what is the result from this equation .349 +0.131 d, +2.7511,₂ - 1 (x²0.48 + 10.729 +0.8947, 1/₂)

The double-entry principle in the balance of payments states that every transaction in the balance of payments is recorded as both a credit and a debit.

In the first transaction, the Saudi Arabian oil company's purchase of $1 million worth of U.S. government bonds from a U.S. bank will appear as a credit in the financial capital account and as a debit in the current account.

In the second transaction, Arielle's payment of $400 for her hotel stay in San Francisco using her French bank-issued debit card will appear as a credit in the current account and as a debit in the financial capital account.

In the third transaction, Frank's receipt of yen 500,000 in dividend payments on his shares in a Japanese company, which are deposited in his account in a Japanese bank, will appear as a credit in the financial capital account and as a debit in the current account.

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The solution of the linear equation:

7x – 13 = ─2x + 5

is x = 2

Here we want to find the value of x that is a solution of:

7x - 13 = -2x + 5

To solve it, we need to isolate x in one of the sides of the equation.

7x - 13 = -2x + 5

7x + 2x = 5 + 13

9x = 18

x = 18/9

x = 2

The value x = 2 makes the given linear equation true.

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Coefficient of determination and Correlation coefficient Is any one of the curves -superior is Y = [2.83321 3.17805 3.43399 3.49651 3.61092 3.61092 3.68888 3.68888 3.73767 3.71357]

n = 10

(a) Fitting a straight line using least-squares regression:

To find the equation of the line of best fit, we need to calculate the slope and intercept using the following formulas:

a1 = (nΣ(xy) - ΣxΣy) / (nΣx^2 - (Σx)^2)

a0 = y - a1x

where n is the sample size, Σ denotes the sum of, x and y are the mean of X and Y respectively.

Substituting the given values, we get:

n = 10

Σx = 275

Σy = 342

Σxy = 11745

Σx^2 = 8250

x = 27.5

y = 34.2

a1 = (1011745 - 275342) / (108250 - 275^2) = 0.8929

a0 = 34.2 - 0.892927.5 = 10.3143

Therefore, the equation of the line of best fit is:

y = 10.3143 + 0.8929x

To check these results using Matlab, we can use the following code:

x = [5 10 15 20 25 30 35 40 45 50];

y = [17 24 31 33 37 37 40 40 42 41];

mdl = fitlm(x,y)

The output should show the intercept and slope values, which match our calculated values. We can also plot the data and the line of best fit using the following code:

plot(x,y,'o')

hold on

xfit = 5:50;

yfit = 10.3143 + 0.8929*xfit;

plot(xfit,yfit,'-')

(b) Fitting a power equation using least-squares regression:

A power equation has the form y = ax^b, where a and b are constants. To fit a power equation using least-squares regression, we need to transform the equation into a linear form by taking the logarithm of both sides:

log(y) = log(a) + b*log(x)

Let Y = log(y) and X = log(x), then the equation becomes:

Y = log(a) + bX

This is now in the form of a straight line, y = a0 + a1x, where a0 = log(a) and a1 = b. We can use the same formulas as in part (a) to find the slope and intercept of the line of best fit:

a1 = (nΣ(XY) - ΣXΣY) / (nΣX^2 - (ΣX)^2)

a0 = Y - a1x

where X and Y are the means of X and Y respectively.

Substituting the given values, we get:

X = [0.69897 1 1.17609 1.30103 1.39794 1.47712 1.54407 1.60206 1.65321 1.69897]

Y = [2.83321 3.17805 3.43399 3.49651 3.61092 3.61092 3.68888 3.68888 3.73767 3.71357]

n = 10

ΣX = 12.05009

ΣY =

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A) The best graphical representation for the given data is a histogram.

B) The histogram of the given data is illustrated below.

Part A:

A histogram is a type of bar graph that shows the frequency distribution of a set of continuous or discrete data. The given data is a set of discrete data, and a histogram is the most appropriate graph to display the distribution of these data.

Part B:

To create a histogram for the given data, we need to follow these steps:

In summary, to create a histogram for the given data, we need to provide a title, label the x and y-axes, choose an appropriate scale for the x-axis, plot the data, and add final touches to make the graph more informative and visually appealing.

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The value of equation 7x² + 9x - 3 for x= 3 is 87.

We have the equation

7x² + 9x - 3.

Now, put the value of x = 3 in the given equation we get

7x² + 9x - 3.

= 7(3)² + 9(3) - 3.

=7(9) + 27- 3

= 63 - 3 + 27

= 60 + 27

= 87

Thus, the required value is 87.

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87 will be the value of the given expression when x= 3.

To find the value of the expression 7x^2 + 9x - 3 when x=3, we substitute x=3 into the expression and simplify:

7(3)^2 + 9(3) - 3

= 7(9) + 27 - 3

= 63 + 24

= 87

Therefore, the value of the expression 7x^2 + 9x - 3 when x=3 is 87.

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The coefficients of determination that are incorrect are -.88, 1.15, and 1.45.

The coefficient of determination, also known as R-squared, is a value between 0 and 1 that measures the proportion of variance in the dependent variable explained by the independent variable(s) in a regression model.

Values outside the range of 0 to 1, such as negative values or values greater than 1, are not valid coefficients of determination. In this case, -.88, 1.15, and 1.45 are incorrect because they fall outside the valid range.

The correct coefficients of determination in the given list are .77, .53, .11, and -.34. These values indicate the proportion of variance in the dependent variable explained by the corresponding independent variables in their respective regression models.

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a. There are 10 kg salt in the tank after t minutes

b.  After 30 minutes, the amount of salt in the tank is still 10 kg.

a) After t minutes, the amount of salt in the tank can be found by the formula:

Amount of salt = initial amount of salt + (rate of salt in - rate of salt out) x time

The initial amount of salt is 10 kg, and the rate of salt in is 0.01 kg/L x 15 L/min = 0.15 kg/min. The rate of salt out is also 0.01 kg/L x 15 L/min = 0.15 kg/min, because the solution is kept thoroughly mixed. Therefore, the amount of salt in the tank after t minutes is:

Amount of salt = 10 + (0.15 - 0.15) x t = 10 kg

b) After 30 minutes, the amount of salt in the tank is still 10 kg. This is because the rate of salt in and the rate of salt out are equal, and so the amount of salt in the tank remains constant. Therefore, the answer is the same as part (a), which is 10 kg

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Answer:

26 units

Step-by-step explanation:

The distance between two points with coordinates

Mateo will pay $56.32 when Starry and Ocean car rentals will cost the same.

Let's start by defining the cost functions for both car rentals. For Starry car rental, the cost function can be expressed as C1 = 31.19 + 0.47m, where m is the number of miles driven. For Ocean car rental, the cost function can be expressed as C2 = 48.57 + 0.36m.

We want to find the point where C1 = C2, so we can set the two cost functions equal to each other and solve for m:

31.19 + 0.47m = 48.57 + 0.36m

0.11m = 17.38

m = 158

So when Mateo drives 158 miles, the cost of renting from Starry car rental and Ocean car rental will be the same. We can then substitute m = 158 into either cost function to find the cost:

C1 = 31.19 + 0.47(158) = $107.33

C2 = 48.57 + 0.36(158) = $107.33

Therefore, Mateo will pay $107.33 to rent from either car rental when he drives 158 miles. However, we need to find the cost for just one day of rental. To do this, we can subtract the fixed daily cost from each cost function:

C1 = 31.19(1) + 0.47(158) = $105.33

C2 = 48.57(1) + 0.36(158) = $105.33

So, when Mateo rents a car for one day and drives 158 miles, he will pay $105.33 from either car rental. However, this is not the final answer as we need to find the cost when both car rentals will cost the same. To do this, we can substitute m = 158 into either cost function and round the result to the nearest cent:

C1 = 31.19(1) + 0.47(158) = $105.33

C2 = 48.57(1) + 0.36(158) = $105.33

Therefore, Mateo will pay $56.32 when Starry and Ocean car rentals will cost the same.

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The requested probabilities are: A. P(X > 1) ≈ 0.628;                                  B. P(X > 0.36) ≈ 0.844; C. P(X < 0.47) ≈ 0.226;                                              D. P(0.32 < X < 2.46) ≈ 0.524

The probability density function of an exponentially distributed random variable with parameter lambda is given by:

f(x) = lambda * e^(-lambda * x), for x >= 0

The cumulative distribution function (CDF) of X is given by:

F(x) = P(X <= x) = 1 - e^(-lambda * x), for x >= 0

Using the given value of lambda = 0.47, we can solve for each probability as follows:

A. P(X > 1) = 1 - P(X <= 1) = 1 - (1 - e^(-0.47 * 1)) = e^(-0.47) ≈ 0.628

B. P(X > 0.36) = 1 - P(X <= 0.36) = 1 - (1 - e^(-0.47 * 0.36)) = e^(-0.1692) ≈ 0.844

C. P(X < 0.47) = P(X <= 0.47) = 1 - e^(-0.47 * 0.47) ≈ 0.226

D. P(0.32 < X < 2.46) = P(X <= 2.46) - P(X <= 0.32) = (1 - e^(-0.47 * 2.46)) - (1 - e^(-0.47 * 0.32)) ≈ 0.524

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Check the picture below.

so the area of the pyramid is really just the area of a 3x3 square with four triangles with a base of 3 and a height of 5.

[tex]\stackrel{ \textit{\LARGE Areas} }{\stackrel{ square }{(3)(3)}~~ + ~~\stackrel{ \textit{four triangles} }{4\left[\cfrac{1}{2}(\underset{b}{3})(\underset{h}{5}) \right]}}\implies 9+30\implies \text{\LARGE 39}~in^2\textit{ for the cardboard}[/tex]

Answer:

I assume you trying to find a surface area (tell me if I'm wrong. okay?

Step-by-step explanation:

V = (1/2)bhL

where b is the base of the triangle, h is the height of the triangle, and L is the length of the prism.

The formula for the surface area of a triangular prism is:

SA = bh + 2(L + b)s

where b and h are the same as above, L is the length of the prism, and s is the slant height of the triangle.

To use these formulas, we need to identify the values of b, h, L, and s from the given dimensions. The base of the triangle is 8 units, the height of the triangle is 6 units, and the length of the prism is 15 units. The slant height of the triangle can be found using the Pythagorean theorem:

s^2 = b^2 + h^2 s^2 = 8^2 + 6^2 s^2 = 64 + 36 s^2 = 100 s = sqrt(100) s = 10

Now we can plug these values into the formulas and simplify:

V = (1/2)bhL V = (1/2)(8)(6)(15) V = (1/2)(720) V = 360

SA = bh + 2(L + b)s SA = (8)(6) + 2(15 + 8)(10) SA = 48 + 2(23)(10) SA = 48 + 460 SA = 508

Therefore, the volume of the triangular prism is 360 cubic units and the surface area is 508 square units.

The number of possible outcomes for each game is 3 (win, lose, or tie). Since there are 2 games left, the total number of possible outcomes is 3 x 3 = 9. Therefore, none of the given answers (a, b, or c) is correct. The correct answer is d.

To determine the number of possible outcomes for your favorite football team's remaining 2 games, we'll consider each game independently. Each game can have 3 possible outcomes: win, lose, or tie. For 2 games, you can use the multiplication principle:

Number of possible outcomes = Outcomes for Game 1 × Outcomes for Game 2

So, the number of possible outcomes is:

3 (win, lose, or tie in Game 1) × 3 (win, lose, or tie in Game 2) = 9

Since 9 is not among the given options, the correct answer is:

d. None of the other answers is correct.

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The probability that a wedding costs less than $20,000 is approximately 0.3745.

The probability that a wedding costs between $20,000 and $31,000 is approximately 0.6188.

The minimum cost for a wedding to be included among the most expensive 5% of weddings is approximately $31,229.

(a) To find the probability that a wedding costs less than $20,000, we need to standardize the value of $20,000 by subtracting the mean and dividing by the standard deviation:

z = (20000 - 21858) / 5800 = -0.32

We can then use a standard normal distribution table or technology to find the corresponding probability:

P(z < -0.32) ≈ 0.3745

Therefore, the probability that a wedding costs less than $20,000 is approximately 0.3745.

(b) To find the probability that a wedding costs between $20,000 and $31,000, we need to standardize both values and find the area between the corresponding z-scores:

z1 = (20000 - 21858) / 5800 = -0.32

z2 = (31000 - 21858) / 5800 = 1.58

Using a standard normal distribution table or technology, we can find the probabilities:

P(-0.32 < z < 1.58) ≈ 0.6188

Therefore, the probability that a wedding costs between $20,000 and $31,000 is approximately 0.6188.

(c) To find the minimum cost for a wedding to be included among the most expensive 5% of weddings, we need to find the z-score that corresponds to the 95th percentile of the standard normal distribution. We can use a standard normal distribution table or technology to find this value:

z = invNorm(0.95) ≈ 1.645

We can then use the formula for standardizing a value to find the minimum cost:

z = (x - 21858) / 5800

Solving for x, we get:

x = z(5800) + 21858

x = 1.645(5800) + 21858

x ≈ 31229

Therefore, the minimum cost for a wedding to be included among the most expensive 5% of weddings is approximately $31,229.

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The observed proportion of men who said they had not been screened is 0.8 or 80%.

The observed proportion of men who had not been screened can be calculated by dividing the number of men who had not been screened (160) by the total sample size (200):

Observed proportion of yet-to-be-screened men = number of unscreened men/ total sample size.

Observed proportion = 160/200 = 0.8

Therefore, the observed proportion of men who said they had not been screened is 0.8 or 80%.

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Answer:

V = 120 cm³

Step-by-step explanation:

the volume (V) of the prism is calculated as

V = Ah ( A is the area of the base and h the height )

to find h (ON)

use Pythagoras' identity in right triangle MNO

ON² + MN² = MO²

ON² + 7.5² = 8.5²

ON² + 56.25 = 72.25 ( subtract 56.25 from both sides )

ON² = 16 ( take square root of both sides )

ON = [tex]\sqrt{16}[/tex] = 4

Then

V = (4.5 × 4) × 4 = 30 × 4 = 120 cm³

The false statement is (a) a chi-square distribution with k degrees of freedom is more right-skewed than a chi-square distribution with k+1 degrees of freedom.

In fact, as the degrees of freedom increase, the chi-square distribution becomes less skewed and approaches a normal distribution. Statement (b) is true, a chi-square distribution never takes negative values. Statement (c) is generally true, the degrees of freedom for a chi-square test are determined by the sample size minus one. Statement (d) is incomplete, as there is no specified value for df. The larger the degrees of freedom, the smaller the p-value for a given chi-square value.

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The angle at which the brace meets the wall is approximately 56.51 degrees.

To calculate the angle at which the brace meets the wall at a construction site, we can use the right triangle trigonometry. Here, the brace is the hypotenuse of a right-angled triangle, with the distance from the wall to the lower end of the brace being one of the legs. We will use these terms: construction, brace, and angle in our explanation.

Step 1: Identify the given measurements
- Length of the brace (hypotenuse) = 9.6 m
- Distance from the wall to the lower end of the brace (adjacent leg) = 5.3 m

Step 2: Use the cosine function to find the angle
cos(angle) = adjacent leg / hypotenuse
cos(angle) = 5.3 m / 9.6 m

Step 3: Calculate the angle using the inverse cosine function
angle = cos^(-1)(5.3 m / 9.6 m)

Step 4: Find the angle using a calculator
angle ≈ cos^(-1)(0.5521) ≈ 56.51°

So, at the construction site, the angle at which the brace meets the wall is approximately 56.51 degrees.

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A 98% confidence interval for the population proportion that requested level X=70 with n=125 is (0.456, 0.664).

Using the given data, we can calculate the sample proportion as

p-hat = X/n = 70/125 = 0.56

To construct a confidence interval for the population proportion, we can use the formula

p-hat ± z√(p-hat(1-p-hat)/n)

where z is the z-score corresponding to the desired confidence level. For a 98% confidence level, the z-score is approximately 2.33.

Plugging in the values, we get

0.56 ± 2.33√(0.56(1-0.56)/125)

Simplifying, we get

0.56 ± 0.104

Therefore, the 98% confidence interval for the population proportion is (0.456, 0.664).

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The area between -2 and 0 is 0.5000 - 0.0228 = 0.4772. Therefore, P(-2 < z ≤ 0) = 0.4772.

(a) To find P(z ≤ -3.0), we can use a standard normal distribution table or technology such as a calculator or statistical software. Looking at a standard normal distribution table, we find that the area to the left of -3.0 is 0.0013 (rounded to four decimal places). Therefore, P(z ≤ -3.0) = 0.0013.

(b) To find P(z ≥ -3), we can use the fact that the standard normal distribution is symmetric about its mean of 0. Therefore, P(z ≥ -3) is the same as the area to the right of 3, which we can find using a standard normal distribution table or technology. Looking at a table, we find that the area to the right of 3 is also 0.0013. Therefore, P(z ≥ -3) = 0.0013.

(c) To find P(z ≥ -1.7), we can use a standard normal distribution table or technology. Looking at a table, we find that the area to the left of -1.7 is 0.0446 (rounded to four decimal places). Therefore, the area to the right of -1.7 (which is the same as P(z ≥ -1.7)) is 1 - 0.0446 = 0.9554. Therefore, P(z ≥ -1.7) = 0.9554.

(d) To find P(-2.6 ≤ z), we can use a standard normal distribution table or technology. Looking at a table, we find that the area to the left of -2.6 is 0.0047 (rounded to four decimal places). Therefore, P(-2.6 ≤ z) is the same as the area to the right of -2.6, which is 1 - 0.0047 = 0.9953. Therefore, P(-2.6 ≤ z) = 0.9953.

(e) To find P(-2 < z ≤ 0), we can use the fact that the standard normal distribution is symmetric about its mean of 0. Therefore, we can find the area to the left of -2 and the area to the left of 0 and subtract them to find the area between -2 and 0. Looking at a standard normal distribution table, we find that the area to the left of -2 is 0.0228 (rounded to four decimal places), and the area to the left of 0 is 0.5000. Therefore, the area between -2 and 0 is 0.5000 - 0.0228 = 0.4772. Therefore, P(-2 < z ≤ 0) = 0.4772.

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From the graph, the complex number with the greatest modulus is z1

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

The complex numbers z1, z2, z3 and z4

The general rule of modulus of complex numbers is that

The complex number that has the greatest modulus is the complex number that is at the farthest distance from the origin

Using the above as a guide, we have the following:

From the graph, the complex number that is at the farthest distance from the origin is the complex number z1

Hence, the complex number with the greatest modulus is z1

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100°

Supplementary angle pairs sum to 180°.

Supplementary Angles

Supplementary angle pairs form a straight line. Since straight lines have a measure of 180°, the sum of supplementary angles is always 180°. Supplementary angles do not necessarily have to be adjacent, but the angles above are. Since the angles above create a straight line together, they must be supplementary angles.

Solving for j

Now that we know that the sum must be 180°, we can create an equation to find j.

To solve this, all we need to do is subtract 80 from both sides.

Angle j must have a measure of 100°.

Samantha uses 3.75 feet of material to make each scarf if the total material used is 45 feet and she makes 12 scarves out of them.

Samantha has the total amount of material to make scarves is 45 feet. The total number of scarves made out of the material is 12. To calculate the material for one scarf we calculate it by dividing the total material by the number of scarves produced

Thus, Total material used = 45 feet

Number of scarves made = 12

Material for one scarf = 45 ÷ 12 = 3.75 feet

Thus, one scarf requires 3.75 feet of material.

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The function f(x) is increasing for all x < 3. Then the correct option is A.

Given that:

Function, f(x) = (x + 6) / (x² - 9x + 18)

A function is an assertion, concept, or principle that establishes an association between two variables. Functions may be found throughout mathematics and are essential for the development of significant links.

Simplify the function, then we have

f(x) = (x + 6) / (x² - 9x + 18)

f(x) = (x + 6) / (x² - 6x - 3x + 18)

f(x) = (x + 6) / [x(x - 6) - 3(x - 6)]

f(x) = (x + 6) / (x - 6)(x - 3)

The graph is given below.

The function f(x) is increasing for all x < 3. Then the correct option is A.

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In summary, changing the population mean affects the position or location of the confidence interval but does not directly impact its length. The length of the confidence interval is primarily influenced by the standard deviation and the sample size.

When the population standard deviation (σ) is large, confidence intervals tend to be wider or longer. This is due to the nature of how confidence intervals are constructed and the relationship between standard deviation and precision.

Conceptually, a confidence interval is a range of values that is likely to contain the true population parameter with a certain level of confidence. The width of the confidence interval depends on various factors, including the sample size, the variability of the data, and the desired level of confidence.

When the standard deviation is large, it indicates that the data points are spread out over a wider range. This high variability in the data means that individual sample observations can differ significantly from the population mean. As a result, to capture a larger range of possible values for the population mean within the confidence interval, the interval needs to be wider.

Mathematically, the width of a confidence interval is proportional to the standard deviation (σ) divided by the square root of the sample size (n). When σ is larger, the numerator of this ratio increases, causing the width of the interval to increase. On the other hand, as the sample size increases, the denominator of the ratio increases, leading to a narrower interval.

In summary, when the standard deviation is large, the data points are more spread out, and there is more uncertainty in estimating the true population mean. To account for this higher variability and capture a wider range of possible values, confidence intervals need to be wider or longer. On the other hand, when the standard deviation is small, the data points are more clustered around the mean, resulting in a narrower interval and higher precision in estimating the population mean.

2. Yes, changing the population mean (µ) does influence the length of the confidence interval.

The length of a confidence interval is determined by various factors, including the standard deviation (σ), the sample size (n), and the level of confidence. However, the population mean (µ) itself does not directly impact the length of the confidence interval.

The population mean affects the point estimate of the sample mean, which is used to calculate the center or midpoint of the confidence interval. A higher population mean would lead to a higher sample mean, resulting in a shift of the confidence interval along the number line. However, the length of the interval is primarily determined by the standard deviation and the sample size.

When the population mean is changed, the location of the confidence interval shifts, but the width or length of the interval remains relatively unchanged if the standard deviation and sample size remain the same. This is because the standard deviation reflects the variability of the data, which determines how spread out the observations are around the mean.

In summary, changing the population mean affects the position or location of the confidence interval but does not directly impact its length. The length of the confidence interval is primarily influenced by the standard deviation and the sample size.

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The answer is option [tex](cx^2y^2).[/tex]

To find the least common multiple (LCM) of [tex]xy, x^2,[/tex] and xy^2, we need to factor each term into its prime factors and then take the highest power of each factor.

xy = (x) * (y)

x^2 = (x) * (x)

xy^2 = (x) * [tex](y^2)[/tex]

The prime factorization of the given terms are:

xy = (x) * (y)

x^2 = (x) * (x)

xy^2 = (x) * [tex](y^2)[/tex]

So, the LCM can be found by taking the highest power of each factor, which gives us:

LCM = [tex](x^2)[/tex] * [tex](y^2)[/tex] =[tex]x^2y^2[/tex]

Therefore, the answer is option [tex](cx^2y^2).[/tex]

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In the expression 7x + 15, 15 is a COEFFICIENT: False.

In the expression 7x + 15, 15 is a constant.

3x + 7 means (3x + 7) DIVIDED BY 2: False.

3x + 7 means 3x plus 7.

You can rewrite 2(4 + 8) as (2)(4) + (2)(8) using the DISTRIBUTIVE PROPERTY: True.

In Mathematics, the distributive property of multiplication states that when the sum of two or more addends are multiplied by a particular numerical value, the same result and output would be obtained as when each addend is multiplied respectively by the same numerical value, and the products are added together.

By applying the distributive property of multiplication to left side of the equation, we have the following:

2(4 + 8) = (2)(4) + (2)(8)

2(12) = 8 + 16

24 = 24

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The z-score of the norminal distribution is 10.14.

Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values.

To calculate the z-score of the norminal distribution, we use the formula below

Formula:

Where:

From the question,

Given:

Substitute these values into equation 1

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The probability of obtaining exactly seven heads can be calculated using the binomial probability formula: P(X=7) = (10 choose 7) * (0.7)^7 * (0.3)^3 = 0.2668, where (10 choose 7) represents the number of ways to choose 7 heads out of 10 tosses.

The probability of obtaining exactly ten heads is also calculated using the binomial probability formula: P(X=10) = (10 choose 10) * (0.7)^10 * (0.3)^0 = 0.0282, where (10 choose 10) represents the number of ways to choose all 10 heads out of 10 tosses.

The probability of obtaining no heads can be calculated by using the complement rule: P(no heads) = 1 - P(at least one head). Since there are only two outcomes (heads or tails) for each toss, the probability of obtaining no heads is simply (0.3)^10 = 0.000005904.

=The probability of obtaining at least one head can also be calculated using the complement rule: P(at least one head) = 1 - P(no heads) = 1 - (0.3)^10 = 0.999994096.\

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