Each Can be represented by an atomic Each atomic symbol can tell you how he number of The atomic And the Of the atom.
You can figure out the number of By The number of protons from the atomic mass. A symbol represents an If there is a Or negative number in the upper Corner.

Ion, protons, neutrons, charge, subtracting, element, symbol, positive, mass, right

the rate of change of the radius at the instant the volume equals 36π cm³ is 7 / (36π) cm/sec.

The volume V of a sphere with radius r is given by the formula V = (4/3)πr³. We are given that the rate of change of the volume is 7 cm³/sec. Differentiating the volume formula with respect to time, we get dV/dt =(4/3)π(3r²)(dr/dt), where dr/dt represents the rate of change of the radius with respect to time.

We are looking for the rate of change of the radius, dr/dt, when the volume equals 36π cm³. Substituting the values into the equation, we have: 7 = (4/3)π(3r²)(dr/dt)

7 = 4πr²(dr/dt) To find dr/dt, we rearrange the equation: (dr/dt) = 7 / (4πr²) Now, we can substitute the volume V = 36π cm³ and solve for the radius r: 36π = (4/3)πr³

36 = (4/3)r³

27 = r³

r = 3  Substituting r = 3 into the equation for dr/dt, we get: (dr/dt) = 7 / (4π(3)²)

(dr/dt) = 7 / (4π(9))

(dr/dt) = 7 / (36π)

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Statistical guidance should perform well in situations such as clinical trials and market research where rigorous data analysis and inference are necessary. Statistical methods provide a systematic approach to control biases, handle variability, and draw reliable conclusions, ensuring accurate decision-making and predictions based on the data.

Statistical methods are crucial in determining sample sizes, designing the study, and analyzing the data to draw valid conclusions about the effectiveness and safety of the treatment.

In this situation, statistical guidance should do well because it provides a systematic framework to control for biases, random variability, and confounding factors, ensuring robust and reliable results that can be generalized to a larger population.

One example where statistical guidance should perform well is in clinical trials for new drugs or treatments.

Another example is in market research and opinion polling. Statistical techniques can be used to collect and analyze data from a representative sample of the target population, allowing for accurate estimation and prediction of consumer preferences, market trends, or election outcomes.

Statistical guidance should do well in this situation because it provides methods for random sampling, hypothesis testing, and confidence interval estimation, which help minimize sampling errors and increase the reliability of the findings.

Additionally, statistical models can capture complex relationships and make accurate predictions based on the observed data.

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The answer to the trigonometry question in the picture attached is:

   = cos θ / [sin θ * (1 - sin θ)] * (1 + sin θ)

Simplify 1-csc θ as follows:

1 - csc θ = (1 - csc θ)(1 + csc θ) / (1 + csc θ)

= 1 - csc^2 θ / (1 + csc θ)

= 1 - 1/sin^2 θ / (1 + 1/sin θ)

= 1 - sin^2 θ / (sin θ + 1)

= (sin θ - sin^2 θ) / (sin θ + 1)

Simplify 1+csc θ as follows:

1 + csc θ = (1 + csc θ)(1 - csc θ) / (1 - csc θ)

= 1 - csc^2 θ / (1 - csc θ)

= 1 - 1/sin^2 θ / (1 - 1/sin θ)

= 1 - sin^2 θ / (sin θ - 1)

= (sin θ + sin^2 θ) / (sin θ - 1)

Substitute the above simplifications in the expression cos θ/(1-csc θ) * 1+csc θ/(1+ csc θ) to get:

cos θ / (sin θ - sin^2 θ) * (sin θ + sin^2 θ) / (sin θ + 1)

Simplify the expression by canceling out the sin^2 θ terms:

cos θ / (sin θ - sin^2 θ) * (sin θ + sin^2 θ) / (sin θ + 1)

= cos θ / (sin θ - sin^2 θ) * (1 + sin θ) / (sin θ + 1)

Simplify further by factoring out common terms in the numerator and denominator:

cos θ / (sin θ - sin^2 θ) * (1 + sin θ) / (sin θ + 1)

= cos θ * (1 + sin θ) / [(sin θ - sin^2 θ) * (sin θ + 1)]

Finally, simplify the expression by factoring out a sin θ term from the denominator:

cos θ * (1 + sin θ) / [(sin θ - sin^2 θ) * (sin θ + 1)]

= cos θ * (1 + sin θ) / [sin θ * (1 - sin θ) * (sin θ + 1)]

= cos θ / [sin θ * (1 - sin θ)] * (1 + sin θ)

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Answer:

52

Step-by-step explanation: This would be incorrect because 53.864 must round up.

The standard deviation of returns is 0.0665 when a person is holding stock and there are three possible outcomes.

To calculate the expected return, we multiply the probability of each state by its corresponding return and sum them up:

Expected return = (20% * 18%) + (55% * 9%) + (25% * -5%)

Expected return = 0.20 * 0.18 + 0.55 * 0.09 + 0.25 * (-0.05)

Expected return = 0.036 + 0.0495 - 0.0125

Expected return = 0.073

The expected return is 7.30%.

To calculate the standard deviation of returns, we need to find the variance first. The variance is calculated as the weighted sum of squared deviations from the expected return:

Variance = (20% * (18% - 7.30%)^2) + (55% * (9% - 7.30%)^2) + (25% * (-5% - 7.30%)^2)

Variance = 0.20 * (0.1077)^2 + 0.55 * (0.0177)^2 + 0.25 * (-0.123)^2

Variance = 0.00232 + 0.000173 + 0.001903

Variance = 0.004423

The standard deviation is the square root of the variance:

Standard deviation = √(0.004423)

Standard deviation = 0.0665

Therefore, the value obtained is 0.0665.

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If the roots are 5 and 4, the factors are (x - the roots).  So the factors are (x-5) and (x+4).  The leading coefficient tells us what the factors are multiplied by.

Therefore, the equation is (1) (x-5)(x+4)  =  x^2 -x 20  

Answer: 60

6 x 10 is 60 and a negative times a negative is positive.

Answer: 60 hope this helps

1) The given function is 25x² +6x +2.

To determine the location of each local extremum of the given function,

We need to find its derivative, f'(x) = 50x +6.

Now, to find the critical points, we need to solve f'(x) = 50x +6 = 0 => x = -3/25.

This is the only critical point of the function.

So, to check whether it is a local maxima or a local minima,

We need to find the second derivative. f''(x) = 50 which is always positive for any x.

Therefore, the only critical point x = -3/25 is the location of local minimum.

Hence, the local minimum is at x = -3/25.

The local minimum is at x = -3/25.2) The given function is f(x) = x² + 9x²³ - 81x² + 20.

To determine the location of local extrema, we need to find its first derivative. f'(x) = 2x + 27x²² - 162x.

Now, to find the critical points, we need to solve f'(x) = 2x + 27x²² - 162x = 0 => 27x²² - 160x = 0 => x = 0, x = 160/27.

These are the only critical points of the function .

So, to check whether they are a local maxima or a local minima, we need to find the second derivative. f''(x) = 2 + 54x²¹ - 162

Which can be written as f''(x) = -160 for x = 0 and f''(x) = 898 for x = 160/27.

Therefore, x = 0 is a point of inflection and x = 160/27 is the point of local minima.

Hence, the local minimum is at x = 160/27. Answer: A. The local minimum is at x = 160/27.

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Answer:

You need to use a nested for loop. Use the range() builtin to produce an iterable sequence. The outer for loop should iterate over the number of rows.

Step-by-step explanation:

Use the range() builtin to produce an iterable sequence. The outer for loop should iterate over the number of rows overtime.

If you rolled two dice, recorded the face values and summed them up, you would be collecting quantitative data. This is because quantitative data is numerical in nature and involves counting, measuring or quantifying something.

In this case, the numbers on the faces of the dice would be counted and added together to obtain a total sum. This data can be further classified as discrete since the possible outcomes of rolling dice are limited to a set of discrete values.

Therefore, this data can be easily analyzed using statistical methods to determine the probability of certain outcomes occurring. Collecting quantitative data is essential in many fields such as science, economics, and finance, as it provides valuable insights into the behavior and trends of various phenomena.

In this situation, the face values on the dice represent numbers, and the sum of these values is also a number. The data you collect can be analyzed using statistical methods and can provide meaningful insights.

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Given:

Amount deposited on birth = $10,000.

Interest rate = 5% compound quarterly.

To find:

The balance on the person's 18th birthday.

Solution:

The formula for amount is

\(A=P\left(1+\dfrac{r}{n}\right)^{nt}\)

where, P is principal, r is rate of interest, n is number of times interest compounded in an year and t is number of years.

Substitute P=10000, r=0.05, n=4, t=18 in the above formula.

\(A=10000\left(1+\dfrac{0.05}{4}\right)^{4(18)}\)

\(A=10000\left(1+0.0125\right)^{72}\)

\(A=10000\left(1.0125\right)^{72}\)

\(A=24459.2026814\)

\(A\approx 24459.20\)

Therefore, the balance on the person's 18th birthday is $24459.20.

Answer:

1/3 and 6/18 their relationship is 6

Step-by-step explanation:

I think this might be the answer but I was confused as to what it meant as well. Sry if it’s wrong :(

The correct answer is b. we know the standard deviation of the population.

The Nearly Normal condition, also known as the Central Limit Theorem, states that the sampling distribution of the sample mean tends to be approximately normal, even if the population distribution is not normal, under certain conditions. One way to meet the Nearly Normal condition is by knowing the standard deviation of the population.

When the standard deviation of the population is known, the sample size does not have to be large for the sampling distribution of the sample mean to be approximately normal. This is because the standard deviation provides information about the variability of the population, allowing for a more accurate estimation of the sample mean distribution.

While the other options (a, c, and d) may be relevant in specific scenarios, they are not directly related to meeting the Nearly Normal condition as defined by the Central Limit Theorem.

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Answer:

‒3

Step-by-step explanation:

2b/3‒5=3

2b=3(3‒5)

2b=3(‒2)

2b=‒6

2b/2=‒6/2

b=‒3

you can proof as the following(by replace ‒3)

2(‒3)/3‒5=3

‒6/‒2=3

3=3

i hope it helps you

A system of two linear equations will have only one solution, and two quadratic equations will have two solutions, and an exponential equation will have either two or one or many solutions.

The solution of an equation is the set of all values that, when substituted for unknowns, make an equation true.

Given that, a system of two linear equations, quadratic equations and exponential equations,

A linear equation have three possible outcomes for solutions, if lines coincides will have infinitely many solutions, if lines are parallel will have no solutions and if lines intersects at a point then it will have exactly one solution.

Exponential equations with one term and an even power will have up to 2 solutions. Exponential equations with one term and an odd power will have exactly one solution. Exponential equations with multiple terms and both even and odd exponents can have many solutions.

In a system of quadratic equations, a quadratic equation have two solutions, if discriminant is smaller than 0 will have two imaginary solutions and if discriminant is greater than 0 will have two real solutions.

Hence, A system of two linear equations will have only one solution, and two quadratic equations will have two solutions, and an exponential equation will have either two or one or many solutions.

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The total Production cost  is:  $6900

Production cost is simply defined as the sum of costs of all resources that is consumed in the process of making a product.

The production cost is classified into three categories. They are;

- direct materials cost

- direct labor cost

- manufacturing overhead

It is also seen as a  factor in total delivery cost.

From the information given, we have that;

Labor costs = 4140

Computing costs = 1035

Savings on reusable material = 1725

Production cost = 4140 + 1035 + 1725

add the values

Production cost = $6900

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Answer:

x=56

Step-by-step explanation:

add 8 to both sides to get 1/2x=28

multiply both sides by 2 to get 1x=56

so x=56

Answer:

x=24

Step-by-step explanation:

1/2x+8=20

Move 8 to the right side

1/2x=20

multiply both sides by 2

2*1/2x=20*2

simplify and you get the answer where x=24

Answer:

Step-by-step explanation:

Step one- is solving the left side of the equation using PEMDAS, 1.4x10 = 14

Step two- 14-5 = 9

Step 3 - 2.8 times 10 = 28

Step 4 - 28- 4 = 24

The answer is 9 and 24

Using the triangle inequality theorem, the largest possible whole-number length for the third side is 4.

The third side of a triangle must be shorter than the sum of the other two sides and longer than the difference between the other two sides.

So, for a triangle with sides of length 1, 4, and x (where x is the length of the third side), we have:

1 + 4 > x

4 + x > 1

1 + x > 4

Simplifying these inequalities, we get:

5 > x

x > 3

x > -3 (this inequality is always true)

The largest possible whole-number length for the third side is 4, since it is the largest integer that satisfies the above inequalities.

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The correct answer is incorrect. The 99.8% confidence interval for the population mean is not 54.4.

To construct a confidence interval, we can use the formula:

CI = x ± z * (s / sqrt(n))

Where x is the sample mean, s is the sample standard deviation, n is the sample size, and z is the critical value corresponding to the desired confidence level.

For a 99.8% confidence level, the critical value is z = 2.807. Plugging in the values into the formula, we have:

CI = 58.5 ± 2.807 * (9.5 / sqrt(57))

Calculating the values, we get:

CI = 58.5 ± 2.807 * 1.253

CI = 58.5 ± 3.512

The confidence interval for the population mean L is therefore:

CI = (58.5 - 3.512, 58.5 + 3.512)

CI = (54.988, 62.012)

Rounding to one decimal place, the 99.8% confidence interval for the population mean is (55.0, 62.0).

The given answer of 54.4 is incorrect and does not fall within the calculated confidence interval.

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The optimal consumption bundle with initial prices is (X,Y) = ($5,$5). The optimal consumption bundle changes when the price of good X increases.

The new optimal consumption bundle with the increased price of X is (X,Y) = ($3.33,$6.67).

The total effect is a decrease in the consumption of good X by approximately $1.67.

The income effect is zero, and the substitution effect is a decrease in the consumption of good X by approximately $1.67.

To find the optimal consumption bundle, we maximize the utility function subject to the budget constraint. The budget constraint is given by the equation Px*X + Py*Y = Income.

1. Initial prices:

Here, Px = $1, Py = $1, and the consumer has $10 as income. To find the optimal consumption bundle, we substitute the utility function into the budget constraint and differentiate it with respect to X. By setting the derivative equal to zero, we find the optimal consumption bundle:

Px = Py

1 = 1

X = Y

Substituting X = Y into the budget constraint:

1*X + 1*X = 10

2*X = 10

X = 5

Thus, the optimal consumption bundle with initial prices is (X,Y) = ($5,$5).

2. Increased price of X:

When the price of X increases to $3, we need to find the new optimal consumption bundle. By following the same steps as above, we differentiate the utility function with respect to X, taking into account the new price of X:

Px = Py

3 = 1

X = Y

Substituting X = Y into the budget constraint:

3*X + 1*X = 10

4*X = 10

X = 2.5

The new optimal consumption bundle is (X,Y) = ($2.5,$2.5).

To calculate the total effect, we compare the change in the consumption of good X between the initial and new optimal bundles. The total effect is the decrease in the consumption of good X, which is approximately $1.67.

To decompose the total effect into income and substitution effects, we need to hold the consumer's utility constant at the initial level. By adjusting the consumer's income, we find that the income effect is zero. Thus, the total effect can be attributed entirely to the substitution effect.

The optimal consumption bundle changes when the price of good X increases. The consumer reduces their consumption of good X and increases their consumption of good Y. The total effect is a decrease in the consumption of good X by approximately $1.67, which is solely attributed to the substitution effect.

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Answer:

Step-by-step explanation:

the sum of the interior angles of a triangles is 180°

so

180 - 39 - 102 =

39

(it is an isosceles triangle)

In the given triangle the value of x° = 39°.

" A triangle is defined as the two dimensional closed shape with three sides , three vertices and three angles enclosed in it."

Theorem used

In ΔABC,

∠A + ∠B + ∠C = 180°

According to the question,

In the given triangle,

∠A represents measure of 102°

∠B represents measure of 39°

∠C represents measure of x°

Substitute the value in the triangle theorem   we get,

102° + 39° + x° = 180°

⇒141° + x° = 180°

⇒ x° = 180° - 141°

⇒ x° = 39°

Hence, in the given triangle the value of x° = 39°.

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Answer:

300 mins

Step-by-step explanation:

1 hours = 60 mins

5 hours = 5×60=300 mins

Answer:

300

Step-by-step explanation:

5 * 60 (minutes in an hour) = 300

Answer:

12 simple division

Step-by-step explanation:

Answer: A

Step-by-step explanation:

The answer is True. Degrees of freedom are a feature of statistics that are used when we are analyzing a sample rather than the population.

The degrees of freedom (df) refers to the number of independent observations in a sample that can be used to make inferences about a population. The concept of degrees of freedom is used in many statistical methods, including t-tests, ANOVA, and regression analysis.

In simple terms, degrees of freedom can be thought of as the number of data points in a sample that are "free" to vary in order to estimate a population parameter. For example, in a sample of two measurements, only one measurement is "free" to vary since the other measurement is used to calculate the mean. Hence, the degrees of freedom would be 1.

It's important to note that when analyzing a population, there are no degrees of freedom since all of the observations are considered independent and can be used to estimate the population parameters. In contrast, when working with a sample, the degrees of freedom are reduced by the number of constraints that are imposed on the sample in order to make inferences about the population.

In summary, the degrees of freedom are a feature of statistics that reflect the number of independent observations in a sample that can be used to make inferences about the population.

Therefore, The answer is True. Degrees of freedom are a feature of statistics that are used when we are analyzing a sample rather than the population.

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The answer is True. Degrees of freedom are a feature of statistics that are used when we are analyzing a sample rather than the population.

The degrees of freedom (df) refers to the number of independent observations in a sample that can be used to make inferences about a population. The concept of degrees of freedom is used in many statistical methods, including t-tests, ANOVA, and regression analysis.

In simple terms, degrees of freedom can be thought of as the number of data points in a sample that are "free" to vary in order to estimate a population parameter. For example, in a sample of two measurements, only one measurement is "free" to vary since the other measurement is used to calculate the mean. Hence, the degrees of freedom would be 1.

It's important to note that when analyzing a population, there are no degrees of freedom since all of the observations are considered independent and can be used to estimate the population parameters. In contrast, when working with a sample, the degrees of freedom are reduced by the number of constraints that are imposed on the sample in order to make inferences about the population.

In summary, the degrees of freedom are a feature of statistics that reflect the number of independent observations in a sample that can be used to make inferences about the population.

Therefore, The answer is True. Degrees of freedom are a feature of statistics that are used when we are analyzing a sample rather than the population.

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