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A contractor bought 8.2 ft? of sheet metal. She has used 2.3 f? so far and has $177 worth of sheet
metal remaining. The equation 8.2x - 2.3x = 177 represents how much sheet metal is remaining and
the cost of the remaining amount. How much does sheet metal cost per square foot?
Sheet metal costs $ per square foot.

Answer: \(2\log_{9}(5)=\log_{9}(25)\)

Step-by-step explanation:

Recall the following property of logarithm:

\(n\log_{a}(b)=\log_{a}(b^n)\)

So, by using the property above, it follows:

\(2\log_{9}(5)=\log_{9}(5^{2})=\log_{9}(25)\)

A hypothesis test may be used to test whether the mean tax rates for the two genders differ because-

In statistics, hypothesis testing is the process by which a predicting the occurrence an assertion about a population parameter. The analyst's methodology is determined by the characteristics of the information and the purpose of the analysis.

Some key features regarding the hypothesis testing are-

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Answer:

y+6=2(x-3)

Step-by-step explanation:

y-y1=m(x-x1)

y-(-6)=2(x-3)

y+6=2(x-3)

I think that's ur answer

Answer:

The degrees of freedom, Df = The number of bags produced on Monday - 1

Step-by-step explanation:

The number of degrees of freedom is the limiting number of values that are logically not influenced by other values such that they are capable of having variation

The degrees of freedom = The sample size - 1 = N - 1

Therefore, the degrees of freedom, Df = The number of bags produced on Monday - 1

Answer:

A.

type A: Y= 15x +36

type B: Y= 10x + 48

B.

15x +36= 10x+48

5x=12

x= 2.4

2.4 years

C.

72 inches

The probability that exactly 6 individuals in the sample favor this president candidate is 0.2068.

The area of mathematics known as probability deals with the outcomes of random events. Probability refers to a result's chance or potential. It clarifies the likelihood that a specific occurrence will take place. We frequently say things like, "He will probably pass the test," "There is very little chance of receiving a storm tonight," and "Most likely the price of onions will increase once more." We substitute the word probability for every instance of chance, uncertainty, maybe, likely, etc. in these statements. In essence, probability is the ability to anticipate an outcome based on the variety and quantity of potential possibilities or the analysis of historical data.

Given,

P( favor president) = 0.4

P( does not favor president) = 0.6

P( x = 6)

= ¹⁵C₆ (0.4)⁶(0.6)⁶⁻³

= 15!/6!9! (0.6)³(0.4)⁶

= 0.2068916

= 0.2068

The probability that exactly 6 individuals in the sample favor this president candidate is 0.2068.

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Answer:

a

Step-by-step explanation:

Answer:

Step-by-step explanation:

Correct option is C

The convolution of $e^{at}$ and $e^{bt}$ when $a=b$ is zero

When computing the convolution of two functions, we use the following formula:

$$(f * g)(t) = \int_{-\infty}^{\infty} f(\tau) g(t-\tau) d\tau$$

In this case, we are given $f(t) = e^{at}$ and $g(t) = e^{bt}$, where $a = b$. So we have:

$$(f * g)(t) = \int_{-\infty}^{\infty} e^{at} e^{b(t-\tau)} d\tau$$

Simplifying the exponent, we get:

$$(f * g)(t) = \int_{-\infty}^{\infty} e^{(a+b)\tau} e^{-bt} dt$$

Now, we can integrate:

$$(f * g)(t) = \frac{1}{a+b} e^{(a+b)t} \Big|_{-\infty}^{\infty} = \frac{1}{a+b} (e^{(a+b)\infty} - e^{(a+b)(-\infty)})$$

Note that this expression is only defined if $a+b$ is negative, since otherwise the exponential terms will blow up to infinity. But if $a+b<0$, then we have:

$$(f * g)(t) = \frac{1}{a+b} (0 - 0) = 0$$

Therefore, the convolution of $e^{at}$ and $e^{bt}$ when $a=b$ is zero.

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The probability that the sample proportion is between 0.2 and 0.42 can be calculated using the standard normal distribution.

To calculate the probability, we need to assume that the sample proportion follows a normal distribution. This assumption holds true when the sample size is sufficiently large and the conditions for the central limit theorem are met.

First, we need to calculate the standard error of the sample proportion. The standard error is the standard deviation of the sampling distribution of the sample proportion and is given by the formula sqrt(p(1-p)/n), where p is the estimated proportion and n is the sample size.

Next, we convert the sample proportion range into z-scores using the formula z = (x - p) / SE, where x is the given proportion and SE is the standard error. In this case, we use z-scores of 0.2 and 0.42.

Once we have the z-scores, we can use a standard normal distribution table or a statistical software to find the corresponding probabilities. The probability of the sample proportion falling between 0.2 and 0.42 is equal to the difference between the two calculated probabilities.

Alternatively, we can use the z-table to find the individual probabilities and subtract them. The z-table provides the cumulative probabilities up to a certain z-score. By subtracting the lower probability from the higher probability, we can find the desired probability.

In conclusion, the probability that the sample proportion is between 0.2 and 0.42 can be calculated using the standard normal distribution and z-scores. This probability represents the likelihood of observing a sample proportion within the specified range.

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Answer:

Use the formula SA=2×length×width+2 length× height+2×height×width. With this I believe your answer should be 13.5. Sorry if it's wrong since the answer choices don't line up but thats the only way it makes sense for me.

Answer:

170$

Step-by-step explanation:

150+20=170

Answer:

Step-by-step explanation:

170

Answer:

Step-by-step explanation:

its 190 because you started on page 4 and you add 186

Xds for the given straight line segment and parabolic curve are Xds = (2/9) (1+(1.5x)²)\(^(3/2)\)+ C.

The parabolic curve x =t, y =12, from (0,0) to (2,4), for the straight line segment, x ds, use the formula:

Xds = ∫√(1+dy/dx²)dx.

For the given straight line segment, x=t;y= from (0,0) to (20,4), the equation is y = 4x/20, or y = 0.2x.

Therefore, dy/dx = 0.2.

Xds = ∫√(1+(0.2)²)dx= ∫√(1+0.04)dx= ∫√(1.04)dx

Evaluating this integral using the substitution method, let u = 1.04x,

we have:

Xds = 1/√1.04 ∫√u du

= 1/√1.04ˣ(2/3) u\(^(3/2)\) + C

= 1/√1.04 ˣ (2/3) (1.04x)\(^(3/2)\) + C

= 0.9626(1.04x)\(^(3/2)\) + C.

For the given parabolic curve x =t, y =12, from (0,0) to (2,4), the equation is y = 12x²/16 = 0.75x².

Therefore, dy/dx = 1.5x. Substituting this value in the formula above, we have:

Xds = ∫√(1+(1.5x)²)dx

Again, using the substitution method, let

u = 1+(1.5x)²,

we have:

Xds = (2/3)∫√u du= (2/3) ˣ (1/3) u\(^(3/2)\) + C= (2/9) (1+(1.5x)²)\(^(3/2)\) + C.

Therefore, Xds for the given straight line segment and parabolic curve are:

For straight line segment:

Xds = 0.9626(1.04x)\(^(3/2)\) + C.For parabolic curve:

Xds = (2/9) (1+(1.5x)²)\(^(3/2)\)+ C.

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This is a budgeting exercise. Based on the estimated cost of college which was set at $58,000, the following steps indicate how I intend to pay for college:

                                        $58,000

Budgeting is simply the process of outlining the total expense requirements of an individual person or a corporate entity and how those expenses will be satisfied and efficiently allocated.

From the above, the total sum of $58,000 will be satisfied from three sources:

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Answer:

first second and fifth are the answers

The relative frequency of the class interval 65-75 is .20.

The word 'relative' is used to indicate that an event is being considered in relation or in proportion to something else.

Frequency is a way to measure how often a particular event occurs. Relative frequency, on the other hand, is a way to measure how often a particular event occurs against total occurrences.

Given that: 50 participants scored between 65 and 75 on a test.

Hence,

The relative frequency of the class interval 65-75 = 75 - 65 = 20

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Answer:

B

Step-by-step explanation:

the other answers don't make sense

b. Linear programming model is the correct option.

A linear programming model is a mathematical technique used to find the best outcome in a given set of constraints. In this case, Manders Manufacturing Corporation is trying to determine the optimal product mix for its two products, metal (M) and scrap metal (S), based on certain constraints. The objective is to maximize the profit, represented by the function Z = $30M + $70S.

The constraints are represented by the inequalities:

3M + 2S ≤ 15

2M + 4S ≤ 18

These constraints define the limitations on the production of metal and scrap metal. The model aims to find values of M and S that satisfy these constraints while maximizing the objective function.

Using linear programming techniques, the corporation can solve this model to find the optimal values for M and S that will maximize their profit. This approach allows them to make data-driven decisions and allocate their resources efficiently. By formulating the problem as a linear programming model, Manders Manufacturing Corporation can make informed choices about the optimal product mix to achieve their business objectives.

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Answer:

y=x-9

Step-by-step explanation:

Answer:

-1352x

Step-by-step explanation:

Because x never got a value and then so it stands there.

The correlation coefficient (r) can be calculated by using the following formula: r = (nΣXY - (ΣX)(ΣY)) / sqrt((nΣX² - (ΣX)²)(nΣY² - (ΣY)²))where X and Y are the variables, n is the number of observations, ΣXY is the sum of the products of paired scores, ΣX is the sum of X scores, ΣY is the sum of Y scores, ΣX² is the sum of squared X scores, and ΣY² is the sum of squared Y scores.

Given the value, it is mentioned that X and Y are uncorrelated.

The formula to calculate the correlation coefficient is:r = (nΣXY - (ΣX)(ΣY)) / sqrt((nΣX² - (ΣX)²)(nΣY² - (ΣY)²))where X and Y are the variables, n is the number of observations, ΣXY is the sum of the products of paired scores, ΣX is the sum of X scores, ΣY is the sum of Y scores, ΣX² is the sum of squared X scores, and ΣY² is the sum of squared Y scores.

When X and Y are uncorrelated, it means that the covariance between the two is zero, which means ΣXY = 0.

Using this information in the formula for correlation coefficient, we get:r = 0 / sqrt((nΣX² - (ΣX)²)(nΣY² - (ΣY)²))This simplifies to r = 0.

Summary:Thus, the correlation coefficient between X and Y is 0 when X and Y are uncorrelated.

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Answer:

Step-by-step explanation:

-23=-3X-8

We are given the following equation

Let us solve this equation for k

Step 1:

Multiply both sides of the equation by k

Step 2:

Subtract 8k from both sides of the equation

Step 3:

Add 10 to both sides of the equation

Step 4:

Finally, divide both sides of the equation by -4

Therefore, the value of k is equal to -5/2

Temperature of refrigerators - Cannot determine. Horsepower of race car engines - Ratio. Marital status of school board members - Nominal. Ratings of television programs - Ordinal. Ages of children enrolled in a daycare - Interval

The level of measurement for the temperature of refrigerators cannot be determined based on the given information. The temperature could potentially be measured on a nominal scale if the refrigerators were categorized into different temperature ranges. However, without further context, it is not possible to determine the specific level of measurement.

The horsepower of race car engines can be measured on a ratio scale. Ratio scales have a meaningful zero point and allow for meaningful comparisons of values, such as determining that one engine has twice the horsepower of another.

The marital status of school board members can be measured on a nominal scale. Nominal scales are used for categorical data without any inherent order or ranking. Marital status categories, such as "married," "single," "divorced," etc., can be assigned to school board members.

The ratings of television programs, such as "poor," "fair," "good," and "excellent," can be measured on an ordinal scale. Ordinal scales represent data with ordered categories or ranks, but the differences between categories may not be equal or measurable.

The ages of children enrolled in a daycare can be measured on an interval scale. Interval scales have equal intervals between values, allowing for meaningful differences and comparisons. Age, measured in years or months, can be represented on an interval scale.

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Answer:

82(-x-5)=26

-82x-410=26

-410-26=82x

-436/82=x

x=-218/41

Answer: \(m=\frac{y2-y1}{x2-x1}\)

Step-by-step explanation:

Choose two points and insert them for x and y.

(3,0) and (0,-4) will work

If you need extra help ask me, I'd be glad to help but i encourage you to try to solve it yourself

Answer:

1 A 4 three-course meal can be possible

2 An 8 two course meal can be available

Step-by-step explanation:

This is because the number of dessert is the lowest which is and the starter and main dishes are higher in number since only 4 desert can go around only a 4 three course meal is available.

2 This is because 5+8+4= 17. Since it's a two course meal 17÷2= 8.5. Meaning 8 meals are the only whole 2 course meal available

By applying the counting principle in combinatorics, we find that there are 160 different possible three-course meals and 92 different possible two-course meals in the given menu.

This question involves the concept of the counting principle, a fundamental principle in combinatorics. The principle states that if there are m ways to do one thing, and n ways to do another, then there are m*n ways of doing both.

In part a), a three-course meal consists of one starter, one main dish, and one dessert. To figure out the number of different meals possible, we multiply the number of options at each course: 5 starters * 8 main dishes * 4 desserts, which equals 160 different three-course meals.

In part b), a two-course meal consists of either a starter with a main dish, a starter with a dessert, or a main dish with a dessert. For each of these combinations, we multiply the number of possibilities at each course and then add the results together. Hence, (5 starters * 8 main dishes) + (5 starters * 4 desserts) + (8 main dishes * 4 desserts) equals 40 + 20 + 32, giving us 92 different two-course meals.

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