Save According to a certain organization adults worked an average of 1,820 hours last year Assume the population standard deviations 440 hours and that a random sample of 50 adults was selected Complete parts a through e below a. Calculate the standard error of the mean = 6223 (Round to two decimal places as needed b. What is the probability that the sample mean wit be more than 10 hours? P(1830) - (Round to four decimal places as needed

The correct answer is: "The second job offer is better by $21,840."

Let's calculate the total value of the second offer after 4 years:

Yearly salary: $63,000

Total gross income after 4 years: $63,000 x 4 = $252,000

For the 401k contributions, the company matches 5% of the employee's salary, so the employee contributes 5% of $63,000 = $3,150 per year, and the company contributes an additional 5% of $63,000 = $3,150 per year.

After 4 years, the total contributions and company matches are:

Employee contributions: $3,150 x 4 = $12,600

Company matches: $3,150 x 4 = $12,600

Total 401k contributions: $12,600 + $12,600 = $25,200

Therefore, the total value of the second offer after 4 years is:

Total value: $252,000 + $25,200 = $277,200

Now, let's compare this to the total value of the first offer, which is given as $255,360.

Therefore, the second job offer is better by:

$277,200 - $255,360 = $21,840

So the correct answer is: "The second job offer is better by $21,840."

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The theoretical probability of choosing List A is less than the experimental probability of choosing List A.

The theoretical probability of choosing List B is greater than the experimental probability of choosing List A.

For a fair coin, the theoretical probability of obtaining a head or tail is 0.5 or 50% each.

Therefore, theoretically, the probability of choosing List A is 0.5, and the probability of choosing List B is also 0.5.

The experimental probability of choosing List A or List B is obtained using the formula below:

Experimental probability of List A = 37/70

Experimental probability of List A = 0.529

The experimental probability of choosing List B is:

Experimental probability of List B = 33/70

Experimental probability of List B = 0.471

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95% Confidence Interval = (0.310, 0.490), 98% Confidence Interval = (0.293, 0.507), 99% Confidence Interval = (0.278, 0.522)

To compute the confidence intervals for the population proportion p, we need to use the following formula:

CI = p ± z * √(p(1-p)/n)

Where CI is the confidence interval, p is the sample proportion, z is the z-score for the desired level of confidence, and n is the sample size.

For p = 0.4 and n = 129, we have:

- For a 95% confidence interval, the z-score is 1.96:
CI = 0.4 ± 1.96 * √(0.4(1-0.4)/129) = (0.323, 0.477)
So we can say with 95% confidence that the population proportion p is between 0.323 and 0.477.

- For a 98% confidence interval, the z-score is 2.33:
CI = 0.4 ± 2.33 * √(0.4(1-0.4)/129) = (0.304, 0.496)
So we can say with 98% confidence that the population proportion p is between 0.304 and 0.496.

- For a 99% confidence interval, the z-score is 2.58:
CI = 0.4 ± 2.58 * √(0.4(1-0.4)/129) = (0.293, 0.507)
So we can say with 99% confidence that the population proportion p is between 0.293 and 0.507.

In summary, as the level of confidence increases, the width of the confidence interval increases, reflecting the increased uncertainty in our estimate of the population proportion.

To compute the 95%, 98%, and 99% confidence intervals for the population proportion p with p=0.4 and n=129, you can use the following formula:

Confidence Interval = p ± Z * sqrt((p*(1-p))/n)

Where p is the proportion, n is the sample size, and Z is the Z-score corresponding to the desired confidence level (1.96 for 95%, 2.33 for 98%, and 2.58 for 99%).

95% Confidence Interval = 0.4 ± 1.96 * sqrt((0.4*(1-0.4))/129)
98% Confidence Interval = 0.4 ± 2.33 * sqrt((0.4*(1-0.4))/129)
99% Confidence Interval = 0.4 ± 2.58 * sqrt((0.4*(1-0.4))/129)

After performing the calculations, you will get:

95% Confidence Interval = (0.310, 0.490)
98% Confidence Interval = (0.293, 0.507)
99% Confidence Interval = (0.278, 0.522)

These intervals represent the range in which the true population proportion is likely to be found with the given confidence level.

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The volume of the given rectangular prism is 13.5 units³

Given that the area of the base of a rectangular prism is 27/5 units², and the height is 5/2 units, we need to find the volume,

Volume = base area x height

= 27/5 x 5/2

= 13.5

Hence, the volume of the given rectangular prism is 13.5 units³

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Probability is the likelihood or chance of an event occurring.

The probability of Malik drawing a green marble on the first draw is 7/10, and the probability of drawing a black marble on the second draw, without replacement, is 3/9 (since there are 9 marbles left in the bag after the first draw, and 3 of them are black). Therefore, the probability of drawing a green marble followed by a black marble is:

P(Green, then Black) = P(Green) x P(Black | Green)

P(Green, then Black) = (7/10) x (3/9)

Simplifying:

P(Green, then Black) = 7/30

So the equation to show the probability of Malik drawing a green marble and then a black marble is:

P(Green, then Black) = (7/10) x (3/9) = 7/30

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Answer:The radius of a circle is 7 centimeters. What is the length of a 135° arc? 135⁰ r=7 cm Give the exact answer in simplest form. centimeters​  

Step-by-step explanation:The radius of a circle is 7 centimeters. What is the length of a 135° arc? 135⁰ r=7 cm Give the exact answer in simplest form. centimeters​ jus do it

Answer:

B. 27 Units

Step-by-step explanation:

To find the perimeter of the figure, we simply add up the lengths of all the sides.

So, the perimeter of the figure with sides of length 8, 6, 4, and 9 units is:

P = 8 + 6 + 4 + 9 = 27 units

Therefore, the answer is B. 27 units.

To find the p-value for the test examining the positive linear relationship between speed and jump height, you need to calculate the Pearson correlation coefficient, determine the degrees of freedom, and then find the corresponding p-value.

To determine the p-value for this test, we would need to conduct a hypothesis test using a linear regression model. The null hypothesis would be that there is no linear relationship between speed and jump height, while the alternative hypothesis would be that there is a positive linear relationship between the two variables.

After running the regression model and performing the hypothesis test, we would look for the p-value associated with the slope coefficient for speed. If this p-value is less than the chosen significance level (usually 0.05), we can conclude that there is convincing evidence of a positive linear relationship between speed and jump height for students like these.

Without actually running the regression model and hypothesis test, it is not possible to provide an exact p-value for this scenario.

To determine if there is convincing evidence of a positive linear relationship between speed (mph) and jump height (in) for students like these, you need to conduct a correlation test, specifically a Pearson correlation test. The p-value will help you determine the significance of the relationship.

Step-by-step explanation:

1. Gather the data: Obtain the values for speed (mph) and jump height (in) for each student.

2. Calculate the Pearson correlation coefficient (r): This value will help you measure the strength and direction of the linear relationship between the two variables. You can use statistical software or a calculator for this.

3. Determine the degrees of freedom (df): Calculate this by subtracting 2 from the total number of data points (n). Formula: df = n - 2.

4. Calculate the p-value: Using the Pearson correlation coefficient (r) and the degrees of freedom (df), you can find the p-value in a t-distribution table or by using statistical software.

5. Interpret the p-value: If the p-value is less than your chosen significance level (commonly 0.05), there is convincing evidence of a positive linear relationship between speed and jump height. If the p-value is greater than 0.05, there is not enough evidence to suggest a significant positive linear relationship.

In summary, to find the p-value for the test examining the positive linear relationship between speed and jump height, you need to calculate the Pearson correlation coefficient, determine the degrees of freedom, and then find the corresponding p-value. Comparing this p-value to your chosen significance level will help you conclude if there is convincing evidence of a positive linear relationship between the two variables.

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The solution is:

Anna bought 3 pounds of grapes, 6 pounds of bananas, and 5 pounds of apples.

Let the amount of grapes be g. The amount of grapes, bananas, and apples are represented as follows.

Grapes: g

Bananas: 2g

Apples: g + 2

The total amount is 14; that means the above expressions must be equal to 14. Set up an equation and solve algebraically for g.

14 = g + 2g + (g + 2)

14 = g + 2g + g + 2

14 = 4g + 2

12 = 4g

3 = g

Remember, g represents the amount of grapes; that means Anna bought 3 pounds of grapes. To find the amount of bananas and apples, substitute into the expressions 2g and g + 2.

2g  =>  2(3)  =>  6

g + 2  =>  3 + 2  =>  5

Anna bought 3 pounds of grapes, 6 pounds of bananas, and 5 pounds of apples.

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The expression which can be used to find the remaining area of the larger square is calculated to be A = (12 in)² - 4(2 in)²

If Eli cuts off a 2-inch square from each corner of his 12-inch square, the new dimensions of the square will be 12 - 2 - 2 = 8 inches. Therefore, the remaining area of the larger square is:

(8 in) x (8 in) = 64 square inches

We can also express this mathematically as:

(12 in)A = (12 in)² - 4(2 in)² - 4(2 in)^2 = 144 sq in - 16 sq in = 128 sq in

So the expression that can be used to find the remaining area of the larger square is:

A = (12 in)² - 4(2 in)²

where A is the remaining area of the larger square.

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Answer: 13.1

Step-by-step explanation:

Arc length is angle of given section divided by 360 multiply all of this by the circumference. A is the angle, b is the radius d is the circumference. X is the arc length.

(letters shown have no correlation with the answer choices)

[tex]a=125\\b=6\\d\ =\ \left(2b\right)\cdot3.14\\x=\left(\frac{a}{360}\right)\cdot d[/tex]

This makes the arc length equal to 13.0833333333, which you can round up to be 13.1.

Even if you leave pi as what the Desmos Graphing Calculator simplifies it to, it still gives you the answer 13.08996939, which can be rounded up to 13.1.

Although you did not ask for this further information, the arc measure is equal to the center angle that corresponds to the arc, meaning the arc measure is equal to 125°, regardless what the radius or circumference is.

The inverse of the matrix [tex]\left[\begin{array}{cc}2&-7\\-2&5\end{array}\right][/tex] is [tex]-\frac 14 \left[\begin{array}{cc}5&7\\2&2\end{array}\right][/tex]

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

[tex]\left[\begin{array}{cc}2&-7\\-2&5\end{array}\right][/tex]

The determinant (D) of the matrix is

D = 2 * 5 + 7 * -2

Evaluate

D = -4

The inverse, I is then calculated as

[tex]I = -\frac 14 \left[\begin{array}{cc}5&7\\2&2\end{array}\right][/tex]

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Answer:

  x ∈ {π/4, π/3, 2π/3, 3π/4}

Step-by-step explanation:

You want the solutions on the interval [0, 2π) of the equation ...

  [tex]-4\cos^2(x)-2(\sqrt{3}+\sqrt{2}\sin(x)+\sqrt{6}+4=0[/tex]

Replacing the cosine function with its equivalent, we have a quadratic in sin(x).

  [tex]-4(1-\sin^2(x))-2(\sqrt{3}+\sqrt{2}\sin(x)+\sqrt{6}+4=0\\\\4\sin^2(x)-2(\sqrt{3}+\sqrt{2})\sin(x)+\sqrt{6}=0\\\\(2\sin(x)-\sqrt{3})(2\sin(x)-\sqrt{2})=0\\\\x\in\left\{\dfrac{\pi}{2}\pm\dfrac{\pi}{4},\dfrac{\pi}{2}\pm\dfrac{\pi}{6}\right\}\\\\\boxed{x\in\left\{\dfrac{\pi}{4},\dfrac{\pi}{3},\dfrac{2\pi}{3},\dfrac{3\pi}{4}\right\}}[/tex]

__

Additional comment

It is helpful to have the solutions provided by a graphing calculator. This gives a useful clue as to how the equation factors.

The graph was created using Desmos.

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NORMDIST uses numerical integration to compute the cumulative probability associated with a given point in the normal distribution because an analytical solution for the CDF is not available.

NORMDIST is a function that calculates the probability density function (PDF) or cumulative distribution function (CDF) of the normal distribution (also known as the Gaussian distribution). It uses numerical integration because the normal distribution's CDF cannot be expressed as a simple closed-form equation.

The reason for using numerical integration in NORMDIST is to compute the area under the curve of the normal distribution's PDF up to a specific point. This area represents the cumulative probability of a value being less than or equal to the given point. Numerical integration is an efficient way to approximate the integral of the function when an analytical solution is not possible or feasible.

In summary, NORMDIST uses numerical integration to compute the cumulative probability associated with a given point in the normal distribution because an analytical solution for the CDF is not available.

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Therefore, the options "it is usually shown on the horizontal axis of a scatter diagram" and "it is usually shown on the vertical axis of a scatter diagram" could both be true, depending on the preference of the researcher or the convention used in a particular field or context.

Neither of the variables is considered as the dependent variable in a correlation analysis. Correlation refers to the strength of the relationship between two variables, without implying a cause-and-effect relationship or assigning one variable as the independent or dependent variable. Therefore, the options "in a cause and effect relationship, it is the effect" and "in a cause and effect relationship, it is the cause" are not applicable.

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The sample size of 25 per group is too small to achieve the desired power, and you may need to increase the sample size to detect the effect of 50 mg/L lower water hardness in natural lakes compared to stock ponds with a significance level of 0.05.

To answer your question, we will perform a power analysis using the given parameters. Here are the given values:

Desired effect (Δ): 50 mg/L
Significance level (α): 0.05
Estimated population standard deviation (σ): 78.9170 mg/L
Desired power: 0.8
Sample size (n): 25 per group

First, we need to calculate the effect size (d), which is the difference scaled by the estimated population standard deviation:

d = Δ / σ = 50 / 78.9170 ≈ 0.6334

Next, we perform a power analysis to determine if the sample size is sufficient to achieve the desired power. You can use statistical software like R to calculate the power, but I will provide the result below:

Alternative: two. sided
Power (4 decimals): 0.4681

Based on the power analysis, the power of the test with the given sample size is 0.4681, which is less than the desired power of 0.8. Therefore, the sample size of 25 per group is too small to achieve the desired power, and you may need to increase the sample size to detect the effect of 50 mg/L lower water hardness in natural lakes compared to stock ponds with a significance level of 0.05.

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The actual area in square feet of the base of the building given the scale model will be; 418 square feet.

Since scale drawing is a reduced form in the dimensions of an original image / building / object.

Therefore, Scale of the drawing = original dimensions / dimensions of the scale drawing

Length of the base = 2 x 47 = 94 ft

Width of the base = 1 x 47 = 47

Area = 47 x 94 = 4418 square feet

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The height of the ball will be 16.94 feet. Then the baseball travels over the fence.

Given that:

Distance at time t, x = 140t

Height at time t, y = 3.1 + 40t − 16t²

Height, h = 10 feet

Distance, x = 320 feet

The time is calculated as,

320 = 140t

t = 320/140

t = 16/7

The height at t = 16/7 is calculated as,

y = 3.1 + 40(16/7) − 16(16/7)²

y = 3.1 + 97.43 - 83.59

y = 16.94 feet

y > 10 feet

The height of the ball will be 16.94 feet. Then the baseball travels over the fence.

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Answer:

21.9

Step-by-step explanation:

[tex]a^{2}[/tex] + [tex]b^{2}[/tex] = [tex]c^{2}[/tex]   If 18 is the whole base then 1/2 would be 9

[tex]9^{2}[/tex] + [tex]20^{2}[/tex] = [tex]c^{2}[/tex]

81 + 400 = [tex]c^{2}[/tex]

481 = [tex]c^{2}[/tex]

[tex]\sqrt{481}[/tex] = [tex]\sqrt{c^{2} }[/tex]

21.9 ≈ c Rounded to the nearest tenth

The solution of the equation is x = 7, so the correct option is C

Here we want to find the solution of the equation:

3*(x + 9)^(3/4) = 24

First divide both sides by 3 to get:

(x + 9)^(3/4) = 24/3 = 8

Now we can pass the exponent to get:

(x + 9) =8^(4/3) = 2^4 = 16

x + 9 = 16

Now subtract 9 in the left side.

x = 16 - 9

x  =7

The correct option is C.

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Firstly, when we say that a set is "non-void", we mean that it is not empty. In other words, it contains at least one element. On the other hand, when we say that something is "void", we mean that it is empty.

Now, let's take a look at the statement you provided. We have two sets, S and T, which are both non-void (meaning they are not empty). If S is less than or equal to T (S ≤ T), then we can say that S is a subset of T.

In this case, we want to show that the intersection of S and T, denoted as S ∩ T, can have at most one element. This means that there can be either one element in both S and T, or there can be no elements in common between the two sets. If there were two or more elements in common, then the intersection would not have at most one element.

Furthermore, if S ∩ T is non-void (meaning it is not empty), then we can say that it has a unique element. This unique element is both an upper bound for S and a lower bound for T. In other words, it is greater than or equal to all elements in S, and less than or equal to all elements in T.

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The quadratic equations that are taller, that is, with a greater dilation factor:

Case A: y = 10 · x²

Case B: y = x²

Case C: y = 3 · x²

Case D: y = x²

In this problem we find four pairs of quadratic equations of the form:

y = k · x², k > 0

Where:

A quadratic equation is taller when it has a greater dilation factor. Now we proceed to determine the function for each case:

Case A: y = x² and y = 10 · x²

y = 10 · x²

Case B: y = x² and y = (1 / 7) · x²

y = x²

Case C: y = x² and y = 3 · x²

y = 3 · x²

Case D: y = x² and y = (1 / 12) · x²

y = x²

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The solution to the multiplication of the table is:

A) -205

B) -67

C) -7.93

D) 1

E) -121

Multiplication is an order of operation used in mathematical operations or algebraic problems.

Now, when we multiply two numbers, the answer is called product. The number of objects in each group is called multiplicand, and the number of such equal groups is called the multiplier. Thus:

We have that we are to find the solution for x * y and this gives:

A) -205 * 1 = -205

B) 67 * -1 = -67

C) 1 * -7.93 = -7.93

D) -1 * -1 = 1

E) 11 * -11 = -121

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The probability of selecting a brown or black golf ball from the bag is 3/4 or 0.75.


To find the probability of the golf ball being either brown or black, follow these steps:

1. Find the total number of balls in the golf bag.
2. Calculate the combined number of brown and black balls.
3. Divide the number of brown and black balls by the total number of balls.

Step 1: Total number of balls = 5 brown + 7 black + 4 yellow = 16 balls
P(brown or black) = P(brown) + P(black)
P(brown or black) = 5/16 + 7/16
P(brown or black) = 12/16 or 3/4

Step 2: Combined number of brown and black balls = 5 brown + 7 black = 12 balls

Step 3: Probability of selecting a brown or black ball = (number of brown and black balls) / (total number of balls) = 12/16

To simplify the fraction, we can divide both the numerator and denominator by 4:
12/16 = (12/4) / (16/4) = 3/4

So, the probability of selecting a brown or black golf ball is 3/4 or 0.75.

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The constraint corresponding to node London in the shortest path problem, considering the westbound routes, is:
X(Waterloo-London) + X(Hamilton-London) - X(London-Windsor) = 0

The constraint corresponding to node London would be:
X(Waterloo-London) + X(Hamilton-London) >= 1

This is because the constraint ensures that there is at least one path that includes London in the route, in order to travel from Toronto to Windsor.

In mathematics, a constraint is a condition that the solution of an optimization problem must meet. In general, there are two types of constraints: inequality and inequality. A solution set that satisfies all constraints is called a fit set. An equation is an example of a constraint. We can use it to think about what it means to solve equations and inequalities.

For example, solving 3x + 4 = 10 gives x = 2, which is an easier way to express the same limit.

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40) If the demand for specialty car license plates is perfectly inelastic and the supply curve is upward sloping, then the burden of the tax falls entirely on the consumers (drivers). Therefore, option C) Drivers pay all of the tax is true.

41) If the elasticity of demand for a product is 0 and the elasticity of supply is 1, then the burden of the tax falls entirely on the consumers (buyers). Therefore, option B) Buyers pay all of the tax is true.

42) If the demand for peaches from South Carolina is perfectly elastic and the supply curve is upward sloping, then the burden of the tax falls entirely on the producers (peach sellers). Therefore, option A) Peach sellers pay all of the tax is true.

40) In this scenario, since the demand for specialty car license plates is perfectly inelastic and the supply curve is upward sloping, the correct answer is C) Drivers pay all of the tax. This is because the burden of the tax falls entirely on the consumers with perfectly inelastic demand.

41) With an elasticity of demand of 0 and elasticity of supply of 1, the correct answer is B) buyers pay all of the tax. This is because the inelastic demand means that buyers will absorb the entire tax burden, whereas the elastic supply indicates that sellers can adjust their supply in response to the tax.

42) When the demand for peaches from South Carolina is perfectly elastic and the supply curve is upward sloping, the correct answer is A) peach sellers pay all of the tax. This is because buyers will simply switch to other sources if the price increases due to the tax, so the burden of the tax falls entirely on the peach sellers.

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The false interpretation is that exactly 95% of the population has a caloric intake between 1875 and 2128 calories.

The 95% confidence interval means that if the student were to take multiple samples and calculate multiple confidence intervals, about 95% of those intervals would contain the true population mean caloric intake.
You provided a 95% confidence interval for the population mean 1-day caloric intake as (1875, 2128). The false interpretation of this confidence interval is:
"95% of the sampled individuals have a caloric intake between 1875 and 2128."
This statement is incorrect because a 95% confidence interval estimates the range within which the true population mean 1-day caloric intake is likely to fall, with 95% confidence. It does not describe the caloric intake range for individual people within the sample.

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