the volume of the small cube below is 1cm^3 estimate the volume of the cuboid

a random variable x, the number of successes, follows a Poisson process, then the probability of success for any two intervals of the same size.

A) is the same

The correct answer is A) is the same.

Probability is a way to gauge how likely something is to happen. Many things are difficult to forecast with absolute confidence. Using it, we can only make predictions about the likelihood of an event happening, or how likely it is. The probability can be between 0 and 1.

In a Poisson process, the probability of success within a certain time interval is determined only by the length of the interval and the rate of success. Therefore, any two intervals of the same size will have the same probability of success, regardless of when the intervals occur.

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The closed-form expression for the given summation is (3n^2 + 7n) / (2n^2). Using this formula, the sums for n = 10, 100, 1000, and 10,000 are 37/20, 307/200, 3007/2000, and 30007/20000, respectively.

The given expression can be rewritten using the summation formulas as

∑nj=1 3j+2/n2 = (3(1)+2)/n2 + (3(2)+2)/n2 + ... + (3(n)+2)/n2

Let's simplify this expression by factoring out the common term of 1/n2

= (3/n2)(1 + 2 + ... + n) + (2/n2)(1 + 1 + ... + 1)

= (3/n2)(n(n+1)/2) + (2/n2)(n)

= (3n(n+1) + 4n) / (2n2)

= (3n^2 + 7n) / (2n^2)

Therefore, we have the closed-form expression for S(n) as

S(n) = (3n^2 + 7n) / (2n^2)

Using this formula, we can find the sums for n = 10, 100, 1000, and 10,000

S(10) = (3(10^2) + 7(10)) / (2(10^2)) = 37/20

S(100) = (3(100^2) + 7(100)) / (2(100^2)) = 307/200

S(1000) = (3(1000^2) + 7(1000)) / (2(1000^2)) = 3007/2000

S(10000) = (3(10000^2) + 7(10000)) / (2(10000^2)) = 30007/20000

Therefore, the sums for n = 10, 100, 1000, and 10,000 are 37/20, 307/200, 3007/2000, and 30007/20000, respectively.

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Answer:

answer is (-2,5)

Step-by-step explanation:

gonna make 2 by 5 into Percent

x=0.4y-4

3x-9y=-51

step 2 Add 3 into first column and make it negative

-3x=-1.2y+12

then move y to other side

-3x+1.2y=12

3x-9y=-51

-7.8y=-39

y=5

U got y now

add it into y in first column

x= 2/5(5)-4

then it be 2-4= -2

x=-2

+) Replace x = (2/5)y - 4 into 3x - 9y = -51

[tex] 3 \times ( \frac{2}{5} y - 4) - 9y = - 51 \\ [/tex]

[tex] \frac{6}{5} y - 12 - 9y = - 51[/tex]

[tex]\frac{6}{5} y - 9y = - 51 + 12 = - 39[/tex]

[tex] \frac{ - 39}{5} y = - 39[/tex]

[tex]y = (- 39) \div \frac{( - 39)}{5} = ( - 39) \times \frac{5}{( - 39)} [/tex]

[tex]y = 5[/tex]

[tex]x = \frac{2}{5} y - 4 = \frac{2}{5} \times 5 - 4 = 2 - 4 [/tex]

[tex]x = - 2[/tex]

Ans: (x;y) = (-2;5)

Ok done. Thank to me >:33

Answer:

simplifying

Step-by-step explanation:

The image of triangle EFG after rotation 90 degrees countercloeckwise is shown below.

We know that when we rotate a point P(x, y) 90 degrees counterclockwise about the origin then the coordinates of point after rotation becomes (-y, x)

Here the coordinates of the triangle EFG are:

E(4, -8)

F(4, -1)

G(3, -9)

We need to rotate triangle EFG 90 degrees counterclockwise.

With the help of above statement the coordinates of rotated triangle would be,

E'(8, 4)

F'(1, 4)

G'(9,3)

The transformed triangle is shown below.

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The statement " An example of continuous data would be the numbers on baseball player jerseys" is false because the numbers on baseball player jerseys represent a finite set of distinct values, which makes them an example of discrete data, not continuous data.

Continuous data is data that can take on any value within a range or interval. This means that the data can be measured and expressed as a decimal or a fraction, and there are an infinite number of possible values within the range. For example, the height of a person can be any value between 5 feet and 6 feet, including all the possible fractions or decimals in between.

On the other hand, discrete data is data that can only take on certain distinct values. These values cannot be measured or expressed as a decimal or a fraction. Examples of discrete data include the number of children in a family, the number of students in a classroom, or the number of books on a shelf.

In the case of baseball player jerseys, the numbers are assigned to players based on a finite set of integers (typically 0 to 99), and there are no fractional or decimal values in between. Therefore, the numbers on baseball player jerseys are an example of discrete data, not continuous data.

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It will take approximately 67 months to have $10,000 to buy a boat with monthly deposits of $140 at a 3% monthly compounded interest rate.

To determine how long it will take to save $10,000 with monthly deposits of $140 at a 3.0% interest rate compounded monthly, we'll use the future value of a series formula:
FV = P * (((1 + r)^n - 1) / r)
Where:
FV = future value of the series ($10,000)
P = monthly deposit ($140)
r = interest rate per period (0.03 / 12)
n = number of periods (number of months)
Rearrange the formula to solve for n:
n = ln((FV * r / P) + 1) / ln(1 + r)
Plug in the values:
n = ln((10,000 * (0.03 / 12) / 140) + 1) / ln(1 + (0.03 / 12))
n ≈ 62.1
Since we need to round up to the next whole month, it will take approximately 63 months to save $10,000 to buy the boat.

It will take approximately 67 months to have $10,000 to buy a boat. Using the formula for compound interest, we can calculate the future value of monthly deposits of $140 at a rate of 3% compounded monthly:
FV = PMT * ((1 + r)^n - 1) / r
Where:
PMT = $140 (monthly deposit)
r = 0.03/12 (monthly interest rate)
n = number of months
We want to find the value of n that gives us a future value of $10,000:
$10,000 = $140 * ((1 + 0.03/12)^n - 1) / (0.03/12)
Simplifying and solving for n, we get:
n = log(1 + ($10,000 * 0.03/12 / $140)) / log(1 + 0.03/12)
n ≈ 66.8
Since we can't have fractional months, we round up to the next higher month:
n ≈ 67
Therefore, it will take approximately 67 months to have $10,000 to buy a boat with monthly deposits of $140 at a 3% monthly compounded interest rate.

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The value of the population standard deviation necessary to produce a standard error of 3 points is 18 points. The value of the population standard deviation necessary to produce a standard error of 12 points is 72 points. The value of the population standard deviation necessary to produce a standard error of 2 points is 12 points.

To calculate the value of the population standard deviation (σ) necessary to produce each of the following standard error values for a sample of n = 36 scores, we can use the formula:

σM = σ / √n
where σM is the standard error of the mean, σ is the population standard deviation, and n is the sample size.

1. If σM = 12 points, then:
12 = σ / √36
12 = σ / 6
σ = 12 x 6
σ = 72 points

Therefore, the value of the population standard deviation necessary to produce a standard error of 12 points is 72 points.

2. If σM = 3 points, then:
3 = σ / √36
3 = σ / 6
σ = 3 x 6
σ = 18 points

Therefore, the value of the population standard deviation necessary to produce a standard error of 3 points is 18 points.

3. If σM = 2 points, then:
2 = σ / √36
2 = σ / 6
σ = 2 x 6
σ = 12 points

Therefore, the value of the population standard deviation necessary to produce a standard error of 2 points is 12 points.

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Using a trigonometric relation we can see that the value of x is 3,549.3 ft

We can see that we have a right triangle, where x is the hypotenuse.

We know one angle of the triangle and the opposite cathetus of said angle.

Then we need to use the trigonometric relation:

sin(a) = (opposite cathetus)/hypotenuse.

Replacing the things that we know we will get.

sin(25°) = 1500ft/x

Solving that for x we will get:

x = 1500ft/sin(25°)

x = 3,549.3 ft

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The value of the triple integral ∭bzex ydv over the box b determined by 0≤x≤4, 0≤y≤3, and 0≤z≤3 is [tex]27e^{12} - 36.[/tex]

What is integration?

Integration is a fundamental concept in calculus that involves finding the integral of a function.

To evaluate the triple integral ∭bzex ydv over the box b determined by 0≤x≤4, 0≤y≤3, and 0≤z≤3, we integrate with respect to z, y, and then x.

∭bzex ydv = [tex]\int\limits^3_0 \int\limits^3_0\int\limits^4_0 bzex y\ dx\ dy\ dz[/tex]

Integrating with respect to x, we get:

[tex]\int\limits^4_0 bzex\ y\ dx\ = bzex\ y\ |^4_0 = bze 4^y - bz[/tex]

Substituting this result into the triple integral, we get:

∭bzex ydv = [tex]\int\limits^3_0 \int\limits^3_0(bze 4^y - bz) dy dz[/tex]

Integrating with respect to y, we get:

[tex]\int\limits^3_0 (bze4^y - bz) dy = (1/4)bze4^y - bzy|_0^3 = (1/4)bz(e^{12} - 1) - 3bz[/tex]

Substituting this result into the triple integral, we get:

∭bzex ydv = [tex](1/4)bz(e^{12} - 1) - 3bz) \int\limits^3_0 dz[/tex]

Integrating with respect to z, we get:

[tex]\int\limits^3_0 (1/4)bz(e^{12} - 1) - 3bz) dz = (9/4)bz(e ^{12} - 1) - 9bz[/tex]

Substituting this result into the triple integral, we get:

∭bzex ydv =[tex](9/4)bz(e^{12} - 1) - 9bz)[/tex]

Now, substituting the limits of integration, we get:

∭bzex ydv = [tex](9/4)(4)(e_{-1} ^{12} - 1) - 9(4) = 27e^{12} - 36[/tex]

Therefore, the value of the triple integral ∭bzex ydv over the box b determined by 0≤x≤4, 0≤y≤3, and 0≤z≤3 is [tex]27e^{12} - 36.[/tex]

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Doing some changes of units, we can see that the total volume is V = 1.5 gal

We know that the recipe that Janelle follows is the following one:

So we need to do some changes of units, we know that:

1 pint = 0.125 gal

Then:

5 pints = 5*(0.125 gal) = 0.625 gal

Then for the orange juice we have:

1 cup = 0.0625 gal

Then for the 14 cups of apple and grape juice we have:

14*(0.0625 gal) = 0.875 gal

Adding that we have the total volume:

0.625 gal + 0.875 gal = 1.5 gal

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To find the PDF of Z = X + Y when X and Y have the given joint PDF, f(x,y) = 1/900 for 0≤x,y≤3, and 0 otherwise.

Step 1: Identify the range of Z. Since X and Y range from 0 to 3, the minimum value for Z is 0 (when X = 0 and Y = 0) and the maximum value for Z is 6 (when X = 3 and Y = 3).

Step 2: Find the marginal PDFs of X and Y. Since X and Y are uniformly distributed, we have f_X(x) = 1/3 for 0≤x≤3 and f_Y(y) = 1/3 for 0≤y≤3.

Step 3: Compute the convolution of the marginal PDFs.

To find the PDF of Z = X + Y, we need to compute the convolution of f_X(x) and f_Y(y): f_Z(z) = ∫ f_X(x) * f_Y(z-x) dx

Now, let's compute the convolution for different ranges of Z:

a) 0≤z≤3: f_Z(z) = ∫(1/3)(1/3) dx from x=0 to x=z f_Z(z) = (1/9)[x] from 0 to z f_Z(z) = z/9

b) 3

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Answer:

Step-by-step explanation:

[tex]6 + 36x + 72x^2 + 96x^3[/tex] / 3! + ... this is the Maclaurin series for f(x). Note that since e^x has a well-known Maclaurin series, we were able to simplify the original expression before finding the series.

The problem asks us to find the Maclaurin series for the function:

[tex]f(x) = 6e^x e^4x[/tex] sigma^infinity_n=0 (1^n / n!)

To do this, we first need to recognize that the expression inside the sigma notation is actually the Maclaurin series for e^x:

sigma^infinity_n=0 (1^n / n!) = e^x

We can substitute this expression into the original function to get:

[tex]f(x) = 6e^x e^4x e^x[/tex]

Now we can simplify this expression using the laws of exponents:

[tex]f(x) = 6e^x * e^(4x) * e^x[/tex]

f(x) = 6e^(6x)

Now we need to express this function as a Maclaurin series. We can start by writing out the first few terms of the series:

[tex]f(x) = 6e^(6x)[/tex]

[tex]= 6(1 + 6x + (6x)^2 / 2! + (6x)^3 / 3! + ...)[/tex]

[tex]= 6 + 36x + 72x^2 + 96x^3 / 3! + ...[/tex]

This is the Maclaurin series for f(x). Note that since e^x has a well-known Maclaurin series, we were able to simplify the original expression before finding the series.

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The differential of arc length for the curve C parametrized by r(t) is given by:

ds = sqrt((dx/dt)² + (dy/dt)²) dt

where x =  [tex]e^t[/tex]² and y = ln(t+1).

Taking the derivatives, we get:

dx/dt = 2t ([tex]e^t[/tex])²
dy/dt = 1/(t+1)

Substituting into the formula, we get:

ds = sqrt((2t [tex]e^t[/tex]²)² + (1/(t+1))²) dt

Simplifying, we get:

ds = sqrt(4t²e²t² + 1/(t+1)²) dt

Therefore, the differential of arc length for the curve C parametrized by r(t) is:

ds = sqrt(4t²e²t² + 1/(t+1)²) dt.

This formula allows us to calculate the length of the curve C between two points on the curve by integrating the differential of arc length between the corresponding values of t.

The formula shows that the length of the curve increases as t increases, with the rate of increase depending on the values of t and e.

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Answer:

[tex] {x}^{2} - 36 = 5x[/tex]

[tex] {x}^{2} - 5x - 36 = 0[/tex]

[tex](x - 9)(x + 4) = 0[/tex]

[tex]x = 9[/tex]

Answer:

vertex = (- 4, - 2 )

Step-by-step explanation:

given a parabola in standard form

f(x) = ax² + bx + c ( a ≠ 0 )

then the x- coordinate of the vertex is

[tex]x_{vertex}[/tex] = - [tex]\frac{b}{2a}[/tex]

f(x) = 2x² + 16x + 30 ← is in standard form

with a = 2 , b = 16 , then

[tex]x_{vertex}[/tex] = - [tex]\frac{16}{2(2)}[/tex] = - [tex]\frac{16}{4}[/tex] = - 4

substitute x = - 4 into f(x) for corresponding y- coordinate

f(- 4) = 2(- 4)² + 16(- 4) + 30

      = 2(16) - 64 + 30

      = 32 - 34

     = - 2

vertex = (- 4, - 2 ) or x = - 4 , y = - 2

Answer:

3400

Step-by-step explanation:

3.4 x 1000 =3400

to go from km a big unit to meters a smaller unit, you multiply by 1000

The area of the composite shape is 40.57 square m and the perimeter is 34.57 meters

The surface area of composite shapes can be found by breaking the composite shape down into simpler shapes and then finding the surface area of each individual shape.

Here, we have

Area = Area of rectangle + circle

So, we have

Area = 4 * 7 + 22/7 * (4/2)^2

Area = 40.57 square m

So, the area is 40.57 square m

For the perimeter, we have

Perimeter = 2 * (4 + 7) + 2 * 22/7 * (4/2)

Perimeter = 34.57

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To solve this problem, we can use the principle of inclusion-exclusion.

First, let's find the total number of ways to select n students from a class of 5n:

Total ways = (5n choose n) = (5n)! / (n!*(5n-n)!) = (5n)! / (n!*(4n)!)

The probability that the average amount of paid time lost during a three-month period for the 100 blue-collar workers will exceed 1.5 days is 0.0228.

Since the sample size n = 100 is sufficient, we can apply the central limit theorem to roughly approximate the distribution of the sample mean.

Let X represent the total paid time a single blue-collar worker missed during a three-month period. Given that the population mean is 1.3 days and the population standard deviation is 1.0 days, X N(1.3, 1.02) follows.

Let Y be the sample mean of X for a sample of 100 blue-collar workers selected at random. So, according to the central limit theorem, Y = N(1.3, 1.02/100).

We are looking for P(Y > 1.5). By standardized Y, we obtain:

Z is defined as (Y - ) / (n /√(n)) = (1.5 - 1.3) / (1.0 / √(100)). = 2

The probability of the event that average amount of the paid time loss is 0.0288.

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Complete question - In an article in the Journal of Management, Joseph Martocchio studied and estimated the costs of employee absences. Based on a sample of 176 blue-collar workers, Martocchio estimated that the mean amount of paid time lost during a three-month period was 1.3 days per employee with a standard deviation of 1.0 days. Martocchio also estimated that the mean amount of unpaid time lost during a three-monthperiod was 1.4 day per employee with a standard deviation of 1.2 days.

Suppose we randomly select a sample of 100 blue-collar workers. Based on Martocchio's estimates:

(a)What is the probability that the average amount of paid time lost during a three-month period for the 100 blue-collar workers will exceed 1.5 days?

Answer:

Step-by-step explanation:

A. Let x be the mass of 1 slice of cheese.

B. The difference in the masses of 1 slice of cheese and 1 cracker is:

x - 3.25 grams

C. Since one package contains 16 slices of cheese, the total mass of the package is:

16x

According to the problem, the mass of one cracker is 18 grams less than the mass of one slice of cheese. Therefore, we can write:

x - 18 = 3.25 + m/16

where m is the mass of the package of 16 slices of cheese.

Simplifying the equation:

x = 3.25 + m/16 + 18

x = m/16 + 21.25

This equation represents the relationship between the masses of 1 cracker and 1 slice of cheese in terms of the mass of a package of 16 slices of cheese.

We will need 7 cubic feet of dirt to fill the garden box completely.

The formula for the volume of a rectangular box is:
Volume = Length × Width × Height

In this case, the dimensions of the garden box are:
Length = 3 1/2 feet
Width = 4 feet
Height = 1/2 foot
First, convert the mixed numbers to improper fractions:
Length = (3 × 2 + 1)/2 = 7/2 feet
Now, multiply the dimensions together:
Volume = (7/2) × 4 × (1/2)
Simplify the fractions:
Volume = (7 × 4 × 1) / (2 × 2) = 28 / 4
Finally, divide to find the volume in cubic feet:
Volume = 28 ÷ 4 = 7 cubic feet.

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If h(x) = 6 5f(x) , where f(5) = 6 and f '(5) = 4, then h'(5). h'(5) =20

To find h'(5) given h(x) = 6 + 5f(x), f(5) = 6, and f'(5) = 4, follow these steps:

1. Differentiate h(x) with respect to x: h'(x) = 0 + 5f'(x) (since the derivative of a constant is 0, and we use the chain rule for the second term).

2. Now, h'(x) = 5f'(x).

3. Plug in the given values: h'(5) = 5f'(5).

4. Since f'(5) = 4, substitute this value: h'(5) = 5 * 4.

5. Compute the result: h'(5) = 20.

So, h'(5) = 20.

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Number of Folds | Style 1 Number of Sections | Style 2 Number of Sections:

From the table, the pattern relating the number of folds to the number of sections for Style 1 (accordion-style) is that the number of sections doubles with each additional fold. In other words, the number of sections is equal to 2 raised to the power of the number of folds. For Style 2 (half-folds), the pattern is less clear, but we can observe that the number of sections increases more rapidly with each additional fold than it does for Style 1. This is likely due to the fact that each fold in Style 2 creates two new sections, whereas in Style 1, each fold only creates one new section.

The two different folded styles of paper produce different results because they create different shapes and arrangements of rectangular sections when folded. In Style 1 (accordion-style), each fold creates a single new section that is added to the end of the folded paper. The result is a long, thin strip of paper with rectangular sections stacked on top of each other. In contrast, Style 2 (half-folds) creates a zig-zag pattern of rectangular sections that are stacked on top of each other. Each fold in Style 2 creates two new rectangular sections, which allows the number of sections to increase more rapidly than in Style 1. This difference in the way the paper is folded and the resulting shapes and arrangements of rectangular sections leads to different patterns in the number of sections as the number of folds increases.

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f(x) = sqrt(x^2 + x)

Yes, f(x) is O(x^2) because sqrt(x^2 + x) is dominated by x when x is sufficiently large.

f(x) = 17x^(11)

Yes, f(x) is O(x^2) because 17x^11 is dominated by x^2 when x is sufficiently large.

f(x) = x^(2/1000)

Yes, f(x) is O(x^2) because x^(2/1000) is dominated by x^2 when x is sufficiently large.

f(x) = x^42

Yes, f(x) is O(x^2) because x^42 is dominated by x^2 when x is sufficiently large.

f(x) = ⌊x⌋⋅⌈x⌉

Yes, f(x) is O(x^2) because ⌊x⌋⋅⌈x⌉ is bounded above by x^2 when x is sufficiently large.

f(x) = log(2x)

No, f(x) is not O(x^2) because log(2x) grows much more slowly than x^2 when x is sufficiently large.

f(x) = xlog(x)

No, f(x) is not O(x^2) because xlog(x) grows much more slowly than x^2 when x is sufficiently large.

f(x) = sqrt(x^2 + x)

Yes, f(x) is O(x^2) because sqrt(x^2 + x) is dominated by x when x is sufficiently large.

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Out of the given options, the task that is not a likely task of descriptive statistics is "estimating unknown parameters."

Descriptive statistics is a branch of statistics that deals with the collection, analysis, and interpretation of data. It involves summarizing and presenting data in a meaningful way using measures of central tendency, variability, and other statistical tools.

This task is usually carried out in inferential statistics, which involves drawing conclusions about a population based on a sample.

Descriptive statistics, on the other hand, is focused on describing and summarizing the characteristics of a sample or population, rather than making inferences about it.

Therefore, while summarizing a sample, making visual displays of data, and presenting measures of central tendency and variability are all common tasks in descriptive statistics, estimating unknown parameters is not typically a part of descriptive statistics.

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Answer:  The store can sell 451 packs of socks.

Step-by-step explanation:  To find the number of packs of socks the store can sell, we need to divide the total number of socks by the number of socks in each pack.

Since each pack contains 3 pairs of socks, or 6 individual socks, we can find the number of packs by dividing the total number of socks by 6:

1353 socks ÷ 6 socks per pack = 225.5 packs

However, since we can't sell a fraction of a pack, we need to round up to the nearest whole number. Therefore, the store can sell 451 packs of socks.

Share Prompt

The set of parameters that would give this person the worst grade on the exam relative to others is µ = 70 and σ = 5. This can be found using z-score. The correct option is option c).

To determine which set of parameters would give this person the worst grade on the exam relative to others, we need to find the z-score for the score of 65 under each set of parameters and see which one is the lowest. The z-score is a measure of how many standard deviations a particular value is from the mean.

The formula for calculating the z-score is:

z = (x - µ) / σ

where x is the score, µ is the mean, and σ is the standard deviation.

a. µ = 60 and σ = 5

z = (65 - 60) / 5 = 1

b. µ = 70 and σ = 10

z = (65 - 70) / 10 = -0.5

c. µ = 70 and σ = 5

z = (65 - 70) / 5 = -1

d. µ = 60 and σ = 10

z = (65 - 60) / 10 = 0.5

The lowest z-score is -1, which corresponds to option c. This means that most people scored higher than 65, and those who scored lower did so by a smaller margin.

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