your brother's kids eat vegetables 43% of the time. your dog plays in the mud 38% of the time. if your brother's family visits for a dinner after a huge rainstorm, what is the probability that the kids eat their vegetables and your dog plays in the mud? round to the nearest thousandths.

The ratio of water and alcohol when the mixture in all containers is poured into the fourth container if the ratio of the volume of three buckets is 3:4:5 and if the ratio of water and alcohol is 1:4, 1:3, and 2:5 respectively is 53 : 157

Let the volume of the first container be 3x

the volume of the second container be 4x

the volume of the third container be 5x

In the first container,

the ratio of water and alcohol is 1:4

Alcohol = [tex]\frac{1}{5}[/tex] * 3x = 0.6x

Water = [tex]\frac{4}{5} *3x[/tex] = 2.4x

In the second container,

the ratio of water and alcohol is 1:3

Alcohol = [tex]\frac{1}{4}[/tex] * 4x = x

Water = [tex]\frac{3}{4} *4x[/tex] = 3x

In the third container,

The ratio of water and alcohol is 2:5

Alcohol = [tex]\frac{2}{7}[/tex] * 5x = [tex]\frac{10}{7}[/tex]x

Water = [tex]\frac{5}{7} *5x[/tex] = [tex]\frac{25}{7}[/tex]x

The total amount of alcohol = 0.6x + x + [tex]\frac{10}{7}[/tex]x

= [tex]\frac{21.2}{7}[/tex]

The total amount of water = 2.4x + 3x + [tex]\frac{25}{7}[/tex]x

= [tex]\frac{62.8}{7}[/tex]

The ratio of alcohol to water is [tex]\frac{21.2}{7}[/tex] : [tex]\frac{62.8}{7}[/tex]

= 53 : 157

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Assuming all else remains constant, increasing the sample size from 25 to 100 will generally result in a narrower confidence interval around the mean. increasing the sample size generally leads to a more precise estimate of the population mean, resulting in a narrower confidence interval around the mean.

This can be since the standard blunder of the cruel, which measures the changeability of the test cruel around the populace cruel, diminishes as the test estimate increments. As the standard blunder diminishes, the edge of the blunder (which is based on the standard mistake and the chosen certainty level) diminishes, coming about in a smaller certainty interim.

The relationship between the test measure and the width of the certainty interim is contrarily corresponding. This implies that as the test measure increments, the width of the certainty interim diminishes, and as the test measure diminishes, the width of the certainty interim increments.

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Answer:

C

Step-by-step explanation:

common number of students would be if it was like 50 left early every other day but average would mean averagely yk and the mean is 56.5

To test for a linear relationship in simple linear regression (SLR), we make an inference on the parameter "slope." A significant slope indicates a linear relationship between the independent and dependent variables.

The parameter we make inferences on in simple linear regression (SLR) to test for a linear relationship is the slope. The slope represents the change in the response variable for a one-unit increase in the predictor variable, and it indicates the strength and direction of the linear relationship between the two variables.
In statistics, simple linear regression is a linear regression model with explanatory variables. That is, it contains two sample points with one independent and one dependent variable (usually x and y coordinates in the Cartesian coordinate system) and shows the line as the function (a non-continuous line) that is the true value of the dependent variable. the variable is approximately a function of the independent variable. The adjective simply refers to the fact that different outcomes are associated with a different predictor.

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Answer: 34,29

Step-by-step explanation: subtracting 5 every time

The dimensions of the box that minimize the surface area where x is the length of each side of the base and y is the height of the box are 8 cm x 8 cm x 2 cm.

To design a rectangular box with a square base and an open top, we need to determine the dimensions of the box that will minimize the surface area.

Let x be the length of each side of the base and y be the height of the box. The volume of the box must be 128 cm, so we can write the equation as x^2y=128.

Using the volume equation, we can solve for y in terms of x: y=128/x^2. Substituting this into the surface area equation, we get:

A=2x^2+4x(128/x^2)=2x^2+512/x.

We can find the critical points by taking the derivative and setting it to zero: A'(x)=4x-512/x^2=0.

Solving for x, we get x=8 cm. Substituting this into the volume equation, we get y=2 cm.

Therefore, the dimensions of the box that minimize the surface area are 8 cm x 8 cm x 2 cm.

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Our total profit would be the difference between the amount we received in USD ($867,000) and the amount we borrowed ($850,000), plus the interest we earned ($20,000), which equals $37,000 USD.

To determine the total profit of a money market hedge, we need to know the details of the transaction, including the amount of currency involved and the interest rates in both countries.

Assuming we have all the necessary information, a money market hedge involves borrowing the foreign currency, converting it to the domestic currency, and investing the proceeds in a domestic money market instrument.

In this case, if the spot rate is 0.85$/c$, it means that 1 Canadian dollar is worth 0.85 US dollars. So, if we borrow 1 million Canadian dollars, we would receive $850,000 USD (1,000,000 CAD x 0.85 USD/CAD).

Next, we would convert the 850,000 USD to Canadian dollars at the current spot rate of 0.85, giving us 1,000,000 CAD. We would then invest the 1,000,000 CAD in a Canadian money market instrument, earning interest on our investment.

Assuming the interest rate in Canada is 2%, we would earn $20,000 CAD in interest over the year.

When the investment matures in one year, we would convert the 1,020,000 CAD back to USD at the prevailing spot rate. If the spot rate at that time is still 0.85, we would receive $867,000 USD (1,020,000 CAD x 0.85 USD/CAD).

Our total profit would be the difference between the amount we received in USD ($867,000) and the amount we borrowed ($850,000), plus the interest we earned ($20,000), which equals $37,000 USD.

To calculate the total profit of a money market hedge, we would need additional information such as the initial investment amount, interest rates in both countries, and the length of the investment. However, I can provide you with a general explanation of a money market hedge:

A money market hedge is a financial strategy used to manage currency risk by investing in short-term, interest-bearing instruments in two different currencies. In this case, you have a spot rate of 0.85 USD/CAD. To determine the total profit, you would need to consider the interest rate differential between the two currencies and the investment period.

Once you have all the required information, you can calculate the profit by comparing the returns from the investments in both currencies, considering the spot rate and interest rates. Remember that the effectiveness of a money market hedge depends on the accuracy of interest rate predictions and market movements.

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The correct option is C, It will reduce the margin of error by one-half. This is because the margin of error is inversely proportional to the square root of the sample size.

if Malia quadruples her sample size from 100 to 400, the square root of the sample size increases by a factor of 2, and the margin of error is reduced by a factor of 2.

The square root of a number is a value that, when multiplied by itself, gives the original number. It is denoted by the symbol "√", which is called the radical sign. For example, the square root of 9 is 3 because 3 multiplied by 3 equals 9.

The square root is an important concept in mathematics and has many applications in various fields. It is used in geometry to find the length of the sides of a right triangle, and in physics to calculate the magnitude of a vector. Square roots can be either positive or negative, although when we write √x, we usually mean the positive square root. There are also imaginary square roots, which involve the imaginary unit "i," and are used in complex analysis.

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a) The proportion of odd numbers in the population is 2/3, or 0.667.

b) The probability distribution table is as follows:

Proportion of odd numbers Probability

0 1/9

0.5 4/9

1 4/9

c) The mean of the sampling distribution of the sample proportion of odd numbers is 0.833.

d) Based on the results, the sample proportion is an unbiased estimator of the population proportion.

a) The population consists of three numbers: 3, 4, and 11. The proportion of odd numbers in the population is 2/3, or 0.667.

b) To construct a probability distribution table for the sampling distribution of the proportion of odd numbers, we need to consider all possible samples of size 2 that can be taken with replacement from the population. There are 9 different samples, as listed in the problem statement. For each sample, we compute the proportion of odd numbers.

The probability distribution table is as follows:

Proportion of odd numbers Probability

0 1/9

0.5 4/9

1 4/9

c) To find the mean of the sampling distribution, we weight each possible proportion of odd numbers by its probability, and sum the results:

Mean = (0)(1/9) + (0.5)(4/9) + (1)(4/9) = 0.833

d) The sample proportion of odd numbers is an unbiased estimator of the population proportion if its expected value is equal to the population proportion. In this case, we have:

E(p) = 0(1/9) + 0.5(4/9) + 1(4/9) = 0.833

Since the expected value of the sample proportion is equal to the population proportion, we can conclude that the sample proportion is an unbiased estimator of the population proportion.

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The geometric distribution models the number of trials needed until the first success, where each trial has a fixed probability of success.

Model each game as a trial, and the probability of Peter winning each game as the probability of success.

We want to find the probability that Peter goes broke, which means he loses all his money before Paul does.

So, we need to find the probability that Peter loses a certain number of games before he wins enough games to reach Paul's current amount.

p = 2/3

The probability of Paul winning as q = 1/3.

We want to find the probability that Peter loses all his money, which means he loses 2 games for every game he wins on average.

The probability of this happening on any given sequence of games is:

P(loss) = (1/3) * (2/3)2 = 4/27

This means that Peter loses 2 games for every 3 games played, on average.

Now, we can model the number of games played until Peter goes broke as a geometric distribution with p = 4/27.

Let X be the number of games played until Peter goes broke. Then:

P(X = k) = (1 - p)(k-1) x p

where k is the number of games played until Peter goes broke.

We want to find the probability that Peter goes broke before Paul does, which means he loses all his money before Paul does.

This is the same as the probability that Peter goes broke in the first X games played since if he doesn't go broke in the first X games, then Paul must have gone broke first.

So, we want to find P(Peter goes broke before Paul) = P(X < Y) where Y is the number of games played until Paul goes broke.

Since X and Y are independent geometric distributions with the same probability of success p.

We can use the formula for the probability of the first success in two independent geometric distributions:

P(X < Y) = p/(1 - (1-p)2) = 4/7

Therefore,

The probability that Peter goes broke before Paul is 4/7.

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To investigate the relationship between the grades students obtain in their midterm exam and the grades they obtain in the final exam, the professor could conduct a correlation analysis.

This analysis would involve calculating the correlation coefficient between the two sets of grades, which would indicate the strength and direction of the relationship between them. Additionally, the professor could use regression analysis to develop a model that predicts final exam grades based on midterm exam grades. This model could be used to identify students who may be at risk of performing poorly in the final exam and provide targeted support to improve their performance.

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The Titans' net gain for the three plays was 2 + x yards, we got by solving the equations.

On the first play, the Titans gained 2 yards.

Let's assume that on the next two plays, they gained x and y yards, respectively.

Then, their net gain for the three plays would be:

Net gain = 2 + x + y

On the second play, they gained some number of yards, which means they ended up at the 30-yard line plus that number of yards.

30 + x = their new position

Similarly, on the third play, they gained some number of yards and ended up at:

30 + x + y = their new position

Since they started and ended at the same position, we can set these two equations equal to each other:

30 + x = 30 + x + y

Simplifying this equation, we get:

y = 0

This means that on the third play, they gained 0 yards.

Now we can substitute this value for y into the equation for the net gain:

Net gain = 2 + x + 0

Net gain = 2 + x

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Secondary data are a fast way to get information. Secondary data are always updated and current.

The advantage of secondary data is that it often fits the research problem exactly and can be a fast way to get information. However, it is important to consider the methodology used in collecting the secondary data as it can affect the validity of the information. Additionally, secondary data may not always be updated and current, so it is important to verify the information before using it in research. Therefore, the correct answer to the multiple-choice question is: secondary data often fits the research problem exactly and secondary data are a fast way to get information.

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1. 456,976 different passwords are possible. 2. 52,428 different passwords end in 1. 3. 17,576 passwords do not start with z. 4. 175,760 passwords have no z's in them.


Assuming that the computer password consists of four letters followed by a single digit and is not case sensitive, we can calculate the number of possible passwords.

There are 26 letters in the alphabet and 10 digits, so there are 36 possible characters for each position. Therefore, there are [tex]36^5[/tex] possible passwords, which is equal to 456,976.

To find the number of passwords that end in 1, we fix the last position as 1, which leaves us with four remaining positions that can be filled with 36 choices each.

Hence, the number of passwords ending in 1 is [tex]36^4[/tex], which is equal to 52,428. The number of passwords that do not start with z is 35 (letters a-y) times [tex]36^3[/tex], which is equal to 17,576.

Finally, to find the number of passwords with no z's in them, we have 35 choices for each of the four letter positions and 10 choices for the digit position, resulting in [tex]35^4[/tex] x 10, which is equal to 175,760.

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The 95% confidence interval estimate for the percentage of all adults who want to lose weight is between 48% and 54%

The given information states that a Gallup Poll found 51% of the sample participants responded "yes" when asked if they would like to lose weight. The margin of sampling error is ±3% at a 95% confidence level.

To calculate the 95% confidence interval estimate for the percentage of all adults who want to lose weight, you simply add and subtract the margin of error from the sample percentage.

Lower limit: 51% - 3% = 48%
Upper limit: 51% + 3% = 54%

Therefore, the 95% confidence interval estimate for the percentage of all adults who want to lose weight is between 48% and 54%. This means that if this poll were repeated multiple times under the same conditions, in 95 out of 100 instances, the true percentage of all adults who want to lose weight would fall within this range.

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Answer:

15

Step-by-step explanation:

The LCD for 1/5 and 1/3 is 15 due to 5, 10, 15

3, 6, 9, 12, 15

15 is the first number that they have in common, when using their denominators, maybe next time with this explanation you won't need help here.

If it was 1/3 and 1/6, you would go 3, 6 and then 6 (though teachers want you to put more to show you understand then put ... at the end since its infinite) So hopefully that clears it up for you.

Diagrams that can convey both data and concepts or ideas are known as infographics.

Diagrams that can convey both data and concepts or ideas are known as "informational graphics" or "infographics". These graphics use visual elements such as charts, graphs, illustrations, maps, and diagrams to convey complex information and ideas in a concise and easy-to-understand way.

Infographics can be used in various fields, including business, education, journalism, and marketing, to present information in a visually appealing and engaging manner.

They are particularly useful when presenting large amounts of data or complex processes and can be designed to cater to different audiences, such as professionals or the general public. Overall, infographics are a powerful tool for communicating information and ideas effectively and efficiently.

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The possible values of a for which x^2+ax+25 is the square of a binomial are +10 and -10

If x^2+ax+25 is the square of a binomial, then it can be expressed in the form (x+b)^2 = x^2+2bx+b^2. Comparing the two expressions, we get:

a = 2b

25 = b^2

Solving for b in the second equation, we get:

b = ±5

Substituting this into the first equation, we get:

a = ±10

Therefore, the possible values of a for which x^2+ax+25 is the square of a binomial are +10 and -10, and these values will make b equal to +5 or -5, respectively.

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Answer:

Range is defined as the difference between the highest and the lowest value(s).

For the set of the given data, the answer is:

3 - 1 = 2

The answer is actually two as there are more than one that fit as the lowest number of the data set, but then including all of them would give negative numbers.

The maximum of the i.i.d. uniform(0,1) random variables x1, ..., xn is a random variable that represents the highest value among the n samples taken from the uniform distribution.

To find the density function of the maximum, we need to first find the cumulative distribution function (CDF). The probability that the maximum is less than or equal to some value t can be expressed as the product of the probabilities that each of the n samples is less than or equal to t, which is (t)^n. The CDF is then given by the integral of this product from 0 to t, which is t^n. The density function is the derivative of the CDF, which is n*t^(n-1).

In other words, the density function of the maximum of i.i.d. uniform(0,1) random variables x1, ..., xn is the probability density function of the (n-1)th order statistic of the uniform distribution on [0,1]. This means that the density function is a monotonically decreasing function that starts at 1 when t=0 and approaches 0 as t approaches 1.

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A rectangle that is not a square has two pairs of sides of different lengths.

When it is rotated counterclockwise about its center, the longer sides will eventually become the shorter sides, and vice versa.

The minimum positive number of degrees it must be rotated until it coincides with its original figure is 180 degrees.

This is because after a rotation of 180 degrees, the longer sides will become the shorter sides and vice versa, and the rectangle will be in the exact same position and orientation as it was originally.

Any rotation less than 180 degrees will result in a mirror image of the original rectangle.

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A) 95% confidence interval for the population mean is (85.37, 94.63). B) the 95% confidence interval for the population mean is (87.53, 92.47).

A) Using the given information, we can use a t-distribution to compute the 95% confidence interval for the population mean:

t(0.025, 69) = 1.994, where 0.025 is the level of significance for a two-tailed test and 69 degrees of freedom (n-1).

The margin of error is given by:

ME = t(0.025, 69) * σ/√n = 1.994 * 15/√70 ≈ 4.63

Thus, the 95% confidence interval for the population mean is:

90 ± 4.63, or (85.37, 94.63).

B) Assuming the same sample mean was obtained from a sample of 140 items, we can again use a t-distribution to compute the 95% confidence interval for the population mean:

t(0.025, 139) = 1.976, where 0.025 is the level of significance for a two-tailed test and 139 degrees of freedom (n-1).

The margin of error is given by:

ME = t(0.025, 139) * σ/√n = 1.976 * 15/√140 ≈ 2.47

Thus, the 95% confidence interval for the population mean is:

90 ± 2.47, or (87.53, 92.47).

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This situation does not contradict Rolle's Theorem because Rolle's Theorem requires the function to be continuous on a closed interval and differentiable on an open interval, which is not satisfied by f(x) = tan x in the interval (0, π).

To show that f(0) = f(π), we evaluate the tangent function at these points. At x = 0, tan(0) = 0, and at x = π, tan(π) = 0. Therefore, f(0) = f(π).

To investigate whether there exists a number c in the interval (0, π) such that f'(c) = 0, we need to find the derivative of f(x). The derivative of tan x is given by f'(x) = sec² x. However, the secant squared function is never equal to zero. Therefore, there is no c in the interval (0, π) where f'(c) = 0.

This situation does not contradict Rolle's Theorem because Rolle's Theorem requires certain conditions to be met. First, the function must be continuous on the closed interval [a, b], which is not satisfied by f(x) = tan x since it is not defined at x = π/2. Second, the function must be differentiable on the open interval (a, b), but f'(x) = sec^2 x is not defined at x = π/2. Thus, the requirements of Rolle's Theorem are not fulfilled, and its conclusion does not apply to f(x) = tan x in the interval (0, π).

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The performance of the portfolios from best to worst, based on their weighted mean RORs, is Portfolio 2, Portfolio 3, and Portfolio 1.

To calculate the weighted mean of RORs for each portfolio, we need to multiply each rate of return by its corresponding portfolio value, sum these products, and divide by the total portfolio value.

For Portfolio 1: (7.3% x $1,150) + (1.8% x $1,825) + (-6.7% x $1,405) + (10.4% x $1,045) + (2.7% x $1,450) = $73.79

Weighted mean ROR for Portfolio 1 = $73.79 / ($1,150 + $1,825 + $1,405 + $1,045 + $1,450) = 2.69%

For Portfolio 2: (7.3% x $800) + (1.8% x $2,500) + (-6.7% x $250) + (10.4% x $1,200) + (2.7% x $1,880) = $99.28

Weighted mean ROR for Portfolio 2 = $99.28 / ($800 + $2,500 + $250 + $1,200 + $1,880) = 3.23%

For Portfolio 3: (7.3% x $1,100) + (1.8% x $525) + (-6.7% x $825) + (10.4% x $400) + (2.7% x $2,225) = $128.09

Weighted mean ROR for Portfolio 3 = $128.09 / ($1,100 + $525 + $825 + $400 + $2,225) = 3.02%

Therefore, the performance of the portfolios from best to worst, based on their weighted mean RORs, is Portfolio 2, Portfolio 3, and Portfolio 1.

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Answer: 08

Step-by-step explanation:

2.8 x 82.6 / 27.8 13.9

≈ 3 x 80 / 30 10

= 0.8

Proposition 9.18 states that the function e preserves multiplication, meaning e(mk) = e(m) * e(k), where the left-hand side refers to multiplication in Z (integers), and the right-hand side refers to multiplication in R (real numbers).

Proposition 9.18 states that the function e preserves multiplication e(mk) = e(m) * e(k), where the left-hand side refers to multiplication in the ring of integers Z, and the right-hand side refers to multiplication in the field of real numbers R. In other words, when we multiply two integers m and k in Z and then apply the exponential function e, we get the same result as when we apply the exponential function to each integer separately and then multiply the resulting real numbers in R. This is an important property of the exponential function, which makes it a useful tool in many areas of mathematics and science.

Proposition 9.18 states that the function e preserves multiplication, meaning e(mk) = e(m) * e(k), where the left-hand side refers to multiplication in Z (integers), and the right-hand side refers to multiplication in R (real numbers). To prove this proposition, we can follow these steps:

1. Define the function e: e is a function that maps integers (Z) to real numbers (R), i.e., e: Z → R.
2. State the proposition: e preserves multiplication, i.e., e(mk) = e(m) * e(k) for all integers m and k.
3. Prove the proposition:

a. Choose arbitrary integers m and k.
b. Calculate e(mk), where mk is the product of m and k in the set of integers Z.
c. Calculate e(m) and e(k) separately, where e(m) and e(k) are the mapped values of m and k in the set of real numbers R.
d. Multiply e(m) and e(k) to obtain the product in the set of real numbers R.
e. Show that e(mk) = e(m) * e(k), which proves that the function e preserves multiplication.

By following these steps, we can demonstrate that the function e indeed preserves multiplication as stated in Proposition 9.18.

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In hypothesis testing, the null hypothesis and alternative hypothesis can be both false statements. This statement is False.

The alternative hypothesis and the null hypothesis both are mutually exclusive possible outcomes that cover all the possible outcomes of an event. One test may be true and the other may be false. The null hypothesis is the default outcome and the alternative hypothesis is the experimental solution.

The main aim of testing the hypothesis is to test the results of research that applies to the size of the population.  It supports the rejection of the null hypothesis in the favour of alternative hypothesis. If both hypothesis cases are failed, the test is invalid.

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The absolute minimum and maximum values of the function f(x,y) = 1+xy – x – y on the region D, bounded by the parabola y = x^2 and the line y = 4, we can follow these steps:

Find the critical points of f(x,y) by setting the partial derivatives of f equal to zero:

fx = y - 1 = 0

fy = x - 1 = 0

Solving these equations simultaneously gives the critical point (1,1).

Check the boundary of region D, which is composed of two curves: y = x^2 and y = 4.

2.1. Along the curve y = x^2:

Substituting y = x^2 into f(x,y), we obtain a function of one variable:

g(x) = f(x, x^2) = 1 + x^3 - 2x^2

Taking the derivative of g(x) and setting it equal to zero to find its critical points:

g'(x) = 3x^2 - 4x = 0

x(3x - 4) = 0

Solving for x, we get x = 0 and x = 4/3. Plugging these values into g(x), we find that g(0) = 1 and g(4/3) = -1/27.

Therefore, the minimum value of f(x,y) along the curve y = x^2 is g(4/3) = -1/27, and the maximum value is g(0) = 1.

2.2. Along the line y = 4:

Substituting y = 4 into f(x,y), we obtain a function of one variable:

h(x) = f(x, 4) = 1 + 4x - x - 4

Simplifying, we get h(x) = 3x - 3.

Taking the derivative of h(x) and setting it equal to zero to find its critical point:

h'(x) = 3 = 0

Since h'(x) is never zero, there are no critical points along the line y = 4. We only need to check the endpoints of the line segment that lies within D.

At the endpoint (4/2, 4), we have f(2, 4) = -2, and at the endpoint (-2, 4), we have f(-2, 4) = 9.

Therefore, the minimum value of f(x,y) along the line y = 4 is f(2,4) = -2, and the maximum value is f(-2,4) = 9.

Compare the values obtained in steps 1 and 2 to find the absolute minimum and maximum values of f(x,y) on D.

The values of f at the critical point (1,1), along the curve y = x^2, and along the line y = 4 are:

f(1,1) = -1

g(4/3) = -1/27

g(0) = 1

f(2,4) = -2

f(-2,4) = 9

Therefore, the absolute minimum value of f(x,y) on D is f(-2,4) = 9, and the absolute maximum value is f(0) = 1.

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In order to determine whether or not the method of undetermined coefficients can be applied to find a particular solution of the given equation, we must first check if the right-hand side of the equation is in the correct form.

That is, it must be a linear combination of exponential and/or trigonometric functions, or a product of these functions with polynomials. In this case, the right-hand side is +(-1)e(t), which is a linear combination of an exponential function and a constant. Therefore, the method of undetermined coefficients can be applied to find a particular solution to the given equation.

In order to determine whether the method of undetermined coefficients can be applied to find a particular solution for the given equation y'' + 2y' - y = (-1)e^(t), we need to analyze the form of the non-homogeneous term, which is (-1)e^(t). The method of undetermined coefficients can be applied when the non-homogeneous term is a polynomial, an exponential, a sine or cosine function, or a combination of these types.

In this case, the non-homogeneous term is an exponential function (-1)e^(t). Therefore, the method of undetermined coefficients can be applied to find a particular solution for the given equation.

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The limit of the given function as x approaches 4 is 1/4. To evaluate the limit lim(√x - 2)/(x-4) as x approaches 4 using L'Hôpital's Rule.

First we need to check if the limit has the indeterminate form of 0/0 or ∞/∞.

As x approaches 4:
Numerator: √x - 2 → √4 - 2 = 0
Denominator: x - 4 → 4 - 4 = 0

Since the limit has the indeterminate form 0/0, we can apply L'Hôpital's Rule. This rule states that if the limit of the ratio of the derivatives exists, then the limit of the original function exists and is equal to that value.

Now, differentiate both the numerator and the denominator with respect to x:

Numerator: d(√x - 2)/dx = 1/(2√x)
Denominator: d(x - 4)/dx = 1

Now, compute the limit of the ratio of the derivatives as x approaches 4:

lim (1/(2√x))/(1) as x → 4 = lim (1/(2√x)) as x → 4 = 1/(2√4) = 1/4

So, the limit of the given function as x approaches 4 is 1/4.

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