Parametric statistics could be used to analyze which of the following dependent variables (select all correct answers).
Grams of iron in a meal
Students' zip codes
Minutes spent on this test
Type of favorite cookie
Snacks eaten in a week
Job titles

Answer: It’s 3

Step-by-step explanation:

Hoped I help :)

Answer:

360

Step-by-step explanation:

Answer:

I don't know.

Step-by-step explanation:

To prove that the set S = 2Z = {2x : x ∈ Z}, the set of even integers, is equicardinal with Z, the set of all integers, we need to show that there exists a one-to-one correspondence (bijection) between the two sets.

A one-to-one correspondence between two sets exists if every element of one set is paired with a unique element from the other set, and vice versa.

Let's define a function f: Z -> S such that f(x) = 2x for every x ∈ Z.

This function assigns each integer x from Z to its corresponding even integer 2x in S.

To prove that f is a bijection, we need to show that it is both injective (one-to-one) and surjective (onto).

Injectivity: Suppose f(a) = f(b) for some a, b ∈ Z. Then, 2a = 2b. Dividing both sides by 2, we get a = b. Hence, f is injective.

Surjectivity: For every y ∈ S, y = 2x for some x ∈ Z. Choosing x = y/2, we have f(x) = 2x = y. Therefore, f is surjective.

Since f is both injective and surjective, it is a bijection. Thus, S and Z are equicardinal sets.

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Answer:

C)  6

Step-by-step explanation:

use slope formula:

(-4 - 3) / (-1 - x) = 1

cross-multiply:

-7 = -1 - x

-6 = -x

6 = x

Answer:

f(x) = 76

Step-by-step explanation:

All you do is plug-in for x: (x = 9)

f(x) = 8x + 4

f(x) = 8(9) + 4

f(x) = 72 + 4

f(x) = 76

Answer:

this is hard to tell and sorry if I'm wrong but I would say it is only a

Step-by-step explanation:

Aanything in the shaded area is correct if it's not it's wrong

Answer:

the eanswer should be 12

Step-by-step explanation:

i took the test

The Europay, Mastercard and Visa (EMV) for not purchase the snow removal machine is $31,000.

The expected monetary value (EMV) for not purchasing the snow removal machine is $31,000. This value is calculated by multiplying the probabilities of each winter condition by the corresponding profits and summing them up. The probabilities for a mild winter, typical winter, and severe winter are 0.3, 0.5, and 0.2, respectively.

The profits for each condition without the machine are $20,000, $530,000, and $50,000. By multiplying each profit by its probability and adding them together, we get the EMV of $31,000 for not purchase the machine.

In detail, the EMV is calculated as follows:

EMV = (Probability of Mild Winter * Profit for Mild Winter) + (Probability of Typical Winter * Profit for Typical Winter) + (Probability of Severe Winter * Profit for Severe Winter)

EMV = (0.3 * $20,000) + (0.5 * $530,000) + (0.2 * $50,000)

EMV = $6,000 + $265,000 + $10,000

EMV = $31,000

Therefore, the EMV for not purchasing the snow removal machine is $31,000.

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Answer:

The distance between corner to corner is equal to √10 times the width.

D = √10*W

Step-by-step explanation:

For a rectangle of length L and width W, the distance between two opposite corners can be calculated if we use the Pythagorean's theorem, where we can think on the length as one cathetus, the width as another cathetus and the diagonal as the hypotenuse.

Then the length of the diagonal is:

D^2 = L^2 + W^2

D = √( L^2 + W^2)

In this case we know that the length is 3 times the width, then:

L = 3*W

Replacing this in the equation for the diagonal we have:

D = √( (3*W)^2 + W^2) = √( 9*W^2 + W^2)

D = √( 10*W^2) = √10*√W^2 = √10*W

D = √10*W

The distance between corner to corner is equal to √10 times the width.

Z-score is used to test the hypothesis that the part is coming out longer than usual. Z-score is defined as the number of standard deviations away from the mean.

It is calculated using the formula z = (x - μ) / σ, where x is the sample mean, μ is the population mean, and σ is the population standard deviation. In the given problem, the population mean is μ = 12.05 cm and the population standard deviation is σ = 0.119 cm. The sample mean is x = 12.25 cm. The sample size is n = 19.

Therefore, the formula to calculate the z-score is Z = (x - μ) / (σ / √n) Substituting the values, we get z = (12.25 - 12.05) / (0.119 / √19) ≈ 6.586Therefore, the z-score which would be used to test the hypothesis that the part is coming out longer than usual is approximately 6.586.

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Answer:

3.14152628283829299348473929

Answer:

Step-by-step explanation:

To find each probability you will state the probability of the first event happening and multiply it by the chance of the second event happening.  

P(2 Nickels):  6/10 x 5/9 = 30/90 (1/3 chance)

P(2 Dimes):  4/10 x 3/9 = 12/90 (4/30 chance)

P(1 nickel and 1 dime): 6/10 x 4/9 = 24/90 (8/30 chance)

I hope this helps :D

Answer:

its 2

Step-by-step explanation:

I have consulted many nice people ( my idiot friends) they all say 2 good luck

Answer: 4x-3

Step-by-step explanation: use the slope formula to calculate the slope, then add the y-int to the equation and ur done hope this helps

Answer:

H

Step-by-step explanation:

The rectangle has a length of (2x + 1) and a width of (5x - 4).

And we want to select the expression that represents the rectangle's area.

Recall that a rectangle's area is simply its length multiplied by its width. Thus:

[tex]A=(2x+1)(5x-4)[/tex]

Expand by distributing:

[tex]A=(2x+1)(5x)+(2x+1)(-4)[/tex]

Distribute:

[tex]A=(10x^2+5x)+(-8x-4)[/tex]

Simplify:

[tex]A=10x^2-3x-4[/tex]

Hence, our answer is H.

Answer:

option a is the answer to the question

Answer:

1.8 inches

Step-by-step explanation:

1. find the # of inches that represents 1 foot.

3/25 = 0.12in

2. to find the length of the line segment that represents 15 feet, multiply 0.12 inches by 15.

0.12*15 = 1.8in

Answer:

x = [-b ±√(b² - 4ac)]/2a

Step-by-step explanation:

ax² + bx + c = 0

dividing through by a, we have

ax²/a + bx/a + c/a = 0

x² + bx/a + c/a = 0

x² + bx/a = -c/a

we now add th square of half the coefficient of x to both sides, thus

x² + bx/a + (b/2a)² = -c/a +  (b/2a)²

simplifying the left hand side and right hand side, we have

(x + b/2a)² = -c/a + b²/4a²

re-arranging, we have

(x + b/2a)² = b²/4a² - c/a

taking L.C.M of the right hand side, we have

(x + b/2a)² = (b² - 4ac)/4a²

taking square-root of both sides, we have

√(x + b/2a)² = ±√[(b² - 4ac)/4a²]

x + b/2a = ±√(b² - 4ac)/2a

So, x = -b/2a ±√(b² - 4ac)/2a

taking the L.C.M of the right hand side, we have

x = [-b ±√(b² - 4ac)]/2a

Answer:

x= 24 and y = 6

Step-by-step explanation:

I think that the right answer

Approximately 48 subjects are needed to estimate the mean number of books read the previous year within six books with 90% confidence.

To estimate the mean number of books read the previous year within a certain margin of error, we need to determine the sample size required. In this case, we want to estimate the mean with a 90% confidence level and a margin of error of ±6 books.

The formula to calculate the required sample size is given by:

Since the standard deviation is unknown, we can use the initial survey result, s = 13.6 books, as an estimate for σ. However, this may result in a larger sample size than necessary.

Referring to the critical values table, we find the z-value corresponding to a 90% confidence level is approximately 1.645. Plugging in the values into the formula:

Since the sample size must be a whole number, we round up to the nearest subject. Therefore, approximately 48 subjects are needed to estimate the mean number of books read the previous year within six books with 90% confidence.

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Answer:

Brand A

Step-by-step explanation:

The volume (V) of a cone is calculated as

V = [tex]\frac{1}{3}[/tex]πr²h ( r is the radius and h the height )

Brand A

V = [tex]\frac{1}{3}[/tex]π × 6² × 15 = [tex]\frac{1}{3}[/tex]π × 36 × 15 = π × 12 × 15 = 180π in³

Brand B

V = [tex]\frac{1}{3}[/tex]π × 5² × 18 = π × 25 × 6 = 150π in³

Brand A have the largest volume

9514 1404 393

Answer:

  9

Step-by-step explanation:

There are 9 such numbers:

  1040, 2080, 3120, 4160, 5200, 6240, 7280, 8320, 9360

_____

For each ABCD, where BCD = x, we want ...

  26x = 1000A +x

  25x = 1000A

  x = 40A

The digit A ranges from 1 to 9 for a 4-digit number. That means there are 9 such numbers. For A=1, for example, x = 40·1 = 40, so the number ABCD is 1040. 26·BCD = 26·040 = 1040 as required.

Answer:

9 is correct but if you are here from caribou math it is 7

Step-by-step explanation:

don't dislike what they said because it is the right formula. 25x = 1000A

you get 1040 2080 3120 4160 5200 6240 7280 8320 9360. But since caribou asks for bcd, b > 0 because its a 3 digit number. from that we can eliminate 1040 and 2080 getting 7

(a) If you measure a wound to be 2.5 inches long, the corresponding length in millimeters is 63.5 mm.

(b) If you measure the depth of a wound to be 0.25 inches, the corresponding length in millimeters is 6.35 mm.

If you measure a wound to be 2.5 inches long, the corresponding length in millimeters is calculated as follows;

1 in = 25.4 mm

2.5 in = ?

? = 2.5 x 25.4 mm

? = 63.5 mm

If you measure the depth of a wound to be 0.25 inches, the corresponding length in millimeters is calculated as follows;

1 in = 25.4 mm

0.25 in = ?

? = 0.25 x 25.4 mm

? = 6.35 mm

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Answer:

19)

20)

21)

22)

23)

24)

Answer:

x = 4

Step-by-step explanation:

Given

[tex]\frac{x-2}{4}[/tex] = [tex]\frac{3x-7}{10}[/tex] ( cross- multiply )

4(3x - 7) = 10(x - 2) ← distribute parenthesis on both sides )

12x - 28 = 10x - 20 ( subtract 10x from both sides )

2x - 28 = - 20 ( add 28 to both sides )

2x = 8 ( divide both sides by 2 )

x = 4

Answer:

Steps:

SA = 2LW + 2WH + 2LH

SA = 2(9×2) + 2(2×11/2) + 2(9×11/2)

SA = 2×18 + 2×22/2 + 2×99/2

SA = 36 + 22 + 99

SA = 157 in²

In order to test if we have adopted the wrong functional forms of independent variables in a regression model Y = α + βX + u, we can use diagnostic plots of the residuals.

Residuals are the differences between the actual values of the dependent variable and the predicted values of the dependent variable. We can plot the residuals against the independent variables to check if there is any functional form that has not been captured by the model, which would indicate that the model has adopted the wrong functional form of independent variables.

If there is no pattern in the residuals when plotted against the independent variables, then it can be concluded that the model has captured the correct functional form of the independent variables. However, if there is a pattern in the residuals, it would indicate that there is some functional form that has not been captured by the model, and we would need to explore different functional forms of the independent variables to see which one fits the data better. This can be done by using different functional forms of the independent variables, such as polynomial, logarithmic, exponential, etc., and comparing the results using various statistical tests.

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If the residuals are normally distributed, then it suggests that the functional form of the independent variable is correct. If they are not, then it suggests that the functional form of the independent variable is incorrect.Overall, it is important to test for the functional forms of independent variables to ensure that the results of the regression model are unbiased and accurate.

In a regression model, it is important to make sure that the functional forms of the independent variables are correct. If they are not, the results of the model may be biased and incorrect. There are several ways to test if the functional forms are correct or not. Below are some of the methods:Plotting the residuals against the independent variable: If the functional form of the independent variable is correct, then the residuals should be randomly distributed around zero, without showing any patterns. If there are patterns in the residuals, then it suggests that the functional form is incorrect. Testing for linearity: One way to test for linearity is by including the square or cubic terms of the independent variable in the model and testing their significance. If the squared or cubic term is significant, then it suggests that the functional form of the independent variable is incorrect. Testing for additivity: One way to test for additivity is by including interaction terms between the independent variables and testing their significance. If the interaction term is significant, then it suggests that the functional form of the independent variable is incorrect. Testing for normality: One way to test for normality is by examining the normal probability plot of the residuals.

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