pls hlp thx your the best

There are 12 possible ways Barney can wear his shorts and shirts.

Now, We can draw a tree diagram as;

Shorts

  /      |       \

Pair1 Pair2 Pair3

 / \   / \   / \ / \

S1 S2 S1 S2 S1 S2

 Shirts

 /   |    |   \

S1 S2 S3 S4

So, Barney can choose from 3 different pairs of shorts and 4 different shirts.

Hence,  To find the total number of possible combinations, we just need to multiply the number of options for each category together.

Now, In this case, Barney has 3 options for shorts and 4 options for shirts,

Hence, the total number of possible ways he can wear his outfit is;

3 x 4 = 12

Thus, There are 12 possible ways Barney can wear his shorts and shirts.

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The kangaroo maximum height is 8.5 feet

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

Initial height = 4 ft

Initia; velocity = 24 ft/s

We start by writing the height function as

h(t) = -32t^2 + 24t + 4

Where

32 = acceleration of gravity

So, we differentiate and set to 0

-64t + 24 = 0

Solve for t

t = 24/64

So, we have

Max height = -32(24/64)^2 + 24(24/64) + 4

Evaluate

Max height = 8.5

Hence, the max height = 8.5

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False.

If A is a 5×4 matrix and B is a 4×3 matrix, then the entry of AB in the 3rd row / 2nd column is obtained by multiplying the 3rd row of A by the 2nd column of B, not the 3rd column of A by the 2nd row of B.

If A is a 5×4 matrix and B is a 4×3 matrix, then the entry of AB in the 3rd row / 2nd column is obtained by multiplying the 3rd row of A by the 2nd column of B, not the 3rd column of A by the 2nd row of B.

To see why, let C = AB be the product of A and B. Then, by definition, the entry in the i-th row and j-th column of C is given by the dot product of the i-th row of A and the j-th column of B. That is, Cij = Ai1B1j + Ai2B2j + ... + Ai4B4j, where Ai1, Ai2, ..., Ai4 are the entries in the i-th row of A and B1j, B2j, ..., B4j are the entries in the j-th column of B.

So, in this case, the entry in the 3rd row / 2nd column of C is given by C32 = A31B12 + A32B22 + A33B32 + A34B42. This involves multiplying the 3rd row of A by the 2nd column of B, not the 3rd column of A by the 2nd row of B.

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The quadratic equation y = ax^2 + bx + c is a suitable example that reveals the minimum or maximum value without altering the equation's form. By finding the vertex of the parabola using the formula x = -b/(2a), you can determine the minimum or maximum value of the function.

The equation that reveals the minimum or maximum value of a function without changing the form of the equation is the derivative of the function. The derivative gives the slope of the function at any given point, which can help us identify the location of the maximum or minimum point.

To find the maximum or minimum point of a function, we first take the derivative of the function and set it equal to zero. Solving for the variable will give us the x-coordinate of the maximum or minimum point. To determine whether it is a maximum or minimum, we can use the second derivative test.

For example, let's consider the function f(x) = x^2 - 6x + 8. Taking the derivative, we get f'(x) = 2x - 6. Setting this equal to zero and solving for x, we get x = 3. This means that the maximum or minimum point of the function occurs at x = 3. To determine whether it is a maximum or minimum, we take the second derivative: f''(x) = 2. Since the second derivative is positive, we know that the function has a minimum at x = 3.

In summary, the derivative of a function reveals the minimum or maximum value of the function without changing the form of the equation. By finding the zeros of the derivative and using the second derivative test, we can identify the location and type of the maximum or minimum point, equation that reveals the minimum or maximum value without changing its form. The quadratic equation, given by the general form y = ax^2 + bx + c, is an ideal example to consider.

A quadratic equation represents a parabola, which has either a minimum or maximum value depending on the coefficient "a". If "a" is positive, the parabola opens upwards and has a minimum value, and if "a" is negative, the parabola opens downwards and has a maximum value. The minimum or maximum value is located at the vertex of the parabola.

To find the x-coordinate of the vertex, you can use the formula x = -b/(2a). By plugging the values of "a" and "b" from the quadratic equation, you can determine the x-coordinate of the vertex. Then, you can substitute this x-coordinate back into the original equation to find the corresponding y-coordinate, revealing the minimum or maximum value of the function without changing its form.

To summarize, the quadratic equation y = ax^2 + bx + c is a suitable example that reveals the minimum or maximum value without altering the equation's form. By finding the vertex of the parabola using the formula x = -b/(2a), you can determine the minimum or maximum value of the function.

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To write (10^2)^-3 as a power of 10 with a single exponent, we can use the property of exponents that states that when we raise a power to another power, we multiply the exponents. So:

(10^2)^-3 = 10^(2*-3) = 10^(-6)

Therefore, (10^2)^-3 can be written as 10^-6 with a single exponent of -6.

Answer:

10^-6 as a power of 10 with a single exponent.

Step-by-step explanation:

To write (10^2)^-3 as a power of 10 with a single exponent, we can simplify the expression by using the rule that states that when we raise a power to another power, we multiply the exponents.

Therefore:

(10^2)^-3 = 10^(2*-3) = 10^(-6)

Therefore, (10^2)^-3 is equivalent to 10^-6 as a power of 10 with a single exponent.

Answer:

A) reflect triangle A over the x-axis Triangle A: (4,-2) (4,-4) (1,-4)

B) Reflect Triangle A over the line y= -x Triangle A: (-2,4) (-4,-4) (-4,-1)

C) Rotate Triangle A 90 degrees counterclockwise Triangle A: (2,-4) (4,-4) (4,-1)

Step-by-step explanation:

A) When reflecting points over the x axis, the points change from

(x,y) to (x,-y)

B) When reflecting points over the line y=-x, the points change from

(x,y) to (-y,-x)

C) When rotating points 90 degrees counterclockwise around the origin, the points change from (x,y) to (y,-x)

The distance between (-5, 3) and (2, -2) on the coordinate plane is approximately 8.6 units.

The formula to find the distance between the two points is usually given by

d=√{(x₂-x₁)² + (y₂-y₁)²}

Here:

x₂ = 2, x₁ = -5, y₂ = -2, and y₁ = 3.

Substitute the provided values,

d = √((2 - (-5))²  + (-2 - 3)²)

= √(7²  + (-5)²)

= √(49 + 25)

= √(74)

Rounding to the nearest tenth, we get:

d ≈ 8.6

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Hey ⊂hcpsibekweou⊃

Answer:

(4 , -6 )

Step-by-step explanation:

Based on the image we can see that M' is in quadrant 2.

Coordinate plane:

As you may know reflection is known as a flip.

For example: (-5, 4) in quadrant 1  reflects to ( -5, -4 ) quadrant 3.

From the given we can see that M' is (-4, 6 ),    Therefore the reflection of             ( -4, 6) is (4, -6).

xcookiex12

4/19/2023

Answer: (-4, -6)

Step-by-step explanation:

      To reflect a point over the x-axis, we can keep the x-value the same and multiply the y-value by -1 (change the sign).

      We are given the coordinate point (-4, 6) so a reflection over the x-axis gives us the point of M' at (-4, -6).

The 95% confidence interval suggests if the nicotine patch is used for 2 months, there is a high likelihood that the proportion of individuals who will report no smoking incidents.

In the following year will fall between 17.4% and 24.8%. This means that the study results are statistically significant and reliable within this range, and it is likely that the nicotine patch can be effective in reducing smoking incidents for a significant proportion of users.
In the study of the nicotine patch, the appropriate interpretation of the 95% confidence interval (17.4%, 24.8%) is that we can be 95% confident that the true proportion of people who reported no smoking incidents in the following year after using the patch for 2 months lies between 17.4% and 24.8%.

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If the stock sells for $58 a share the Dragon company's cost of equity will be 8.97%.

The cost of equity is the return that investors require from the stock of the company. We have to use the DDM (Dividend discount model) here,

The formula for the DDM is,

P₀ = D₁/(ke - g), current stock price is P₀, the expected dividend per share in the next period is D₁, required rate of return (cost of equity) is ke, and expected growth rate of dividends  g.

In this case, we have,

D₁ = D₀ x (1 + g)

= $2.85 x (1 + 0.036)

= $2.95 (expected dividend per share in the next period)

P₀ = $58 (current stock price)

g = 0.036 (expected growth rate of dividends)

Substituting these values into the DDM formula, we get,

$58 = $2.95 / (ke - 0.036)

Solving for ke, we get,

ke = ($2.95 / $58) + 0.036

= 0.0897 or 8.97%

Therefore, Dragon Company's cost of equity is 8.97%.

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We need to use a different test, such as the ratio test or the root test, to make a conclusion.

For the first series, we have:

∑[infinity]k=1 (2+k)/(3-k²)

Using the divergence test, we consider the limit of the general term as k approaches infinity:

lim (k→∞) (2+k)/(3-k²)

We can see that the denominator, k², grows much faster than the numerator, k. Therefore, as k approaches infinity, the term approaches zero. However, the denominator approaches infinity, meaning that the terms do not go to zero fast enough for the series to converge. Therefore, we can conclude that the series diverges.

For the second series, we have:

∑[infinity]k=1 (2e^k)/(3+k)

Using the divergence test, we consider the limit of the general term as k approaches infinity:

lim (k→∞) (2e^k)/(3+k)

We can see that the denominator, 3+k, grows much faster than the numerator, e^k. Therefore, as k approaches infinity, the term approaches zero. However, the denominator approaches infinity, meaning that the terms do go to zero fast enough for the series to converge. Therefore, we cannot conclude anything about the convergence or divergence of the series using only the divergence test. We need to use a different test, such as the ratio test or the root test, to make a conclusion.

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The histogram will show that the mean time is greater than the median time of 7.4 minutes and the histogram will show that most of the data is centered between 6 minutes and 9 minutes are true.

After rounding the data is 6, 6, 7, 10, 8, 8, 10, 9, 8, 8, 7, 8, 6, 7, 6

The histogram will have bars for each minute from 6 to 10, inclusive.

The frequency of each bar will be the number of times a rounded time falls within that minute range.

A histogram will show that the mean time is approximately equal to the median time of 7.5 minutes is not true because mean is not equal to median

The histogram will show that the mean time is greater than the median time of 7.4 minutes.

The mean time is actually 7.47, which is greater than the median time of 7. This statement is true.

The histogram will show that most of the data is centered between 6 minutes and 9 minutes.

Looking at the rounded times, we see that 11 out of 15 fall within the range of 6 to 9 minutes, so this statement is true.

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Mr. Billings needs to reduce his water usage to 2.7 HCF in order to have a water bill of less than $200.

We have,

To calculate Mr. Billings' water bill, we need to know how much water he used during the month of August.

Let's assume that he used x HCF of water.

We can then use the tiered billing rates to calculate his total water bill.

For the first 8 HCF, the billing rate is $3.64 per HCF,

so the cost for this tier is 3.64x.

For usage between 8 and 24 HCF, the billing rate is $4.08 per HCF,

so the cost for this tier is (24-8) x $4.08 = 61.44.

For usage between 24 and 36 HCF, the billing rate is $5.82 per HCF,

so the cost for this tier is (36-24) x $5.82 = 69.84.

For usage over 36 HCF, the billing rate is $8.19 per HCF,

so the cost for this tier is (x-36) x $8.19.

Now,

Total water bill

= $37.78 + 3.64x + 61.44 + 69.84 + (x-36) x $8.19

= $168.86 + 11.55x

To find the amount of water usage that Mr. Billings needs to reduce in order to have a water bill of less than $200, we can set the total water bill to $200 and solve for x:

$200 = $168.86 + 11.55x

$31.14 = 11.55x

x = 2.7 HCF

So,

Mr. Billings needs to reduce his water usage to 2.7 HCF in order to have a water bill of less than $200.

Similarly,

To find the amount of water usage that Mr. Billings needs to reduce in order to have a water bill of less than $150, we can set the total water bill to $150 and solve for x:

$150 = $168.86 + 11.55x

-$18.86 = 11.55x

x = -1.63 HCF

Since water usage cannot be negative, there is no solution to this problem. Therefore, it is not possible for Mr. Billings to have a water bill of less than $150, given his current water usage and the tiered billing rates.

Thus,

Mr. Billings needs to reduce his water usage to 2.7 HCF in order to have a water bill of less than $200.

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Answer:

mean is the answer

Step-by-step explanation:

because mean or average is when the numbers of different value is added over the number you added

for example

the average of 5+4+5+6+4 is

5+4+5+6+4/5

24/5=4.8

THANK YOU

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The expected number of patients experiencing flulike symptoms is 17.33.

Based on the information given, researchers selected 825 patients at random who take a certain widely-used prescription drug daily. In a clinical trial, 22 out of the 825 patients complained of flulike symptoms. The researchers' hypothesis is that more than 2.1% of this drug's users experience flulike symptoms as a side effect.

To test this hypothesis, we can use a one-tailed hypothesis test with a significance level of 0.01. The null hypothesis (H0) is that the proportion of patients experiencing flulike symptoms is equal to or less than 2.1%. The alternative hypothesis (Ha) is that the proportion of patients experiencing flulike symptoms is greater than 2.1%.

To calculate the test statistic, we first need to find the expected number of patients experiencing flulike symptoms under the null hypothesis. This is equal to the sample size (825) multiplied by the proportion of patients experiencing flulike symptoms under the null hypothesis (0.021). So, the expected number of patients experiencing flulike symptoms is 17.33.

Next, we can calculate the test statistic using the formula:

z = (x - μ) / σ

where x is the observed number of patients experiencing flulike symptoms (22), μ is the expected number of patients experiencing flulike symptoms under the null hypothesis (17.33), and σ is the standard deviation of the sampling distribution, which can be approximated by:

σ = sqrt[(p * (1 - p)) / n]

where p is the proportion of patients experiencing flulike symptoms under the null hypothesis (0.021) and n is the sample size (825).

Plugging in the values, we get:

z = (22 - 17.33) / sqrt[(0.021 * (1 - 0.021)) / 825] = 2.17

Looking up the critical value for a one-tailed test with a significance level of 0.01, we find that it is 2.33. Since our test statistic (2.17) is less than the critical value (2.33), we fail to reject the null hypothesis.

Therefore, we do not have sufficient evidence to conclude that more than 2.1% of this drug's users experience flulike symptoms as a side effect at the 0.01 level of significance.

In the given scenario, researchers selected 825 patients who take a certain prescription drug daily. Out of these, 22 patients experienced flulike symptoms. The hypothesis being tested is whether more than 2.1% of this drug's users experience flulike symptoms as a side effect at the α=0.01 level of significance. Since np₀(1-p₀) = 17.0 > 10, the sample size is less than 5% of the population size, and the patients were selected randomly, all requirements for testing the hypothesis are satisfied.

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The missing information for q2 is the mean squares for treatment, which can be calculated by dividing the sum of squares for treatment. The missing information for q3 is the sum of squares for error.The missing information for q4 is the mean squares for error, which can be calculated by dividing the sum of squares for error.To find the p-value for the above ANOVA table, we need to use the F-distribution with degrees of freedom for treatment  and degrees of freedom for error.

Using the given mean squares for treatment (25.25) and mean squares for error (2.95), we can calculate the F-statistic as follows:

F = mean squares for treatment / mean squares for error
F = 25.25 / 2.95
F = 8.5593

The p-value can then be calculated using a one-tailed F-test with alpha level of 0.05:

p-value = pf(F, degrees of freedom for treatment, degrees of freedom for error)
p-value = pf(8.5593, 3, 16)
p-value = 0.0006

Therefore, the answer is A.
Q2: Mean squares (treatment) = Sum of squares (treatment) / Degree of freedom (treatment)
Mean squares (treatment) = 75.75 / 3
Mean squares (treatment) = 25.25
So, the answer for q2 is: a. 25.25

Q3: Mean squares (error) = Sum of squares (error) / Degree of freedom (error)
Mean squares (error) = 47.2 / 16
Mean squares (error) = 2.95
So, the answer for q3 is: b. 2.95

Q4: F-value = Mean squares (treatment) / Mean squares (error)
F-value = 25.25 / 2.95
F-value ≈ 8.5593
So, the answer for q4 is: c. 8.5593

Q5:P-value = 1 - pf(F-value, Degree of freedom (treatment), Degree of freedom (error))
P-value = 1 - pf(8.5593, 3, 16)

So, the answer for question 5 is: c. 1- pf(8.5593, 3, 16)

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a) The equation y = 35(0.57)ˣ represents a decay.

b) The rate of decay is 43% per period.

c) The decay factor is 0.57 or 57% per period.

d) The initial amount is $35.

e) The equation is an exponential decay function.

f) If x = 2, y will be $11.37.

An exponential decay function or equation can be represented by y = 35(0.57)^x  or 35(1 - 0.43)^x showing that the initial amount of $35 reduces by a constant rate of 43% per period.

Exponential functions are known by the consistent percentage rate increasing (growth) or decreasing (decay) over a period.

y = 35(0.57)ˣ

x = 2

y = 35(0.57)^2

= $11.37

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The Zero Property of Multiplication states that the product of any number and zero is always zero. So, whenever you use this property and multiply any number by zero, the answer will always be zero.

One of the abecedarian data of  computation is the Zero Property of Multiplication. It claims that when any integer is multiplied by zero, the  outgrowth is always zero. This  specific is extremely handy for  diving   addition problems.   The Zero Property of Multiplication can be used to reduce  addition statements.

Assume you're given the  ensuing expression   3x( 2y- 5z)   You may extend this statement using the distributive property of  addition to get   6xy- 15xz  

Assume you wish to simplify this formula indeed further by removing a common element. You will see that the factor of x appears in both terms of the equation. So you can abate x to get   x( 6y- 15z)

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To calculate the weighted mean of student 40's exam scores with exam 1 weighted twice that of the other 3 exams, you will need to use the weights provided in the spreadsheet. First, locate student 40's scores for all four exams on the second sheet of the spreadsheet. Then, apply the weights provided to each exam score.

To weight exam 1 twice that of the other 3 exams, you will need to multiply the exam 1 score by 2 and leave the other three scores as they are. Once you have adjusted the weights accordingly, you can calculate the weighted mean using the formula:

weighted mean = (weight1 * score1 + weight2 * score2 + weight3 * score3 + weight4 * score4) / (weight1 + weight2 + weight3 + weight4)

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.

In the year 2003, which is one year after 2002, 500 hamburgers were consumed per person in Michigan.

y = ( 5,000 175,000 x)(1/2)   where y represents the average number of hamburgers consumed by people in Michigan and x is the number of times since 2002.   To find the time when 500 hamburgers were consumed per person, we need to  break for x in the equation  

500 = ( 5,000 175,000 x)(1/2)  

Squaring both sides of the equation,

we get   =  5,000 175,000 x  

Simplifying, we have   x =  245,000

 Dividing both sides by 175,000, we get   x = 1.4  

thus, 500 hamburgers were consumed per person in Michigan1.4 times after 2002. To find the time, we add1.4 to 2002  

20021.4 = 2003.4

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Step-by-step explanation:

answer is in the photo

..

.

I understand you're asking about the volume percentage removed from a solid box when a cube is removed from each corner. Let's consider the dimensions of the original box as L cm x W cm x H cm. When a cube of side length x cm is removed from each corner, there are a total of 8 corners (since a box has 8 corners).

The volume of each removed cube is x^3 cubic cm. Since there are 8 cubes removed, the total volume removed is 8 * x^3 cubic cm. The volume of the original box is L * W * H cubic cm.

Now, to calculate the percentage of the original volume removed, we use the formula:

[tex]Percentage removed = (Total volume removed / Original volume) * 100[/tex]

In this case, it would be:

Percentage removed = (8 * x^3) / (L * W * H) * 100

Keep in mind that the specific values of L, W, H, and x would be needed to calculate the exact percentage of the original volume removed. However, the general formula above can be used to determine the percentage removed for any solid box with given dimensions and removed cubes.

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The maximum total number of observations with a deviation of at least 5 is 1.

If the sum of deviations of 100 observations from 20 is 5, then the maximum total number of them, such that each of which is at least 5, can be found by considering the minimum deviation for the other observations.

Since we want the maximum total number of observations with a deviation of at least 5, let's assume all other observations have a deviation of 0 (meaning they are equal to 20). Let x be the number of observations with a deviation of at least 5. Then, the sum of deviations can be represented as:

5x + 0(100-x) = 5

Solving for x, we get:

5x = 5
x = 1

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To solve any amount of whole numbers or variables raised to a positive power, you need to apply the power to each individual term within the parentheses and simplify as needed.

To solve any amount of whole numbers or variables raised to a positive power, you simply need to apply the power to each term within the parentheses. For example, (2x) raised to the 4th power would be solved by taking 2 to the 4th power (which is 16) and x to the 4th power (which is [tex]x^4[/tex]), and then multiplying these terms together: [tex]16x^4[/tex].

Similarly, (4 times x raised to the 2nd power) raised to the 4th power would first require you to solve the term within the parentheses, which is x raised to the 2nd power (or [tex]x^2[/tex]), multiplied by 4 (to get 4x^2). Then, you raise this entire term to the 4th power, which means you multiply it by itself 4 times: [tex](4x^2)^4 = 4^4 * (x^2)^4 = 256x^8[/tex].

So, in summary, to solve any amount of whole numbers or variables raised to a positive power, you need to apply the power to each individual term within the parentheses and simplify as needed.

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To generate a data set of integer values ranging from 1 to 1000 (inclusive) using a seed and a desired size between 3 and 500, you can utilize a random number generator. First, set the seed to ensure the reproducibility of the random numbers. Then, use the generator to create a data set of the desired size, where each value represents the length.

To generate a data set of integer values ranging from 1 to 1000 (inclusive) with a desired size and a given seed for the random number generator, you can use the following steps:

1. Set the seed for the random number generator using the given seed value.
2. Generate the desired size of the data set, using the random number generator to generate a random integer value between 1 and 1000 (inclusive) for each value in the set. You can do this using a loop or a list comprehension, depending on your preference.
3. Each value in the data set represents the length, so you can use the generated integer value directly as the length for that value.

Here's some sample Python code that shows how to generate a data set of size 10 with a seed of 12345:

```
import random

seed_value = 12345
size = 10

random.seed(seed_value)
data_set = [random.randint(1, 1000) for i in range(size)]
```

This code sets the seed value to 12345, generates a data set of size 10, and stores the resulting list of integers in the `data_set` variable.

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We can say with 90% confidence that the true mean concentration of uric acid in the population lies between 4.32 and 6.24 mg/dl.

To find the 90% confidence interval for the population mean concentration of uric acid, we can use the formula:

CI = x' ± z*(σ/√n)

where:

x' = sample mean concentration = 5.28 mg/dl

z = z-score for 90% confidence level = 1.645 (from standard normal distribution table)

σ = population standard deviation = 1.77 mg/dl

n = sample size (number of tests taken) = 13

Substituting the given values into the formula, we get:

CI = 5.28 ± 1.645 x (1.77/√13)

CI = 5.28 ± 0.96

CI = (4.32, 6.24)

Therefore, we can say with 90% confidence that the true mean concentration of uric acid in the population lies between 4.32 and 6.24 mg/dl.

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