Let C = {factors of 12}
Work out n(C)

The percentage of time users will attempt to operate the opener outside its operating limit is approximately 96.56%.

To calculate the percentage of time users will attempt to operate the opener outside its operating limit, we need to determine the probability that a distance exceeds 50 feet.

We can use the properties of the normal distribution to solve this problem. Given that the distances are normally distributed with a mean of 30 feet and a standard deviation of 11 feet, we can calculate the z-score corresponding to a distance of 50 feet.

The z-score formula is:

z = (x - μ) / σ

where x is the value we want to calculate the z-score for, μ is the mean, and σ is the standard deviation.

Let's calculate the z-score:

z = (50 - 30) / 11

z = 20 / 11

z ≈ 1.82

Next, we can use a standard normal distribution table or a calculator to find the probability corresponding to a z-score of 1.82. This probability represents the percentage of time users will attempt to operate the opener outside its operating limit.

From the standard normal distribution table or using a calculator, the probability corresponding to a z-score of 1.82 is approximately 0.9656, or 96.56%.

Therefore, users will attempt to operate the opener outside its operating limit approximately 96.56% of the time.

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Both methods are correct and either one can be used to evaluate the expression 17.

Both Kode and Elijah are using the distributive property to evaluate the expression 17(4+15).

The distributive property states that a(b+c) = ab + ac.

Kode's method:

17(4+15) = (17*4) + (17*15) = 68 + 255 = 323

Elijah's method:

17(4+15) = 17*19 = 323

Both students get the same answer of 323.

Therefore, both methods are correct and either one can be used to evaluate the expression 17(4+15).

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Answer:

0.84306608

Step-by-step explanation:

The probability of an event, e, occurring exactly r times over n trials follows the formula

(n combination r) * p^r * q ^ (n-r)

with p being the probability the event will occur and q being the probability the event will not occur.

I assume you have a calculator/can find one online that can do combinations.

Here, we want to figure out if you get:

- 0 tails

- 1 tail

- 2 tails

If you get 3 or 4 tails, we are getting more than the 2 tails desired

For 0 tails:

- p is the probability a tail will occur = 0.38

- we want it to occur 0 times, so r = 0

- q is (1-p) = 1- 0.38 = 0.62

- we have 4 trials, as we flip it 4 times

(n combination r) * p^r * q ^ (n-r) = (4 combination 0) * (0.38) ^0 * (0.62) ^(4-0) = 1 * (0.38) ^0 * (0.62) ^(4-0) = 0.14776336

For 1 tail:

- p = 0.38, q = 0.62 as with 0 tails

- r = 1, n = 4

(n combination r) * p^r * q ^ (n-r) = (4 combination 1) * (0.38) ^1 * (0.62) ^(4-1) = 4* (0.38) ^1 * (0.62) ^(4-1) = 0.36225856

For 2 tails:

- p = 0.38, q = 0.62 as with 0 tails

- r = 2, n = 4

(n combination r) * p^r * q ^ (n-r) = (4 combination 2) * (0.38) ^1 * (0.62) ^(4-2) = 6* (0.38) ^2 * (0.62) ^(4-2) = 0.33304416

add our 3 probabilities together

0.33304416 + 0.36225856 + 0.14776336 = 0.84306608 as our answer

Answer: $5 their are 36 donuts and 12 x 3 is 36 and 5 x 3 is 15

First, we want to note two things:

We can describe this with an inequality:  x ≥ -10
Be sure you use ≥ and not >, since -10 is included.

We can describe this with interval notation: [ -10, infty )
Be sure you use [ and not ( on -10, since -10 is included.

You can also use set-builder notation: { x | x ≥ -10 }

Find his speed by dividing 366 miles by 6 hours:

366/6 = 61 miles per hour.

Divide 427 miles by 61 miles per hour to find the time:

427/61 = 7 hours

The answer is 7 hours.

Answer:

8 1/2 hours

Step-by-step explanation:

Sped

A quantity that is difficult to measure with certainty is called an uncertain or imprecise quantity.

This term refers to a situation where the exact value of a quantity cannot be determined accurately or with complete confidence.

There are various reasons why a quantity may be difficult to measure with certainty. Some of the common factors include:

1. Measurement limitations: Certain quantities may be inherently challenging to measure due to technical limitations of the measuring instruments or techniques available. This can include situations where the quantity is extremely small, extremely large, or falls within a range that is difficult to capture accurately.

2. Experimental errors: When conducting experiments or measurements, there is always a degree of error or uncertainty associated with the measurements. This can be due to limitations in the instruments used, human error in reading or recording measurements, or other external factors that affect the measurement process.

3. Inherent variability: Some quantities may exhibit inherent variability or fluctuations, making it difficult to determine their precise value. For example, in complex systems or natural phenomena, certain variables may change over time or exhibit random fluctuations that make it challenging to measure them with certainty.

4. Conceptual limitations: In certain cases, the nature of the quantity itself may pose challenges to precise measurement. This can occur when dealing with abstract or subjective concepts that are difficult to quantify objectively.

In scientific and engineering fields, the uncertainty associated with measurements is often quantified and expressed using statistical or probabilistic methods. This helps in understanding the range of possible values and the confidence level associated with the measurements.

It is important to recognize and account for uncertainties when dealing with imprecise quantities. Properly understanding and managing uncertainty is crucial for making informed decisions, interpreting experimental results, and ensuring the validity and reliability of scientific findings.

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Residual Plot A indicates that the linear model is not appropriate because the fanned pattern shows that the model's predicting power decreases as the values of the explanatory variable increases. Residual Plot B indicates that the linear model is appropriate because the scattered residuals suggest a linear relationship.

Residual Plot A shows a fanned pattern which indicates that the linear model is not appropriate. This means that the model's predicting power decreases as the values of the explanatory variable increases. This suggests that the relationship between the dependent and independent variables is not linear and a different model may be necessary. Residual Plot B, on the other hand, shows a scattered pattern which suggests that the linear model is appropriate. The scattered pattern indicates that the data points are randomly distributed, which is a sign of a linear relationship. This indicates that the linear model is an appropriate fit for the data.

the complete question is :

Tell what each of the residual plots to the right indicates about the appropriateness of the linear model that was fit to the data. (a). Choose the best answer for residuals plot A. The fanned pattern indicates that the linear model is not appropriate. The model's predicting power decreases as the values of the explanatory variable increases. B. The fanned pattern indicates that the linear model is not appropriate. C. The model's predicting power increases as the values of the explanatory variable increases. The scattered residuals plot indicates an appropriate linear model. (b). Choose the best answer for residuals plot A. The scattered residuals plot indicates an appropriate linear model. B. The curved pattern in the residuals plot indicates that the linear model is not appropriate. The relationship is not linear. C. The fanned pattern indicates that the linear model is not appropriate. The model's predicting power decreases as the values of the explanatory variable increases.

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Answer: 3

Step-by-step explanation: got it right on edge

Answer:

3

Step-by-step explanation:

edge 2020

Answer:

the answer would be 2 * 2 * y √2 * 5* 7 * y

Step-by-step explanation:

There are 15 ways for Minnie to select the 4 subjects and decide the order of doing homework. Minnie has 6 subjects to finish homework for including calculus and statistics.

Out of these 6 subjects, she wants to finish homework for 4 subjects.

Since she wants to finish statistics before calculus, there are only 2 ways to select the subjects to do first i.e. either statistics or calculus.

Statistics must be one of the subjects selected to finish homework for today and hence there are only 5 subjects left to choose from for the other 3 subjects.

So, Minnie has to select 3 subjects from a total of 5 subjects which can be done in 5C3 ways.

5C3 = 10

There are 10 ways for Minnie to choose the remaining 3 subjects.

Now, since Minnie wants to finish statistics before calculus, there is only one possible way to arrange these two subjects in the order she wants.

Hence, there are only 2 possible ways to arrange these two subjects for doing homework.

To arrange the remaining 2 subjects,

Minnie has 2 options.

Hence, there are 2 ways to arrange the last 2 subjects.

So, total number of ways to select the 4 subjects and then decide the order of doing homework is:

10 × 2 × 2 = 40.

Therefore, there are 15 ways for Minnie to select the 4 subjects and decide the order of doing homework.

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The probability that the third digit is odd given that the first two digits are odd is 8/45.

To solve this problem, we first need to find the total number of possible combinations. Since the locker combination has three nonzero digits with no repetition, we can choose the first digit in 9 ways (since it cannot be zero), the second digit in 4 ways (since it must be odd and cannot be the same as the first digit), and the third digit in 5 ways (since it can be any odd digit except for the two already chosen). Therefore, the total number of possible combinations is 9 x 4 x 5 = 180.

Next, we need to find the number of combinations where the first two digits are odd and the third digit is also odd. We have already determined that there are 4 choices for the second digit. Since the first digit must also be odd, there are 4 odd choices for the first digit. Once the first two digits have been chosen, there are only 2 odd choices left for the third digit (since one odd digit has already been used). Therefore, there are 4 x 4 x 2 = 32 combinations where the first two digits are odd and the third digit is also odd.

Finally, we can calculate the probability by dividing the number of favorable outcomes (32) by the total number of possible outcomes (180):

P(third digit is odd | first two digits are odd) = 32/180 = 8/45

Therefore, the probability that the third digit is odd given that the first two digits are odd is 8/45.

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Answer:

half eaten pizza has greater circumference

Step-by-step explanation:

full eaten pizza's circumference = 2πr

= 2 * 3.14 * 7 = 43.96 inches

half eaten pizza's circumference = πd

= 3.14 * 20

=62.8 inches

Answer:

Step-by-step explanation:

Express 2x2 – 3x – 5 as the product of two binomial factors.

factorize the given expression

2x^2 – 3x – 5

2x^2 – 5x+2x – 5

x(2x-5)+ 1 (2x-5)

(2x-5) (x+1)

Hence the expression as the product of two binomial is (2x-5) (x+1)

This shows that 24 gauge wire is needed, which is equivalent to 0.205 mm² wire size. Hence the correct option is D. 12

Given: Voltage (V) = 28,

Current (I) = 20A,

Distance (d) = 18.3 meters

To determine the wire size, we have to find the required wire gauge using the below formula;

R = ρ L / A

Where R = resistance, ρ = resistivity of wire, L = length of wire, A = cross-sectional area of wire.

Rearrange the above formula to find A, A = ρ L / R

From Ohm's law, R = V / I

= 28 / 20

= 1.4Ω

Resistivity of wire is given as 1.72 x 10^−8 Ω·m.

Convert meters to feet using the conversion factor 1 meter = 3.281 feet, d = 18.3 m = 60 ft

Substitute these values to find the cross-sectional area of the wire:

A = (1.72 x 10^−8 Ω·m) (60 ft) / 1.4 Ω≈ 7.37 × 10^−7 m²

= 7.37 × 10^−3 cm²

The cross-sectional area of the wire is in square meters and we need to convert it to square centimeters.

We can use the conversion factor, 1m² = 10^4 cm² to get the answer in square centimeters.

A = 7.37 × 10^−7 m²

= 7.37 × 10^−3 × 10^4 cm²

= 0.0737 cm²

Refer to the American Wire Gauge (AWG) standard table, which is commonly used for electrical wire sizes in North America.

The gauge size is given as 10.58 × (d^−0.5), where d is the wire diameter in circular mils.

1 mil is equal to 1/1000 of an inch or 0.0254 millimeters.

Therefore, 1 circular mil is the area of a circle with a diameter of 1 mil.

Rearrange the formula to find d:

d = 10^(A/10.58) / 1000

Substitute A = 0.0737 cm² to find the wire size:

d = 10^(0.0737/10.58) / 1000

= 0.216 mm² or 24 AWG

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Answer:

IL and JK

Step-by-step explanation:

We can see that those line segments have the little arrow

This arrow indicates that the two segments are parallel

Answer:

Its option D :)

---

28° + y + 36° = 180°

Answer:

D

I believe the second one is none of the above

Step-by-step explanation:

61-27

Answer:

34 degrees.

Step-by-step explanation:

m<AOC - m<BOC = <AOB = 61 - 27 = 34

for the second one i think it's none.

The value of the t-test statistic for testing whether the effect of passing yards on salary is equal to 0 is 8.041. Therefore, the correct answer is (d) 8.041.

In order to solve this problem, we need to use the t-test formula: t = (b1 - 0) / SE(b1)

where b1 is the slope coefficient (0.051), and

SE(b1) is the standard error of the slope coefficient.

The standard error can be found using the formula: SE(b1) = sb1 / √(n-2)

where sb1 is the standard error of the estimate for the slope coefficient, and

n is the sample size.

The standard error of the estimate can be found using the formula: sb1 = √(SSR / ((n-2) * Sxx))

where SSR is the sum of squared residuals, and

Sxx is the sum of squared deviations of X from its mean.

We can use the R² value to find SSR: SSR = (1 - R²) * SST

where SST is the total sum of squares.

SST can be found using the formula:SST = sum(y - ybar)²

Now we have all the necessary information to find the t-test statistic:t = (0.051 - 0) / (0.014 / √(32-2))t = 8.041

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Solution:

Let's make,

mechanic #1's rate = x

mechanic #2's rate = y

Note that their rate is dollars per hour.

Now, mechanic #1 worked for 20 hours. Then, we get the following equation:

20x = money earned by mechanic #1

On the other hand, mechanic #2 worked for 15 hours. Then, we get the following equation:

15y = money earned by mechanic #2

together they charged a total of $2250. So the amount of money earned by both mechanics is:

20x + 15y = 2250 EQUATION 1

On the other hand, the sum of the two rates was:

x + y = 125 EQUATION 2

From the equation, if we solve for x, we get:

x = 125-y EQUATION 3

plug (125-y) in for "x" in equation 1 to get everything in terms of one variable:

20(125-y)+15y = 2250

this is equivalent to

2500-20y +15y = 2250

this is equivalent to

2500 -5y = 2250

this is equivalent to

-5y = 2250 -2500

this is equivalent to:

-5y = -250

or

5y = 250

solving for y, we get:

now, replacing this into equation 3, we get:

x = 125-y = 125 - (50) = 75

so that, we can conclude that the correct answer is:

mechanic #1 charged 75 $/hr

mechanic #2 charged 50 $/hr

The estimation of the equation 1/6 + 5/6  is 1 (option C).

For rounding a fraction to the nearest whole number, use the "rounding half up" rule if necessary.

To estimate the solution for the equation 1/6 + 5/6, we can round each fraction to the nearest whole number.

The fraction 1/6 is closer to 0 than it is to 1, so we will round it to 0.

The fraction 5/6 is closer to 1 than it is to 0, so we will round it to 1.

Now we can estimate the solution for the equation as follows:

0 + 1 = 1

Therefore, the estimated solution for the equation 1/6 + 5/6 is 1.

The correct answer is C. 1.

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Answer:

This proves that f is continous at x=5.

Step-by-step explanation:

Taking f(x) = 3x-1 and \(\varepsilon>0\), we want to find a \(\delta \) such that \(|f(x)-14|<\varepsilon\)

At first, we will assume that this delta exists and we will try to figure out its value.

Suppose that \(|x-5|<\delta\). Then

\(|f(x)-14| = |3x-1-14| = |3x-15|=|3(x-5)| = 3|x-5|< 3\delta\).

Then, if \(|x-5|<\delta\), then \(|f(x)-14|<3\delta\). So, in this case, if \(3\delta \leq \varepsilon\) we get that \(|f(x)-14|<\varepsilon\). The maximum value of delta is \(\frac{\varepsilon}{3}\).

By definition, this procedure proves that \(\lim_{x\to 5}f(x) = 14\). Note that f(5)=14, so this proves that f is continous at x=5.

Step-by-step explanation:

Convert each fraction by setting up proportion out of 100.

\( \frac{60}{90} = \frac{?}{100} \)

\( \frac{78}{150} = \frac{?}{100} \)

\( \frac{75}{120} = \frac{x}{100} \)

Cross multiply each fraction. let x represent the missing number.

\(6000 = 90x\)

\(7800 = 150x\)

\(7500 = 120x\)

Solve for x

For the first equation.

\(x = 66.66666\)

For the second equation

\(x = 52\)

For the third equation,

\(x = 62.5\)

Round each missing value to the nearest whole value and add the % sign.

60/90=67%

78/150=52%

75/120=63%

He scored the highest on his English test.

Answer:

2x4   -  5x1x3 {bracket means times] =8-15=-7

Step-by-step explanation:

2f=2xf=2x4=8

-

g=5x1x3=15

=8-15

=-7

Answer: x=-6

Step-by-step explanation:

Add 5 to both sides to get 2x by itself

Yes, subtract 1 from both sides to get 3x by itself so you can subtract 2x as to not get a negative x value

One common mistake would be to accidentaly adding or subtracting 1 or 5 when they are supposed to be added/subtracted. To avoid this just go back and check your awnser by plugging it in.

True, the Greek letter used to represent the probability of a Type I error is alpha ().

The Greek letter alpha (α) is indeed used in statistics, but it represents the level of significance chosen for a statistical test. The level of significance is the probability of rejecting the null hypothesis when it is actually true. The probability of making a Type I error (rejecting the null hypothesis when it is true) is equal to the level of significance (α) chosen for the test.

Therefore, alpha is not used to represent the probability of a Type I error directly, but it is related to it. The probability of a Type I error depends on the chosen level of significance and the specific hypothesis test being conducted.

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True. The Greek letter used to represent the probability of a Type I error is alpha

This is a statement and not a question. However, if you are asking whether the statement "the Greek letter used to represent the probability of a type i error is alpha (α)" is true or false, the answer is that it is partially true. While the Greek letter α is commonly used to represent the significance level (or the probability of a Type I error) in hypothesis testing, it is not the only letter that can be used.

Other letters such as β and γ may also be used in certain contexts. So the complete answer would be a long answer that explains the partial truth of the statement.

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