Your CD player is set for random play. There are 20 CDs in the player and
there are 10 songs on each CD. You have one favorite song on each of the
CDs. What is the probability that the next song played is one of them?

Answer:

53.125 or 53 dumplings.

Step-by-step explanation:

20 percent of 2.00 is 0.40 so 2.00 minus 0.40 is equal to 1.60. Since 85 dumpling were sold we divide 85 with 1.6 to get 53.125

A) The probability of a z-score greater than 1.6189 is 0.0523, P(X > 142.7) = 0.0523.

B)  The probability of a z-score greater than 2.2145 is 0.0135, P(M > 142.7) = 0.0135.

a) Using the z-score formula, we have:

Looking up the z-table, we find the probability of a z-score greater than 1.6189 is 0.0523.

Therefore, P(X > 142.7) = 0.0523.

b) The mean of the sample mean distribution is still μ = 138.1, but the standard deviation is now σ/√n = 30.7/√216 ≈ 2.0894.

Using the central limit theorem, we can approximate the sample mean distribution as a normal distribution.

Looking up the z-table, we find the probability of a z-score greater than 2.2145 is 0.0135.

Therefore, P(M > 142.7) = 0.0135.

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We need four D flip-flops to design a counter to count in the sequence 12, 20, 1, 0, and then repeat.

To count in the sequence 12, 20, 1, 0 and then repeat, we need a counter that has at least four states: 12, 20, 1, and 0. Each state corresponds to a unique output value, and the counter changes state after each clock pulse.

To implement the counter, we can use four D flip-flops, one for each state. The flip-flops will store the current state of the counter and change state on the rising edge of the clock signal. The outputs of the flip-flops will be combined to produce the counter's output.

Therefore, we need four D flip-flops to design a counter to count in the sequence 12, 20, 1, 0, and then repeat.

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We have shown that if b = 0(mod a) and c = 0(mod b), then c = 0(mod a).

The statement "If b = 0(mod a) and c = 0(mod b), then c = 0(mod a)" is true.

To prove this, we need to show that if b is a multiple of a and c is a multiple of b, then c is a multiple of a.

Suppose that b = ak and c = bk' for some integers k and k'. Then, we have:

c = bk' = (ak)k' = a(kk')

Since k and k' are both integers, their product kk' is also an integer. Therefore, we can write c = a(kk'), which shows that c is a multiple of a.

Hence, we have shown that if b = 0(mod a) and c = 0(mod b), then c = 0(mod a).

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a. The nth term of the sequence is  11 - 3n.

b. The nth term of the sequence is  14- 5n.

The sequence is an arithmetic progression. Therefore, the expression for the sequence can be represented as follows:

nth term = a + (n + 1)d

where

Therefore,

a.

a = 8

d = 11 - 8 = - 3

Therefore,

nth term = 8 + (n - 1)-3

nth term = 8  - 3n + 3

nth term = 11 - 3n

b.

a = 19

d = 14 - 19 = -5

nth term = 19 + (n - 1)-5

nth term = 19 - 5n - 5

nth term =  14 - 5n

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We can make 4 servings of chicken noodle soup using 20 oz of egg noodles.

To determine how many servings of chicken noodle soup can be made from 20 oz of egg noodles, we need to divide the total amount of noodles by the amount required for each serving.

Given that 5 oz of egg noodles are needed for one serving, we can divide 20 oz by 5 oz/serving to get the total number of servings.

20 oz ÷ 5 oz/serving = 4 servings

The serving size may vary depending on the recipe and the individual's appetite, so this calculation is an estimate. Other ingredients such as chicken, vegetables, and broth will also affect the overall serving size and number of servings.

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For the polygons in the attached figure,

a) Scale factor = 2.5

b) Scale factor = 2.5

c) Scale factor = 1.5

d) Scale factor = 2

We knoa that a scale factor is nothing but the ratio between the scale of a original object and a transformed object.

Here, the polygons are similar.

We know that the corresponding sides of similar figure are in proportion.

a) 10/6 = 2.5

15/6 = 2.5

18/7.2 = 2.5

So, the scale factor would be 2.5

b)

25/10 = 2.5

15/6 = 2.5

S0, the scale factor = 2.5

c)

12/8 = 1.5

6/4 = 1.5

9/6 = 1.5

So, the scale factor = 1.5

d)

12/6 = 2

16/8 = 2

20/10 = 2

so, the scale factor is 2

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The value of the variable x is 8

To determine the value, we have to take note that the sum of the angles in polygon is determined with the formula

(n -2 )180

Such that the variable, 'n' is the number of sides of the polygon

From the information given, we have that;

n = 4

Substitute the values

(4-2) 180 = 360

Now, equate the measures to the angle, we have;

9x + 5 + 14x + 3 + 15x -11 + 7x + 3 = 360

collect the like terms

9x + 14x + 15x + 7x = 360

Add the like terms

45x = 360

Make 'x' the subject of formula

x = 8

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a. the population standard deviation is not given, we cannot calculate the standard error of the mean.

b. b. The expected shape of the distribution would still be positively skewed, as the skewness of the population does not change with the sample size.

c. the probability of selecting a sample with a mean of at least $117,000 is 1 - 0.9772 = 0.0228, or about 2.28%.

d. the probability of selecting a sample with a mean of more than $107,000 is 1 - 0.0427 = 0.9573, or about 95.73%.

e. the probability of selecting a sample with a mean of more than $107,000 but less than $117,000 is the difference between these probabilities, which is 0.9772 - 0.0427 = 0.9345, or about 93.45%.

What is standard deviation?

Standard deviation is a measure of the amount of variation or dispersion in a set of data values. It shows how much the data deviates from the mean or average value.

a. The standard error of the mean is given by the formula:

SE = σ/√n

where σ is the population standard deviation, n is the sample size, and √n denotes the square root of n.

Since the population standard deviation is not given, we cannot calculate the standard error of the mean.

b. The expected shape of the distribution would still be positively skewed, as the skewness of the population does not change with the sample size.

c. To calculate the probability of selecting a sample with a mean of at least $117,000, we need to find the z-score corresponding to this sample mean:

z = (x - μ) / (σ / √n)

z = (117000 - 113000) / (35000 / √50)

z = 2.02

From Appendix B.1, we can find that the probability of a z-score being less than or equal to 2.02 is 0.9772. Therefore, the probability of selecting a sample with a mean of at least $117,000 is 1 - 0.9772 = 0.0228, or about 2.28%.

d. To find the likelihood of selecting a sample with a mean of more than $107,000, we need to find the z-score corresponding to this sample mean:

z = (x - μ) / (σ / √n)

z = (107000 - 113000) / (35000 / √50)

z = -1.72

From Appendix B.1, we can find that the probability of a z-score being less than or equal to -1.72 is 0.0427. Therefore, the probability of selecting a sample with a mean of more than $107,000 is 1 - 0.0427 = 0.9573, or about 95.73%.

e. To find the likelihood of selecting a sample with a mean of more than $107,000 but less than $117,000, we need to find the z-scores corresponding to these sample means:

z1 = (107000 - 113000) / (35000 / √50)

z1 = -1.72

z2 = (117000 - 113000) / (35000 / √50)

z2 = 2.02

From Appendix B.1, we can find that the probability of a z-score being less than or equal to -1.72 is 0.0427, and the probability of a z-score being less than or equal to 2.02 is 0.9772. Therefore, the probability of selecting a sample with a mean of more than $107,000 but less than $117,000 is the difference between these probabilities, which is 0.9772 - 0.0427 = 0.9345, or about 93.45%.

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The differential dy for y = tan(4x + 6) when x = 4 and dx = 0.2 is 3.22, the differential dy for y = 3x² + 5x + 4 when x = 5 and dx = 0.2 is 30.20, and the change in y [tex]∆y[/tex] for y = [tex]4√x[/tex] when x = 2 and[tex]∆x = 0.3 is 0.848[/tex].

To find the differential of a function, we use the derivative, which is defined as the limit of the ratio of the change in y to the change in x as the change in x approaches zero. The differential dy is then given by the product of the derivative and the change in x, or simply dy = f'(x) dx.

For the function y = tan(4x + 6), we can find the derivative as follows: f'(x) = sec²(4x + 6) * 4 = 4 sec²(4x + 6) Substituting x = 4 and dx = 0.2, we get: dy = f'(4) * 0.2 = 4 sec²(22) * 0.2. Rounding to two decimal places, we get dy = 3.22.

For the function y = 3x² + 5x + 4, we can find the derivative as follows: f'(x) = 6x + 5 Substituting x = 5 and dx = 0.2, we get: dy = f'(5) * 0.2 = 6(5) + 5 * 0.2 Rounding to two decimal places, we get dy = 30.20.

For the function y = [tex]4√x[/tex], we can find the derivative as follows: f'(x) = 2/√x Substituting x = 2 and[tex]∆x = 0.3[/tex], we get: ∆y = f'(2) *[tex]∆x = 2/√2 * 0.3 = 0.848[/tex] Rounding to three decimal places, we get [tex]∆y = 0.848[/tex].

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The probability of rolling a 2 on a single die is 1/6, and the probability of rolling a 4 is also 1/6. To find the probability of both events occurring in sequence, you multiply their individual probabilities: (1/6) * (1/6) = 1/36, which is approximately 2.78%, rounded to the nearest whole number is 3%.

The probability of rolling a 2 on the first throw is 1/6 (since there are six equally likely outcomes when rolling a die). The probability of rolling a 4 on the second throw is also 1/6. To find the probability of rolling both a 2 and a 4, we multiply these probabilities: (1/6) x (1/6) = 1/36.

To convert this to a percentage and round to the nearest whole number, we multiply by 100 and round: 1/36 x 100 = 2.78, which rounds to 3%.

Therefore, the answer is C. 3%.

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Answer:

385 in ^3

Step-by-step explanation:

11 x 7 x 5

To obtain the following tableau, we pivot around the element at the intersection of the x1 column and the x6 row:

| BV | x1 | x2 | x3 | x4 | x5 | x6 | x7

A variable (from the Latin variabilis, "changeable") is a mathematical symbol. A variable can be a number, a vector, a matrix, a function, its argument, a set, or an element of a set.

To solve the given linear programming problem using the Big M method, we need to convert the problem into standard form by adding slack, surplus, and artificial variables as needed. Then, we use the simplex algorithm to iteratively improve the solution until we reach an optimal solution.

Let's first write the problem in standard form by introducing slack and artificial variables as follows:

Maximize Z = -2x1 + x2 - 4x3 + 3x4

Subject to:

x1 + x2 + 3x3 + 2x4 + x5 = 4

x1 - x3 + x4 - x6 = -1

2x1 + x2 + x7 = 2

x1 + 2x2 + x3 + 2x4 = 2

where x5, x6, x7 are slack and artificial variables.

We can see that the problem is infeasible because the last equation is inconsistent with the second equation. To make the problem feasible, we need to introduce artificial variables for the second equation and modify the objective function to penalize their use. This leads us to the following modified problem:

Maximize Z = -2x1 + x2 - 4x3 + 3x4 - M(x6 + x8)

Subject to:

x1 + x2 + 3x3 + 2x4 + x5 = 4

x1 - x3 + x4 + x6 - x8 = -1

2x1 + x2 + x7 = 2

x1 + 2x2 + x3 + 2x4 = 2

where x5, x6, x7, x8 are slack and artificial variables, and M is a large positive constant.

Now, we can construct the initial simplex tableau as follows:

| BV | x1 | x2 | x3 | x4 | x5 | x6 | x7 | x8 | RHS |

|----|----|----|----|----|----|----|----|----|-----|

| x5 | 1  | 1  | 3  | 2  | 1  | 0  | 0  | 0  |  4  |

| x6 | 1  | 0  | -1 | 1  | 0  | 1  | 0  | -1 | -1  |

| x7 | 2  | 1  | 1  | 0  | 0  | 0  | 1  | 0  |  2  |

| x8 | 1  | 1  | 2  | 1  | 0  | 0  | 0  | -1 |  2  |

| Z  | -2 | 1  | -4 | 3  | 0  | M  | 0  | -M |  0  |

The column for the objective function includes the coefficients of the original variables and the artificial variables, with the artificial variables having a coefficient of M in the objective function.

To perform the simplex algorithm, we select the most negative coefficient in the bottom row, which corresponds to x1, as the entering variable. We then select the row with the smallest nonnegative ratio of the RHS to the coefficient of the entering variable, which corresponds to x6, as the leaving variable. We pivot around the element in the intersection of the x1 column and the x6 row to obtain the next tableau:

| BV | x1 | x2 | x3 | x4 | x5 | x6 | x7

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We are similar to gram-negative. It must be noted that we are neither and have different cell characteristics compared to bacteria.

The bacterial cells are classified as gram postive and gram negative depending on their cell membrane structure. The gram negative bacteria are rich in lipid layer and thin peptidoglycan while gram postive have more peptidoglycan content.

Now, peptidoglycan are responsible for gram staining. Human epithelial cells do not have peptidoglycan which do not let them take up the stain. Hence, humans will be considered gram negative while noting the identity will be completely different.

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The blanks are filled as shown below

The product of the first and last terms is calculated as 10x^2 * 3 = 30.

We are then on a quest to discover two digits whose product equals 30 and when added together yields a result of 13.

10 * 3 = 30 and 10 + 3 = 13. then we have

10x^2 + 10x + 3x + 3

grouping them

(10^2 + 10x) + (3x + 3)

10x(x + 1) + 3(x + 1)

You can continue reducing the expression further:

= (10x + 3) (x + 1)

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Answer:

3.2

Step-by-step explanation:

Answer:

pythagorean theorem !!!!!!

Step-by-step explanation:

0.8²+1.6²=3.2²

0.64+2.56=10.24

THAT means the distance is

[tex] \sqrt{10.24} [/tex]

=3.2miles

The whiskers range from 4 to 19 and the box ranges from 7 to 18 with the vertical bar inside the box at 14. Then the correct option is B.

We know that,

The median of the data is the middle value of the data which is also known as the central tendency of the data and is known as the median.

The data set is given as; 12, 10, 16, 19, 18, 14, 4, 18, 4

Arrange the data in the ascending order

4, 4, 10, 12, 14, 16, 18, 18, 19

14 is the middle term that can be treated as a median.

Median = 14

The lowest set of data

4, 4, 10, 12

The lower quartile lies between 4 and 10. Then Q₁ will be

Q₁ = 10+ 4 /2

    = 7

Hence, the start of the box is at 7.

The upper set of data

16, 18, 18, 19

The lower quartile lies between 18 and 18. Then Q₃ will be

Q₃ = 18 + 18 /2

    = 18

Hence, the box range is between 7 and 18.

The whiskers range from 4 to 19 and the box ranges from 7 to 18 with the vertical bar inside the box at 14. Then the correct option is B.

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complete question:

Which box-and-whisker plot represents the data set?

12, 10, 16, 19, 18, 14, 4, 18, 4

A box and whisker plot. The whiskers range from 4 to 19 and the box ranges from 5 to 12.5 with the vertical bar inside the box at 6.

A box and whisker plot. The whiskers range from 4 to 19 and the box ranges from 7 to 18 with the vertical bar inside the box at 14.

A box and whisker plot. The whiskers range from 4 to 19 and the box ranges from 5 to 14 with the vertical bar inside the box at 7.5.

A box and whisker plot. The whiskers range from 4 to 19 and the box ranges from 6 to 14 with the vertical bar inside the box at 10.

The value of z is given as follows:

z = 38.

We have two secants in this problem, and point C is the intersection of the two secants, hence the angle measure of z is half the difference between the angle measure of the largest arc by the angle measure of the smallest arc.

The arc measures are given as follows:

138º and 62º.

Hence the value of z is obtained as follows:

z = 0.5 x (138 - 62)

z = 38.

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This means that if you get strong, then you are guaranteed to win races, according to the original statement.

a) We can convert the statement into propositional logic using the following symbols:

T: You train hard

E: You eat good food

S: You get strong

W: You win races

Using these symbols, the original statement can be represented as follows:

((T ∧ E) → S) ∧ (S → W)

This can be read as "If you train hard and eat good food, then you will get strong, and if you get strong, then you will win races."

b) We can use the propositional logic statement to answer this question. If you don't win races but do train hard, we know that the second part of the statement (S → W) is false, because if S (you get strong) were true, then W (you win races) would have to be true as well. Therefore, we can conclude that S (you get strong) must also be false. In plain English, this means that if you don't win races but do train hard, then you didn't get strong.

c) If you do get strong, we know that the second part of the statement (S → W) must be true, because if S (you get strong) is true, then W (you win races) must also be true. Therefore, we can conclude that if you get strong, then you will win races. In plain English, this means that if you get strong, then you are guaranteed to win races, according to the original statement.

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The Quasilinearization Method is a technique used to approximate solutions for nonlinear differential equations by linearizing them iteratively. It is particularly helpful when solving first-order IVPs.

A maximal solution to a first-order IVP is a solution that exists on the largest possible interval, while a minimal solution exists on the smallest possible interval.

Example 1:
Consider the first-order IVP: dy/dt = y^2, y(0) = 1.

Maximal solution: The maximal solution to this IVP is y(t) = 1/(1 - t) on the interval (-∞, 1).

Minimal solution: The minimal solution is the same as the maximal solution for this example, as there are no other solutions that exist on a smaller interval.

Example 2:
Consider the first-order IVP: dy/dx = x + y, y(0) = 0.

Maximal solution: The maximal solution to this IVP is y(x) = -x + e^x - 1 on the interval (-∞, +∞).

Minimal solution: The minimal solution is the same as the maximal solution for this example since there are no other solutions that exist on a smaller interval.

In both examples, the Quasilinearization Method can be applied to linearize the differential equations and approximate the solutions. The maximal and minimal solutions represent the largest and smallest possible intervals where the solutions are valid.

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The manager of a laptop computer dealership is considering a new bonus plan in order to increase sales. Currently, the mean sales rate per salesperson is five laptops per week.H0 (null hypothesis) represents the current situation, which is the mean sales rate per salesperson being 5 laptops per week. Ha (alternative hypothesis) represents the expected change, which is an increase in the mean sales rate due to the bonus plan.

The correct set of hypotheses for testing the effect of the bonus plan in this scenario is option c: H0: μ ≤ 5 Ha: μ > 5.
This is because the manager wants to increase sales, which means they are hoping for a higher mean sales rate per salesperson. Therefore, the null hypothesis (H0) is that the mean sales rate is less than or equal to 5 (the current rate), while the alternative hypothesis (Ha) is that the mean sales rate is greater than 5.

Option a (H0: μ < 5 Ha: μ ≥ 5) and option d (H0: μ > 5 Ha: μ < 5) both assume that the manager wants to maintain the current sales rate or decrease it, which is not the case. Option b (H0: μ > 5 Ha: μ < 5) assumes that the manager wants to decrease the sales rate, which is also not the case.

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The standard deviation of this sample of counts is 2.07.

To find the standard deviation of this sample of counts, we first need to calculate the mean (average) of the counts. Adding up all of the counts and dividing by 6, we get:
[tex]= (\frac{53 + 49 + 54 + 51 + 48 + 5)}{6})[/tex]
So the mean is 51.

Now we can calculate the variance, which measures how spread out the data is from the mean. We do this by finding the average of the squared differences between each count and the mean:

[tex]\frac{(53 - 51)^{2}+ (49 - 51)^{2}+(54 - 51)^{2}+(51 - 51)^{2}+(48 - 51)^{2}+ (51 - 51)^{2}}{6} = 4.3[/tex]

The variance is 4.3. To get the standard deviation, we take the square root of the variance:
[tex]\sqrt{4.3}=2.07[/tex] .

So the standard deviation of this sample of counts is 2.07.

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Answer:

[tex]3^{21}[/tex]

Step-by-step explanation:

using the rules of exponents

[tex]a^{m}[/tex] × [tex]a^{n}[/tex] = [tex]a^{(m+n)}[/tex]

[tex](a^m)^{n}[/tex] = [tex]a^{mn}[/tex]

given

(3² × [tex]3^{5}[/tex] )³

= ([tex]3^{(2+5)}[/tex] )³

= ([tex]3^{7}[/tex] )³

= [tex]3^{7(3)}[/tex]

= [tex]3^{21}[/tex]

The correct graph of function f(x) =-3ˣ - 2 is shown in option 4.

We have to given that;

Function is,

⇒ f(x) = -3ˣ - 2

Now, In option 4;

Take a point (0, - 3) into function as;

Plug x = 0, y = - 3;

⇒ f(x) = -3ˣ - 2

⇒ - 3 = - 3⁰ - 2

⇒ - 3 = - 1 - 2

⇒ - 3 = - 3

Thus, The correct graph of function f(x) =-3ˣ - 2 is shown in option 4.

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a) A basis for the solution space is the vector (3/4, 1, -1/4).

b) The dimension of the solution space is 1.

c) Basis for the row space is the vector (1, -2, 3, 2).

a) To find a basis for the solution space (nullspace) of the coefficient matrix, we can solve for the variables in terms of the free variable.

Starting with the augmented matrix [A|0]:

| 1  -2  3  2 |
| -3  6  -9  2 |

We can perform row operations to simplify the matrix:

R2 = R2 + 3R1

| 1  -2  3  2 |
| 0  0  0  8 |

Now, we can solve for the variables in terms of the free variable:

x - 2y + 3z = -2z

z = -1/4t
y = t
x = 3/4t

So the solution space can be written as:

t * (3/4, 1, -1/4)

Thus, a basis for the solution space is the vector (3/4, 1, -1/4).

b) The dimension of the solution space (nullity) is the number of free variables, which in this case is 1.

So the dimension of the solution space is 1.

c) To find a basis for the row space of the coefficient matrix, we can row reduce the matrix and take the non-zero rows as a basis.

Starting with the augmented matrix [A|0]:

| 1  -2  3  2 |
| -3  6  -9  2 |

We can perform row operations to simplify the matrix:

R2 = R2 + 3R1

| 1  -2  3  2 |
| 0  0  0  8 |

The row space is spanned by the non-zero rows of the row reduced matrix:

(1, -2, 3, 2)

So a basis for the row space is the vector (1, -2, 3, 2).

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To find the z-value needed to calculate one-sided confidence bounds for an 81% confidence level, we first need to determine the area under the normal distribution curve to the left of the confidence level. Since we are looking for one-sided confidence bound, we only need to consider the area to the left of the mean.

Using a standard normal distribution table or calculator, we can find that the area to the left of the mean for an 81% confidence level is 0.905.

Next, we need to find the corresponding z-value for this area. We can use the inverse normal distribution function to do this.

z = invNorm(0.905)

Using a calculator or a table, we can find that the z-value for an area of 0.905 is approximately 1.37.

Therefore, the z-value needed to calculate one-sided confidence bounds for an 81% confidence level is 1.37 (rounded to two decimal places).
The z-value needed to calculate a one-sided confidence bound with an 81% confidence level.

1. First, since it's one-sided confidence bound, we need to find the area under the standard normal curve that corresponds to 81% confidence. This means the area to the left of the z-value will be 0.81.

2. Now, to find the z-value, we can use a z-table or an online calculator that provides the z-value corresponding to the cumulative probability. In this case, the cumulative probability is 0.81.

3. Using a z-table or an online calculator, we find that the z-value corresponding to a cumulative probability of 0.81 is approximately 0.88.

So, the z-value needed to calculate a one-sided 81% confidence bound is 0.88, rounded to two decimal places.

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The  area of the lateral face of cylinder = 75.4 in²

The  area of the two bases of the cylinder = 25.13 in²

The total surface area of the cylinder =  100.53 in²

We know that the formula for the surface area of cylinder is:

A = 2πrh + 2πr²

where r is the radius of the cylinder

and h is the height of the cylinder

Here, r = 2 in and h = 6 in

The area of the lateral face of cylinder is given by,

A₁ = 2 × π × r × h

A₁ = 2 × π × 2 × 6

A₁ = 24 × π

A₁ = 75.4 sq. in.

And the area of two base is,

A₂ = 2πr²

A₂ = 2 × π × 2²

A₂ = 8 × π

A₂ = 25.13 sq. in.

The total surface area of cylinder would be,

A = A₁ + A₂

A = 75.4 + 25.13

A = 100.53 sq. in.

Therefore, the required area = 100.53 in²

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The graph of the inequality is x + 2 ≥ 6 is plotted

Given data ,

Let the inequality equation be represented as A

Now , the value of A is

x + 2 ≥ 6

Subtracting 2 on both sides , we get

x ≥ 4

So , the inequality is x ≥ 4 and the graph is plotted

Hence , the inequality is x ≥ 4

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the answer to your question is  130

The age of a movie attendee with a z-score of 0.89 is approximately 41 years.

Normal distribution problem

Let's use the standard normal distribution table or a calculator to find the proportion/probability corresponding to the given z-score of 0.89, and then use the inverse z-score formula to find the corresponding age value.

Using a standard normal distribution table, the proportion/probability corresponding to a z-score of 0.89 is 0.8133.

Using the inverse z-score formula:

Rearranging the formula to solve for x, we get:

Therefore, the age of a movie attendee with a z-score of 0.89 is approximately 41 years rounded to the nearest whole number.

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