 * 0.54) / 100) = √(0.2484 / 100) = √0.002484 = 0.0498

The sampling distribution of p^ is approximately normal when the sample size is large enough due to the Central Limit Theorem. This theorem states that the sampling distribution of a sample mean or proportion becomes approximately normal as the sample size increases, regardless of the shape of the population distribution. In this case, the sample size is 100, which is considered large enough for the sampling distribution of p^ to be approximately normal.

To calculate the probability that more than 60 households will own VCRs, we need to use the sampling distribution of p^ and the z-score. The z-score measures the number of standard deviations an observation is from the mean. In this case, we want to find the probability that p^ is greater than 0.6.

First, we need to standardize the value of 0.6 using the formula:

z = (x - μp^) / σp^

where x is the value we want to standardize, μp^ is the mean of the sampling distribution of p^, and σp^ is the standard deviation of the sampling distribution of p^.

Plugging in the values, we get:

z = (0.6 - 0.46) / 0.0498 = 2.8096

Next, we need to find the probability that z is greater than 2.8096 using a standard normal distribution table or a calculator. The probability is approximately 0.0024.

If the sample size is decreased from 100 to 50, the standard deviation of the sampling distribution of the sample proportion would be multiplied by a factor of:

√(n1 / n2)

where n1 is the initial sample size (100) and n2 is the final sample size (50). Plugging in the values, we get:

√(100 / 50) = √2 = 1.4142

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                     "

Answer:

B, D and E

Step-by-step explanation:

The first triangle inequality theorem states:

the lengths of any two sides of a triangle must add up to more than the length of the third side.

So as long as the sum of the two shortest is greater than the longest side a triangle is possible

А

7 + 9 < 17  NO

B

2 + 7 > 8   YES

C

1 + 3 < 5   NO

D

3 + 5 > 6   YES

E

12 + 12 > 13  YES

F

3 + 8 = 11    NO

The graphs of the two equations in a system with one solution must intersect at one point and have different slopes and different y-intercepts.

If a system of two linear equations has one solution, it means that the two equations represent two lines that intersect at a single point. Therefore, the correct statement is "They intersect at one point."

When two lines intersect at one point, it implies that they have different slopes and different y-intercepts. The fact that they intersect at only one point ensures that they are not parallel lines, which would never intersect. Also, they cannot be the same line, as they would intersect at infinitely many points.

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Answer: 36

Step-by-step explanation:

6 x 4 = 24 (top box)

(6 x 4) divided by 2 = 12 (bottom triangle)

There are a total (4) 2⁸ = 256 possible methods to join 8 bits or 8 binary digits.

A binary code uses a two-symbol system to represent text, computer processor instructions, or any other data.

The binary number system's "0" and "1" are frequently employed as the two symbols in this system.

Each character, command, etc. is given a set of binary digits, often referred to as bits, by the binary code.

A binary string of eight bits (also known as a byte) can, for instance, represent any of 256 possible values and hence a vast range of distinct things.

8 bits, or 8 binary digits, can be combined in 2⁸=256 different ways.

Some of these combinations are shown in the following table.

(The number in parentheses is the equivalent in decimal form.)

Therefore, there are a total (4) 2⁸ = 256 possible methods to join 8 bits or 8 binary digits.

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A six-sided dice is rolled twice then the probability that the larger of the two rolls was equal to 3, is 0.1389.

A six-sided dice is rolled twice.

Then the possibility of getting numbers in one rolled = 6

The possibility of getting numbers in second rolled = 6

So the possibility of getting numbers in both rolled = 6 × 6

The possibility of getting numbers in both rolled = 36

Let A be the event that have the larger of the two rolls was equal to 3.

So the possible outcomes;

A = {(1,3), (2,3), (3,3), (3,2), (3,1)}

So total number of possible outcomes to getting larger of the two rolls was equal to 3 = 5

Then the probability that the larger of the two rolls was equal to 3 = Number of possible outcome/Total of possible outcome

The probability that the larger of the two rolls was equal to 3 = 5/36

The probability that the larger of the two rolls was equal to 3 = 0.1389

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Answer: -0.5.

Step-by-step explanation:

The constant of variation k for the direct variation is given by:-

\(k= \dfrac{f(x_2)}{x_2}=\dfrac{f(x_1)}{x_1}\)

The given table:

x  f( x )

0   0

2   -1

4    -2

7   -3.5

Then,

\(k=\dfrac{-1}{2}=\dfrac{-2}{4}=\dfrac{7}{-3.5}=-0.5\)

Hence, the constant of variation k for the direct variation is -0.5.

A) Row and column totals were calculated, and a Chi-square analysis was performed to test for association at the 0.05 significance level.

B) Unusual deviations from expected values were examined.

C) Poisson difference tests were conducted within each age group to identify interesting differences across the years. A false discovery rate (FDR) approach was used to evaluate the results at a Q value of 0.1.

D) The issue of independent P values in approach B was discussed.

A) To assess the association between year and age, row and column totals were calculated for the given data, and a Chi-square analysis was performed at a significance level of 0.05. This analysis helps determine if there is a significant relationship between the variables.

B) Unusual deviations from expected values can be identified by comparing the observed frequencies with the expected frequencies. Significant deviations may indicate potential associations or factors influencing the outcomes.

C) Poisson difference tests were conducted within each age group (0-5, 6-59, and >60) to examine differences across the years. A total of nine tests were performed, and the false discovery rate (FDR) approach was used to evaluate the results. FDR controls the expected proportion of false discoveries among all significant results.

D) The issue with independent P values in approach B refers to the fact that when multiple tests are performed simultaneously, the probability of obtaining at least one false-positive result increases. This can lead to inflated overall Type I error rates. To address this issue, the FDR approach is used, which considers the proportion of false discoveries among all significant results, providing a more stringent control over the overall false discovery rate.

In summary, the analysis involves calculating row and column totals, conducting Chi-square analysis for association, examining deviations from expected values, performing Poisson difference tests within age groups, and addressing the issue of dependent P values through the FDR approach.

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The cosine of angle J is given as follows:

\(\cos{J} = \frac{14\sqrt{2}}{49}\)

The three trigonometric ratios are the sine, the cosine and the tangent of an angle, and they are obtained according to the rules presented as follows:

For the angle J in this problem, we have that:

Hence the cosine of angle J is given as follows:

\(\cos{J} = \frac{4}{\sqrt{98}} \times \frac{\sqrt{98}}{\sqrt{98}}\)

\(\cos{J} = \frac{4\sqrt{98}}{98}\)

\(\cos{J} = \frac{2\sqrt{98}}{49}\)

As 98 = 2 x 49, we have that \(\sqrt{98} = \sqrt{49 \times 2} = 7\sqrt{2}\), hence:

\(\cos{J} = \frac{14\sqrt{2}}{49}\)

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Answer:

43, 52, 61

(adding nine each time)

Answer:

\(-9x-10y\)

Step-by-step explanation:

\(10yi^2-9x \\ \\ =10y(-1)-9x \\ \\ =-9x-10y\)

Answer:

the answers got deleted because they didn't give an explanation. so, the explanation is: you multiply 5,280 by 6 to get 31,680 ft

Answer:

31680 feet

Step-by-step explanation:

You multiply 5280 nd  and you get 31680...

Answer:

While it was true that the cotton gin reduced the labor of removing seeds, it did not reduce the need for slaves to grow and pick the cotton. In fact, the opposite occurred. Cotton growing became so profitable for the planters that it greatly increased their demand for both land and slave labor.

Step-by-step explanation:

Pretty sure this isnt math tho

The probability of catching a defect is approximately 99.9768%.

To calculate the probability of catching a defect, we need to consider the complement of the event, which is the probability of not catching a defect in any of the four inspections.

The probability of not catching a defect in inspection 1 is 1 - 0.9 = 0.1 (since the complement of catching a defect is not catching a defect). Similarly, the probabilities of not catching a defect in inspections 2, 3, and 4 are 1 - 0.8 = 0.2, 1 - 0.12 = 0.88, and 1 - 0.95 = 0.05, respectively.

Since the inspections are independent events, we can multiply these probabilities together to find the probability of not catching a defect in all four inspections: 0.1 × 0.2 × 0.88 × 0.05 = 0.0088.

Therefore, the probability of catching a defect is 1 - 0.0088 = 0.9912, or approximately 99.9768%.

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Answer:

4x

Step-by-step explanation:

P = S + S + S

P = x + x + 3 + 2x - 3

P = 4x

The density of the lobster population in the area labeled NBHK is C) 9.02 lobsters/mi^2.

Population density refers to the number of people living in a given area, usually expressed as the number of individuals per square mile or kilometer.

To calculate population density, you can divide the total population of a given area by its land area. For example, if a city has a population of 1 million people and an area of 100 square miles, its population density would be 10,000 people per square mile.

The figure has two trapezoid and the areas are 306 and 756. Total area will be 1062 miles².

Lobster population will be:

= 6817 / 756

= 9

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Answer:

56

Step-by-step explanation:

7⁶ = ~117,649

(2/7)⁵ = ~0.0019

2² = 4

~117,649 x ~0.0019 = 224.

224 / 4 = 56

There is only one way to pick a president from 1000 number of professors, and that is to select one of the professors.

1. There are 1000 number of professors to choose from

2. The board of trustees can only pick one of the 1000 professors

3. Therefore, there is only one way to pick a president - select one of the professors.

The board of trustees can pick a president from the 1000 professors by considering their qualifications, experience, and other criteria. They can also take into account the opinion of the faculty and students of the college. If applicable, the board may also take into account any applicable legal requirements. Finally, they can make their selection by majority vote.

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The hypothesis regarding the convincing evidence that the average number of colleges students apply to is accepted because  p-value is more than the chosen significance level.

The null hypothesis will be that the average number of colleges students apply to is equal to or less than 8. The alternative hypothesis would be that the average number of colleges students apply to is greater than 8.

We can apply a one-sample t-test to test this hypothesis. By doing so we can evaluate the t-statistic
t = (x'- μ) / (s / √n)
here
x' = sample mean,
μ = hypothesized population mean,
s = sample standard deviation,
n = sample size
(x'- μ) / (s / √n)
Staging values
(9.7 - 8) /(7) /√206)
=( 0.3) /( 7/ 14.35)
= (0.3) /(0.4)
= 0.75


Now, the p-value associated with this t-statistic using a t-distribution . The p-value in this case is  greater than the chosen significance level (usually 0.05), we will accept  the null hypothesis.

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Value of r is different for every series

let

a , b , c , d ..... be geometric series then

r = b/a or d/c and so on

where r is common ratio

Answer:

58to20meters a pear of a day

Step-by-step explanation:

1hu2ji

The 30th term a30 of the sequence is -1445

The definition of the function is given as

arithmetic sequence of 1,-4,-9,-14

The above definitions imply that we simply subtract 5 from the previous term to get the current term

Using the above as a guide,

so, we have the following representation

First term, a = 1

Common difference, d = 5

An arithmetic sequence is represented as

a(n) = a + (n - 1)d

For the 30th term, we have

a(30) = a + 29d

So, we have

a(30) = 1 + 29 * -5

Evaluate

a(30) = -144

Hence, the value of a30 is -144

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The statement "The height of the probability density function f(x) of the uniform distribution defined on the interval [a, b] is 1/(a-b)" is False.

In a uniform distribution, the probability density function (PDF) is constant within the interval [a, b]. The height of the PDF represents the density of the probability distribution at any given point within the interval. Since the PDF is constant, the height remains the same throughout the interval.

To determine the height of the PDF, we need to consider the interval length. In a uniform distribution defined on the interval [a, b], the height of the PDF is 1/(b - a) for the PDF to integrate to 1 over the entire interval. This means that the total area under the PDF curve is equal to 1, representing the total probability within the interval [a, b].

Therefore, the correct statement is that the height of the probability density function f(x) of the uniform distribution defined on the interval [a, b] is not 1/(a - b), but rather it is a constant value necessary for the PDF to integrate to 1 over the interval, i.e., 1/(b - a).

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Answer:

affixwritersgmaicom

APP 447520635495

Parallel lines are defined as lines that do not intersect or meet at any point in a plane. They are always parallel and equidistant from one another.

What is answer parallel line?

In geometry, parallel lines can be defined as two lines in the same plane that are at equal distance from each other and never meet. They can be both horizontal and vertical.

Parallel lines are two lines in the same plane that are equal distance apart and never intersect.

Real-world parallel line examples include railroad tracks, sidewalk edges, street markings, zebra crossings, the surface of pineapple and strawberry fruit, staircases and railings, and so on.

Parallel lines are lines in a plane that never meet, no matter how far they are extended. The distance between the parallel lines is constant because they never meet.

Parallel lines are defined as lines that do not intersect or meet at any point in a plane. They are always parallel and equidistant from one another.

these are 8 parallel lines

2x+3y = 6

2x+3y = 4

2x+3y = 1

2x+3y = 2

2x+3y = 3

2x+3y = 8

2x+3y = 7

2x+3y = 5

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Answer:

16 miles

Step-by-step explanation:

The graph is counting by 2, and there are 8 spaces between the Grocery store and the post office.  8(2) = 16

Answer:

16

Step-by-step explanation:

Answer:

Step-by-step explanation:

1. 1/4a = 3

   a = 12

   answer is C

2. -2c = 18

     c = -9

   answer is A

3. 2/3x = 6

    2x = 18

     x = 9

   Answer is A

4. x/4 =12/6

    x/4 = 2

     x = 8

   answer is C

5. 18 - 11= 7 more cupcakes

     answer is C

The fit statistic that can be used across different series that are in fact measured in different units is; MAPE

There are different statistics models in this regards such as;

Mean Absolute Error (MAE)

Mean Absolute Scaled Error (MASE)

Accuracy Percent (Accuracy %)

Mean Squared Error (MSE)

Root Mean Squared Error (RMSE)

Mean Absolute Percent Error (MAPE)

Now, we are told that we need the fit statistic that can be used across different series that are in fact measured in different units.

The correct one will be Mean Absolute Percent Error (MAPE) because the average absolute percent difference between the values that are fitted by the model and the observed data values.

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Answer:

2.56

Step-by-step explanation: