Use Appendix B.5 to locate the value of t under the following conditions. a. The sample size is 15 and the level of confidence is 95%. b. The sample size is 24 and the level of confidence is 98%. c. The sample size is 12 and the level of confidence is 90%.

As a supervisor, if some freshmen cadets in your squad are struggling with a particular skill like the "about face,"

A supervisor is a person who oversees the work of others and ensures that tasks are completed efficiently and effectively. They are typically responsible for managing a team of employees and providing guidance and direction to help them achieve their goals.

Supervisors are essential in most industries, including manufacturing, retail, healthcare, education, and many others. They are often responsible for hiring and training new employees, setting performance expectations, and monitoring progress to ensure that goals are met. They may also be responsible for developing work schedules, coordinating team meetings, and handling employee conflicts.

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Step-by-step explanation:

well, look at it for a second and focus.

what do you see ?

I see a square, where 4 quarter-circles at the corners are removed.

4 quarter-circles = 1 full circle.

so, we need to calculate the area of the square and subtract the area of the circle. that's it.

area of the square :

6 × 6 = 36 m²

area of the circle :

pi × r²

r is the radius, which is half of the diameter. the diameter is 6 m (2 quarter-circles connected with each other).

so, the radius is 3 m.

and we get

pi × 3² = 9pi m² = 28.27433388... m²

the shaded area is then

36 - 28.27433388... = 7.725666118... m² ≈ 7.73 m²

i hope this helps you.

We need to know the percentage of companies in the sample that are likely to require higher employee contributions in order to calculate the confidence interval.

Based on the information provided, we can calculate the margin of error and confidence interval for the proportion of companies likely to require higher employee contributions for health care coverage in the upcoming year. First, we need to know the sample size and the percentage of companies in the sample that are likely to require higher employee contributions. Unfortunately, this information is not given in the question. Without this information, it is impossible to calculate the margin of error and confidence interval. We need to know the sample size to determine the standard error of the proportion, which is necessary for calculating the margin of error. Additionally, we need to know the percentage of companies in the sample that are likely to require higher employee contributions in order to calculate the confidence interval.

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Answer:

Step 1: Identify the given solid figure. Step 2: Identify the faces and side lengths of the given solid figure. Step 3: Using the side lengths and shape of the faces, draw each face of the solid figure on a plane and mark the corresponding side length. You will get the net of the solid figure.

Answer:

  133 m²

Step-by-step explanation:

You want to know the area of a parallelogram with base 9.5 m and height 14 m.

The area is given by the formula ...

  A = bh

  A = (9.5 m)(14 m) = 133 m²

The area of the figure is 133 square meters.

__

Additional comment

The slant height (17 m) is irrelevant for finding the area.

<95141404393>

Find the area of the given figure

At first we have to identify the figure. This is a parallelogram.

Given:

To find :

Formula :

Solution:

We know

Area = Base × Height

Substituting the values we get

Area = 14 × 9.5

→ Area = 133 m²

The 95% confidence interval for the true proportion of tails in the population is (0.510, 0.572). This means that we are 95% confident that the true proportion of tails in the population is between 51.0% and 57.2%.

To find a 95% confidence interval for the true proportion of tails in the population, we can use the following formula:

[tex]CI = p + z\times (\sqrt{(p\times (1-p)/n))}[/tex]

Where:

p = the proportion of tails in the sample (541/1000 = 0.541)

z = the z-score associated with a 95% confidence level (1.96, since the distribution is approximately normal for large sample sizes)

n = the sample size (1000)

Substituting the values we have:

[tex]CI = 0.541 + 1.96\times (\sqrt{(0.541\times (1-0.541)/1000))}[/tex]

Simplifying:

CI = 0.541 ± 0.031

Therefore, the 95% confidence interval for the true proportion of tails in the population is (0.510, 0.572). This means that we are 95% confident that the true proportion of tails in the population is between 51.0% and 57.2%.

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Thus, the df between subjects is 5. This represents the variation between the individual subjects in the study, which helps in determining if the treatment effects are statistically significant or if the differences are due to random chance.

In a two-factor analysis of variance, the dfbetween subjects refer to the degrees of freedom associated with the differences between the group means. In this particular scenario where there are six subjects who each underwent three treatments, we can calculate the dfbetween subjects for each factor separately.

For the first factor (treatment), we have three levels. Therefore, the dfbetween subjects would be equal to the number of treatments minus one, which is 2.
For the second factor (subjects), we have six subjects. Therefore, the dfbetween subjects would be equal to the number of subjects minus one, which is 5.

To calculate df between subjects, you will use the following formula:

df between subjects = (number of subjects - 1)

In this case, there are six subjects, so the formula becomes:

df between subjects = (6 - 1)

Hence, the df between subjects is 5. This represents the variation between the individual subjects in the study, which helps in determining if the treatment effects are statistically significant or if the differences are due to random chance.

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Answer:

Option (D) Non-probability

Step-by-step explanation:

In Non-probability sampling, there is no way to calculate the likelihood that a specific element of the population being studied will be chosen.

The correct answer is d. nonprobability sampling.

In nonprobability sampling, the selection of elements from the population is not based on a known probability or randomization process. It does not allow for the calculation of the likelihood of a specific element being chosen because the selection is typically based on convenience, judgment, or availability. Nonprobability sampling methods are often used when it is difficult or impractical to obtain a representative sample from the population of interest.

In contrast, probability sampling methods (option b) involve random selection, and each element in the population has a known probability of being included in the sample. Probability sampling allows for the calculation of sampling probabilities and enables the estimation of sampling errors and the generalizability of findings to the population.

The other options (a. census, c. stratified, and e. quota) are not directly related to the described characteristic of not being able to calculate the likelihood of specific element selection.

A census involves studying the entire population, stratified sampling involves dividing the population into subgroups and sampling from each subgroup, and quota sampling involves selecting individuals based on pre-defined characteristics to meet specific quotas.

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A large sample size and low variability increase the likelihood of rejecting the null hypothesis, while a small sample size and high variability decrease the likelihood of rejecting the null hypothesis.

When a sample is selected from a population and a treatment is administered, it is important to determine if the treatment had a significant effect on the sample. This is done by comparing the sample mean to the original population mean and testing if the difference is statistically significant.

If there is a 3-point difference between the sample mean and the original population mean, the likelihood of rejecting the null hypothesis depends on the characteristics of the sample. In particular, the size of the sample and the variability of the data can influence the likelihood of rejecting the null hypothesis.

If the sample size is large and the data is relatively homogeneous (low variability), then even a small difference between the sample mean and the population mean may be statistically significant. This is because a larger sample size allows for more precision in estimating the population mean and reduces the effect of random sampling error.

On the other hand, if the sample size is small and the data is highly variable, a larger difference between the sample mean and the population mean may be required to reject the null hypothesis. This is because a small sample size and high variability increase the uncertainty in estimating the population mean and make it more difficult to detect small differences.

In summary, when there is a 3-point difference between the sample mean and the original population mean, the likelihood of rejecting the null hypothesis depends on the sample characteristics, specifically the size of the sample and the variability of the data.

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Answer:

a) 52 beads

b) 8 beads

Step-by-step explanation:

a) First find how many beads fills one inch by dividing 12 by 3.

 Number of beads that fill 1 inch = 12 ÷ 3

                                                      = 4 beads

Now, to find the beads need to fill 13 inches string, multiply 4 and 13.

Number of beads that fill 13 inches = 4 * 13

                                                          = 52 beads

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

b)   Number of beads that fill 1 inch = 4 beads

     Number of beads to be removed = 4 + 4

                                                              = 8 beads

The cost of ordering 22 solder-less lugs at the list price less 35% will be $101.20.

Solder-less lugs are priced at $4.25 each, including a 40% discount when purchased in standard packages of 100. To find the original price without the discount, we'll first calculate the price before the 40% discount:

$4.25 / (1 - 0.40) = $4.25 / 0.60 = $7.08 (rounded to 2 decimal places)

Now, if you only need 22 solder-less lugs and are eligible for a 35% discount, we'll calculate the discounted price for each lug:

$7.08 * (1 - 0.35) = $7.08 * 0.65 = $4.60 (rounded to 2 decimal places)

Finally, to find the total cost for 22 solder-less lugs with a 35% discount, we'll multiply the discounted price by the quantity ordered:

$4.60 * 22 = $101.20

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There are 183183 ways to form a committee with six members if it must have more women than men.

We need to find the number of ways to form a committee with six members, having more women than men.

We can achieve this in three possible scenarios:

To form a committee with more women than men, we can have either 1, 2, or 3 men on the committee.

We need to calculate the number of ways to form a committee in each of these cases and add them up to get the total number of ways.

Case 1: 1 man and 5 women

We can choose 1 man out of 11 and 5 women out of 15.

The number of ways to do this is:

11C1 * 15C5 = 11 * 3003 = 33033.

Case 2: 2 men and 4 women

We can choose 2 men out of 11 and 4 women out of 15.

The number of ways to do this is:

11C2 * 15C4 = 55 * 1365 = 75075

Case 3: 3 men and 3 women

We can choose 3 men out of 11 and 3 women out of 15.

The number of ways to do this is:

11C3 * 15C3 = 165 * 455 = 75075

Total number of ways = 33033 + 75075 + 75075 = 183183
This gives you the total number of ways to form a committee with six members, with more women than men.

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The manager of a grocery store conducted a study with a sample of 100 customers to determine if the mean waiting time is significantly greater than 3 minutes.

With an average checkout time of 3.1 minutes and a standard deviation of 0.5 minutes, at a 95% confidence level, it can be concluded that the mean of the population is c.

significantly greater than 3, the manager of the grocery store took a random sample of 100 customers and found that the average length of time it took customers in the sample to check out was 3.1 minutes with a standard deviation of 0.5 minutes.

The question asks if we can determine whether or not the mean waiting time of all customers is significantly greater than 3 minutes at a 95% confidence level. we need to conduct a hypothesis test. The null hypothesis is that the population mean waiting time is equal to 3 minutes,

while the alternative hypothesis is that the population mean waiting time is greater than 3 minutes. We can use a one-sample t-test to test this hypothesis. With a sample size of 100, we can assume that the sample is normally distributed. Using a t-distribution with 99 degrees of freedom (n-1), we can calculate the t-statistic as:

t = (X- μ) / (s / √n)
t = (3.1 - 3) / (0.5 / √100)
t = 2

Using a t-table with 99 degrees of freedom and a 95% confidence level, we find that the critical value is 1.984. Since our calculated t-statistic (2) is greater than the critical value (1.984), we can reject the null hypothesis and conclude that the mean waiting time of all customers is significantly greater than 3 minutes. Therefore, the answer is: c. significantly greater than 3.

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Answer:

a)

[tex] \sin(2( \frac{5}{13} )) = 2 \sin( \frac{5}{13} ) \cos( \frac{5}{13} ) [/tex]

b)

[tex] \cos( 2(\frac{5}{13}) ) = { cos }^{2} \frac{5}{13} - {sin}^{2} \frac{5}{13} [/tex]

The vertices of the parallelogram are (0,0), (5,2), (6,4), and (11,6). We can use the distance formula to find the lengths of the sides of the parallelogram:

The distance between (0,0) and (5,2) is √(5^2 + 2^2) = √29.

The distance between (5,2) and (6,4) is √(1^2 + 2^2) = √5.

The distance between (6,4) and (11,6) is √(5^2 + 2^2) = √29.

The distance between (11,6) and (0,0) is √(11^2 + 6^2) = √157.

Since opposite sides of a parallelogram are congruent, the lengths of the opposite sides are equal. So the area of the parallelogram is the product of the length of one pair of opposite sides and the height, which is the perpendicular distance between the parallel sides. We can find the height by drawing a line perpendicular to one of the parallel sides and finding its length using the Pythagorean theorem. For example, we can draw a line from (0,0) perpendicular to the side connecting (5,2) and (6,4):

The slope of the side connecting (5,2) and (6,4) is (4-2)/(6-5) = 2.

The slope of a line perpendicular to this side is -1/2.

The equation of the line perpendicular to this side passing through (0,0) is y = (-1/2)x.

The x-coordinate of the point where this line intersects the side connecting (5,2) and (6,4) can be found by setting y = 2 in the equation y = (-1/2)x. Solving for x, we get x = -4.

The length of the line from (0,0) to the point (-4,2) is √((-4-0)^2 + (2-0)^2) = 2√5.

So the area of the parallelogram is (length of one pair of opposite sides) x (height) = √29 x 2√5 = 2√145.

Therefore, the area of the parallelogram is 2√145 square units.

The vertices of the parallelogram are (0,0), (-2,4), (6,-5), and (4,-1). We can use the distance formula to find the lengths of the sides of the parallelogram:

The distance between (0,0) and (-2,4) is √((-2-0)^2 + (4-0)^2) = √20.

The distance between (-2,4) and (6,-5) is √((6-(-2))^2 + (-5-4)^2) = √185.

The distance between (6,-5) and (4,-1) is √((4-6)^2 + (-1-(-5))^2) = √20.

The distance between (4,-1) and (0,0) is √((0-4)^2 + (-1-0)^2) = 2√17.

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In an independent groups experiment, if you must estimate the population standard deviation to determine the significance of the sample results, the appropriate inference test is an F-test or the F-distribution, Welch's t-test.

Explanation:

The F-test is used to compare the variances of two or more groups. In the context of an independent groups experiment, where two or more groups are being compared, the F-test can be used to estimate the population standard deviation by comparing the variances of the samples from each group.

To conduct an F-test, the variances of the samples from each group are calculated, and the ratio of the largest sample variance to the smallest sample variance is computed. This ratio follows an F-distribution, which is a continuous probability distribution with two degrees of freedom: one for the numerator (largest sample variance) and one for the denominator (smallest sample variance). The F-distribution is used to determine whether the observed ratio of sample variances is statistically significant or not.

If the F-test results in a statistically significant ratio of sample variances, it indicates that the population standard deviations are likely to be different. In this case, the appropriate inference test would be a test that takes into account unequal population standard deviations, such as Welch's t-test, which is a modified version of the independent samples t-test that accounts for unequal variances. Welch's t-test is commonly used when the assumption of equal variances is violated in an independent groups experiment, and the population standard deviations cannot be assumed to be equal.

In summary, the appropriate inference test for estimating the population standard deviation in an independent groups experiment is the F-test or the F-distribution. If the F-test results in statistically significant differences in sample variances, then a modified version of the t-test, such as Welch's t-test, should be used to determine the significance of the sample results.

Therefore, the appropriate inference test for estimating the population standard deviation in an independent groups experiment is the F-test or the F-distribution.

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The means and standard deviation of the length of time that four randomly selected transistors will last are 3200 hours and 5 hours, respectively.

mean = 4 * 800 hours = 3200 hours.

The standard deviation of the length of time that four randomly selected transistors will last is equal to the standard deviation of a single transistor's lifetime divided by the square root of the sample size (which is 4), which is:

standard deviation = [tex]\frac{10}{\sqrt{4} }[/tex] = 5 hours.

Standard deviation is a measure of the amount of variation or dispersion of a set of data values around the mean. It is a statistical concept used in probability theory and statistics to measure the amount of spread or dispersion of a data set. The standard deviation is expressed in the same units as the original data and provides a measure of how tightly the data is clustered around the mean.

To calculate the standard deviation, you first find the mean of the data set. Then, for each data point, you find the difference between the data point and the mean. You square these differences, sum them up, and then divide by the number of data points minus one. The resulting value is the variance of the data set. The standard deviation is then calculated by taking the square root of the variance.

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In an independent-measures design experiment with two treatment conditions and 22 scores in each condition, a total of 44 subjects participated in the experiment.

To determine the number of subjects who participated in the experiment with an independent-measures design and 22 scores in each treatment condition, you simply need to add the number of scores in each condition together.

A researcher conducts an experiment comparing two treatment conditions with 22 scores in each treatment condition. If the researcher used an independent-measures design, how many subjects participated in the experiment are as follows:

Step 1: Identify the number of scores in each treatment condition.
There are 22 scores in each of the two treatment conditions.

Step 2: Add the number of scores in both treatment conditions together.
22 scores (from treatment condition 1) + 22 scores (from treatment condition 2) = 44 scores

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Answer:

Option (B) x = 15 , y = 7 , z = 5

Step-by-step explanation:

Options in the question:

(A) x = 10 , y = 27 , z = 5

(B) x = 15 , y = 7 , z = 5

(C) x = 15 , y = 7 , z = 8

(D) x = 12 , y = 7 , z = 4

For this question, Trial and Error meathod is easier to solve.

Numbers on the First Row = 4 , 1 , 6  |  97

Numbers on the Second Row = 1 , 5 , 1  |  55

Numbers on the Third Row = 8 , -1 , 1  |  118

We should multiply the values with a variable to all the numbers on each row. Except the fourth number.

So, it will become —

Numbers on the First Row = 4x , 1y , 6z  |  97

Numbers on the Second Row = 1x , 5y , 1z  |  55

Numbers on the Third Row = 8x , -1y , 1z  |  118

Now, we will add all the First number in all the rows.

So, it will become —

13x , 5y , 8z  |  270

Let’s use the Trial and Error meathod.

Option (A) says that

  (13 * 10) + (5 * 27) + (8 * 5) = 270

= 130 + 135 + 40 = 270

= 305 ≠ 270

So, Option (A) is incorrect.

Option (B) says that

  (13 * 15) + (5 * 7) + (8 * 5) = 270

= 195 + 35 + 40 = 270

= 270 = 270

So, Option (B) is correct.

We now already know the answer but we will continue all the options for clarification.

Option (C) says that

  (13 * 15) + (5 * 7) + (8 * 8) = 270

= 195 + 35 + 64 = 270

= 294 ≠ 270

So, Option (C) is incorrect.

Option (D) says that

  (13 * 12) + (5 * 7) + (8 * 4) = 270

= 156 + 35 + 32 = 270

= 223 ≠ 270

So, Option (D) is incorrect.

The remaining Option is Option (B) x = 15 , y = 7 , z = 5

Hope my answer helps you ✌️

Therefore, the 90% confidence interval for the proportion of medical malpractice lawsuits that are dropped or dismissed is (0.635, 0.695).

To construct a confidence interval for the proportion of medical malpractice lawsuits that are dropped or dismissed, we can use the following formula:

CI = p ± z*sqrt((p*(1-p))/n)

where:

- p is the sample proportion of lawsuits that are dropped or dismissed (p = 732/1100 = 0.665)

- z* is the critical value of the standard normal distribution at a 90% confidence level (from a standard normal distribution table, z* = 1.645 for a 90% confidence level)

- n is the sample size (n = 1100)

Substituting the values into the formula, we get:

CI = 0.665 ± 1.645*sqrt((0.665*(1-0.665))/1100)

  = 0.665 ± 0.030

Therefore, the 90% confidence interval for the proportion of medical malpractice lawsuits that are dropped or dismissed is (0.635, 0.695). This means that we can be 90% confident that the true proportion of lawsuits that are dropped or dismissed is between 0.635 and 0.695.

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Step-by-step explanation:

the given speed is

63 cm / 2 days

1 m = 100 cm

therefore, m = cm/100.

so,

63 cm = 0.63 m

1 day = 24 h

therefore,

2 days = 24×2 = 48 h

so, we have a speed of

0.63 m / 48 h

we need to get the speed of meters in 1 hour.

so, we need to do a normal fraction operation.

e.g. when we have 43/10, but we want to have 1 in the denominator (bottom part).

what do we do ? well, we divide top and bottom (to keep the total value of the fraction unchanged) by 10 and get

4.3/1 = 4.3

we do the same with

0.63 m / 48 h

as we want to have only 1 hour in the denominator.

we divide top and bottom by 48 :

0.63/48 / 1 h = 0.013125 m/h ≈ 0.01 m/h

False. The term "undisturbed" refers to the state of the soil or sediment sample before it is collected.

An undisturbed sample is one that has not been altered or disturbed in any way during the sampling process.

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The correct statement for the given quadratic equation x² - 6x + 2 = 0 is the graph of the quadratic equation has a minimum value. Hence, correct option is C.

The graph of the quadratic equation has a maximum or minimum value depending on the sign of the leading coefficient. In this case, the leading coefficient is positive, which means the graph of the quadratic equation opens upwards and has a minimum value.

The extreme value is not at the point (7,-3) or (3,-7) because those points are not on the graph of the equation.

The solutions of the equation can be found using the quadratic formula

x = [-(-6) ± √((-6)² - 4(1)(2))] / (2(1))

x = [6 ± √(28)] / 2

x = [6 ± 2√7] / 2

x = 3 ± √7

Therefore, the correct statement is C.

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It will take 180 minutes to wash, dry, and fold four loads of laundry using a pipelining approach.

Using a pipelining approach for laundry, we can complete the tasks more efficiently by dividing them into stages. Let's break it down step by step:

1. Washing: Let's assume it takes 30 minutes to wash a single load of laundry.
2. Drying: Let's assume it takes 45 minutes to dry a single load of laundry.
3. Folding: Let's assume it takes 15 minutes to fold a single load of laundry.

Now, using the pipelining approach:

1. Load 1: Wash (30 minutes) → Dry (45 minutes) → Fold (15 minutes) = 90 minutes
2. Load 2: Wash (30 minutes) → Dry (45 minutes) → Fold (15 minutes)
3. Load 3: Wash (30 minutes) → Dry (45 minutes) → Fold (15 minutes)
4. Load 4: Wash (30 minutes) → Dry (45 minutes) → Fold (15 minutes)

The total time taken for four loads of laundry using a pipelining approach will be:
- Time to wash, dry, and fold Load 1: 90 minutes
- Time to wash Load 2: 30 minutes (as drying and folding of Load 1 can be done simultaneously)
- Time to wash Load 3: 30 minutes (as drying and folding of Load 2 can be done simultaneously)
- Time to wash Load 4: 30 minutes (as drying and folding of Load 3 can be done simultaneously)

Total time = 90 + 30 + 30 + 30 = 180 minutes

It will take 180 minutes to wash, dry, and fold four loads of laundry using a pipelining approach.

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7 seconds after inflation has begun, the volume of the balloon is increasing at a rate of approximately 2079.68 cubic inches per second.

The formula for the volume of a sphere is V = (4/3)πr^3. Since the radius of the spherical balloon is increasing at a constant rate of 1.5 inches per second, we can find the rate of change of the volume with respect to time by taking the derivative of the volume formula with respect to time:

dV/dt = 4πr^2(dr/dt)

At t = 7 seconds, we know that dr/dt = 1.5 inches per second, and we can find r by using the fact that the balloon is being inflated, so r = 1.5t = 1.5(7) = 10.5 inches. Substituting these values into the equation above, we get:

dV/dt = 4π(10.5)^2(1.5) = 2209.4π cubic inches per second

Therefore, the rate at which the volume of the balloon is increasing 7 seconds after inflation has begun is approximately 2209.4π cubic inches per second.

To find the rate at which the volume of the balloon is increasing 7 seconds after inflation has begun, we will use the given information and the formula for the volume of a sphere.

1. The formula for the volume of a sphere is V = (4/3)πr³, where V is the volume and r is the radius.

2. The radius of the balloon is increasing at a constant rate of 1.5 inches per second. This means that dr/dt = 1.5 inches per second (the rate of change of the radius with respect to time).

3. We need to find dV/dt, the rate of change of the volume with respect to time, at t = 7 seconds.

4. First, we need to find the radius of the balloon at t = 7 seconds. Since the radius is increasing at a rate of 1.5 inches per second, after 7 seconds, the radius will have increased by 1.5 * 7 = 10.5 inches.

5. Now we will differentiate the volume formula with respect to time: dV/dt = d/dt[(4/3)πr³]. Using the chain rule, we get dV/dt = (4πr²)(dr/dt).

6. We know the radius at t = 7 seconds is 10.5 inches and dr/dt = 1.5 inches per second. Plug these values into the equation: dV/dt = (4π(10.5)²)(1.5).

7. Calculate dV/dt: dV/dt ≈ 2079.68 cubic inches per second.

So, 7 seconds after inflation has begun, the volume of the balloon is increasing at a rate of approximately 2079.68 cubic inches per second.

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The number of hours it will take the airplane to fly the given distance would be = 4.5 hours

To calculate the number of hours that can be used for the distance, the following needs to be done. That is;

The number of hours it take to complete 3600 miles = 3 hours

Therefore the number of hours it will take to complete 5400miles = X hours.

That is;

3600 miles = 3 hours

5400 miles = X hours

make X the subject of formula;

X = 5400×3/3600

= 16,200/3600

= 4.5 hours.

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The three elements of the fire triangle are heat, fuel, and oxygen.

All three elements are present in various locations such as kitchens, factories, workshops, and even in nature such as forests and grasslands. For example, in a kitchen, the stove provides heat, cooking oil or gas is the fuel, and air provides oxygen.

In a factory, welding machines generate heat, combustible materials serve as fuel, and air provides oxygen. In a forest, the hot summer sun provides heat, dry leaves and branches serve as fuel, and air provides oxygen. Whenever all three elements are present, there is an increased risk of fire, and proper precautions should be taken to prevent fires from starting.

For example, if there is a dry and combustible material (fuel) that is exposed to a high temperature or a spark (heat), and there is an ample supply of oxygen in the air, then all three elements of the fire triangle are present and a fire can start. Another example might be a gas stove with an open flame (heat), a can of flammable cooking oil (fuel), and a well-ventilated kitchen (oxygen).

When these three elements are present together, there is an increased risk of fire.

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The 90th percentile for the random sample of size 16 taken from the normal population with a mean of 100 and a variance of 4 is approximately 100.64

To find the 90th percentile of a random sample of size 16 taken from a normal population with a mean of 100 and a variance of 4, follow these steps:

1. Identify the population mean (μ) and variance ([tex]σ^{2}[/tex]). In this case, μ = 100 and [tex]σ^{2}=4[/tex].
2. Calculate the population standard deviation (σ) by taking the square root of the variance: σ = √4 = 2.
3. Since the sample size (n) is 16, the standard error (SE) is calculated by dividing the population standard deviation by the square root of the sample size: [tex]SE= \frac{σ}{\sqrt{n} } = \frac{2}{\sqrt{16} } = \frac{2}{4} = 0.5[/tex].
4. Next, determine the z-score corresponding to the 90th percentile. You can use a z-table or an online calculator. The z-score for the 90th percentile is approximately 1.28.
5. Multiply the z-score by the standard error: 1.28 (0.5) = 0.64.
6. Finally, add this product to the population mean: 100 + 0.64 = 100.64.

The 90th percentile for the random sample of size 16 taken from the normal population with a mean of 100 and a variance of 4 is approximately 100.64.

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Answer:

144 degrees

Step-by-step explanation:

To convert radians to degrees, multiply by

180/π, since a full circle is 360° or 2π radians.(4π/5) ⋅180°/ π

Cancel the common factor of π. 4/5 ⋅ 180

Cancel the common factor of 5. 4 ⋅ 36

Multiply 4 by 36.

144

Convert to a decimal. 144°

We can say that Gustavo found a higher frequency of defective calculators than what the company claimed was expected.

The company claimed that the probability of a defective calculator was 1% per 1000 calculators. This means that they expected 1% of the calculators to be defective.

So, the predicted frequency of defective calculators in the sample of 1000 calculators would be:

Predicted frequency = 1% of 1000 = 0.01 x 1000 = 10

However, Gustavo found 15 defective calculators out of 1000. This is higher than the predicted frequency of 10 defective calculators.

So, the actual frequency of defective calculators in Gustavo's sample is 15/1000 = 0.015, or 1.5%. This is higher than the expected frequency of 1%.

It's worth noting that the sample size of 1000 calculators is quite large, so it's possible that the actual frequency is closer to the expected frequency than it appears in this particular sample. However, based on this sample, we can say that Gustavo found a higher frequency of defective calculators than what the company claimed was expected.

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