write the equation of the line passing through the point (-2, 3) with a y-intercept of 6 in slope-intercept form.

For a researcher's sample of cigarette smoker with average 31 cigarettes a day, as t( critical value) > 0.05, so Null hypothesis can't be rejected and it concludes that the true mean number of cigarettes smoked per day is greater than 31, α=0.05.

We have a researcher who see that a cigarette smoker smokes on average 31 cigarettes a day. So, population or true mean = 31

Now, a sample of smokers is considered with Sample size, n = 10

Mean number of cigarettes they smoked per day = 28

Standard deviations = 2.7

level of significance = 0.05

We have to check the claim of researcher is true. Consider null and alternative hypothesis as right tailed, [tex]H_ 0 : \mu = 31[/tex]

[tex]H_ a : \mu > 31[/tex]

Using t- test for test statistic value :

[tex]t= \frac{\bar X -\mu}{ \frac{\sigma }{\sqrt{n}}}[/tex]

Substitute all known values,

[tex]t= \frac{ 28 - 31}{ \frac{ 2.7 }{\sqrt{10} }}

[/tex]

[tex]= \frac{ - 3}{ \frac{ 2.7 }{\sqrt{10} }}[/tex]

= - 3.51364184463

degree of freedom, df = n - 1 = 9

From the t distribution table, the critical value for [tex]d_f = 9 \: and \: \alpha = 0.05[/tex] is equals to 1.833. Since our computed t( critical) = 1.833 > 0.05, is not in the rejection region, we do not reject the null hypothesis. Hence, There is not enough evidence to support claim.

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For a researcher's sample of cigarette smoker with average 31 cigarettes a day, as t( critical value) > 0.05, so Null hypothesis can't be rejected and it concludes that the true mean number of cigarettes smoked per day is greater than 31, α=0.05.

We have a researcher who see that a cigarette smoker smokes on average 31 cigarettes a day. So, population or true mean = 31

Now, a sample of smokers is considered with Sample size, n = 10

Mean number of cigarettes they smoked per day = 28

Standard deviations = 2.7

level of significance = 0.05

We have to check the claim of researcher is true. Consider null and alternative hypothesis as right tailed,

Using t- test for test statistic value :

Substitute all known values,

= - 3.51364184463

degree of freedom, df = n - 1 = 9

From the t distribution table, the critical value for  is equals to 1.833. Since our computed t( critical) = 1.833 > 0.05, is not in the rejection region, we do not reject the null hypothesis. Hence, There is not enough evidence to support claim.

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The length of BD is 8.

We can use the property that medians of a triangle divide each other in a 2:1 ratio.

Let BD be x. Then, using this property, we can write:

CE = 2ED

FA= 2FD

BE = 2 x ED

Since EB = 12, we can substitute 12 for EB and solve for ED:

12 = 2 x DE

DE = 6

Now, the length of DB is

= 12/3 + 12/3

= 4 + 4

= 8

Therefore, the length of DB is 8.

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Answer:

reflectional symmetry

Step-by-step explanation:

Answer:

  r√2

Step-by-step explanation:

You want to know the distance from the center of a marble of radius r to the corner of an L-shaped track in which it rolls.

The center of the marble can only come within r of the track edges, so the distance to the corner will be the hypotenuse of a right triangle with legs r. That distance is r√2.

The center of the marble is r√2 from the corner of the track.

__

Additional comment

You can see in the second attachment that the distance to the corner of the track will depend on where the marble is rolling in the track. It might only be r away from the corner.

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The probability that you and your friend both have the same two numbers is approximately 0.4823, or about 48.23%.

If you and your friend each roll two dice, there are two possible cases:

You both roll doubles (i.e., both dice show the same number).

You both roll non-doubles (i.e., the two dice show different numbers).

Let's calculate the probability of each case separately:

The probability of rolling doubles on one die is 1/6, since there are six possible outcomes (1, 2, 3, 4, 5, or 6) and only one of them will result in doubles. The probability of rolling doubles on both dice is the product of the probabilities of rolling doubles on each die, which is (1/6) * (1/6) = 1/36. Therefore, the probability that you and your friend both roll doubles is (1/36) * (1/36) = 1/1296.

The probability of rolling non-doubles on one die is 5/6, since there are five possible outcomes (2, 3, 4, 5, or 6) that will result in non-doubles, out of a total of six possible outcomes. The probability of rolling non-doubles on both dice is the product of the probabilities of rolling non-doubles on each die, which is (5/6) * (5/6) = 25/36. Therefore, the probability that you and your friend both roll non-doubles is (25/36) * (25/36) = 625/1296.

Therefore, the overall probability that you and your friend both have the same two numbers is the sum of the probabilities of the two cases:

1/1296 + 625/1296

= 626/1296

= 0.4823 (rounded to four decimal places)

So, the probability that you and your friend both have the same two numbers is approximately 0.4823, or about 48.23%.

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The value of cos⁻¹(−0.53) is approximately equals to  -1.012 radians (rounded to 3 decimal places).

Use the inverse cosine function on a calculator to find the value of cos⁻¹(−0.53),

Evaluate it to at least 3 decimal places, use the following steps,

cos⁻¹(−0.53) = x

⇒cos(x) = −0.53

Use the identity cos²(x) + sin²(x) = 1 to solve for sin(x),

⇒sin²(x) = 1 − cos²(x)

⇒sin²(x) = 1 − (−0.53)²

⇒sin²(x) = 0.7191

⇒ sin(x) ≈ ±0.8479

Both a positive and negative value for sin(x),

since sine is positive in both the first and second quadrants.

To determine which value of sin(x) is correct,

The range of values for the inverse cosine function.

The range of cos⁻¹(x) is [0, π], or [0°, 180°],

⇒ The output of the inverse cosine function is always a non-negative angle in the first or second quadrant.

Since sin(x) is negative in the second quadrant, eliminate the positive value for sin(x).

⇒ sin(x) = −0.8479

Now use the inverse sine function to find x,

⇒sin⁻¹(−0.8479) = x

⇒x ≈  -1.012radians

Therefore, cos⁻¹(−0.53) ≈  -1.012 radians (rounded to 3 decimal places).

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The above question is incomplete, the complete question is:

Use your calculator to evaluate cos⁻¹( − 0. 53 ) to at least 3 decimal places. Give the answer in radians

A z-score of -1.32 indicates that Tim's score on the test is below average, but not extremely unusual or unexpected.

If Tim's calculated z-score for his test score of 72 is -1.32, it means that his score is 1.32 standard deviations below the mean of the distribution.

A z-score represents the number of standard deviations that a data point is away from the mean of the data set.

A negative z-score means that the data point is below the mean, while a positive z-score means that the data point is above the mean.

To calculate Tim's score, we can use the formula:

z = (x - μ) / σ

where:

z = the z-score

x = the test score

μ = the mean of the distribution

σ = the standard deviation of the distribution

Substituting the given values, we get:

-1.32 = (72 - μ) / σ

To solve for μ, we need to rearrange the equation as:

μ = 72 - (-1.32) × σ

This means that if Tim's z-score is -1.32 and his test score is 72, then the mean score.

The distribution is 1.32 standard deviations above his score.

The mean score using the standard deviation of the distribution, but we would need additional information such as the standard deviation value.

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The equivalent expression of 18 + 30 using distributive property is 6(3) + 6(5)

The distributive property states that for any numbers a, b, and c, a multiplied by (b+c) equals a multiplied by b plus a multiplied by c.

a(b + c) = a(b) + a(c)

The prime factor of 18 + 30 is written as;

18 + 30 = 2 x 3 x 3 + 2 x 3 x 5

18 + 30 = 2 x 3 x (3 + 5)

Simplifying the expression inside the parentheses gives:

2 x 3 x (3 + 5) = 6 (3 + 5)

applying distributive property we will have;

6 (3 + 5) = 6(3) + 6(5)

Thus, the final expression is; 18 + 30 = 6(3) + 6(5)

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The correct option is D, we can simplify the expression as:

[tex]\sqrt{125p^2} = 5p\sqrt{5}[/tex]

Remember two things, the square root can be distributed under the product, and it is the inverse of the square exponent.

Then we can rewrite our expression as follows:

[tex]\sqrt{125p^2} = \sqrt{125}*\sqrt{p^2}[/tex]

Now we can simplify both of the square roots to get:

[tex]\sqrt{125}*\sqrt{p^2} = p*\sqrt{125} = p*\sqrt{5*25} = p*\sqrt{5} *\sqrt{25} \\\\= 5p\sqrt{5}[/tex]

Thus, we can see that the correct option is D.

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Based on the given side lengths of 3cm, 7cm, and 7.4cm, the triangle is a(n) scalene triangle. In a scalene triangle, all sides have different lengths.

Triangles are described in terms of their sides and angles in geometry. A closed planar three-sided polygon shape with three sides and three angles is known as a triangle. The lengths of the sides of a scalene triangle vary. They are not equal, and the angles have three measurements. However, it still has a 180° angle sum, just like all triangles.

A scalene triangle is a triangle with three different side lengths and three different angle measurements. The total of all internal angles, however, is always equal to 180 degrees. As a result, it satisfies the triangle's condition of angle sum.

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It should be noted that the values of x and y in the trapezium will be

x=118

y= 35

A trapezoid, also known as a trapezium, is a closed, flat object with four straight sides and one pair of parallel sides. A trapezium's parallel sides are known as the bases, while its non-parallel sides are known as the legs. A trapezium might have parallel legs as well.  A trapezium is a quadrilateral with one parallel pair of opposite sides.

Based on the information, x will be:

= 180-62

= 118

y will be:

= 180-145=35

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The responses that must be included are the population is all high school students, the sample contains freshmen, sophomores, juniors, and seniors, and the sample is representative of students in the entire high school.

Hence, options A, B, and D are correct.

To ensure that a sample is representative of the population, it must be selected in a way that accurately reflects the characteristics of the population. In this case, the population is all high school students in the town, and the possible sample includes an equal number of students from each grade level - freshman, sophomores, juniors, and seniors.

This is a good approach to ensure that the sample is representative of the entire population, as it captures the diversity of the population by including students from each grade level. Additionally, by having an equal number of students from each grade level, the sample is not biased towards any particular group.

It is also important to ensure that the sample is not too small, as a small sample size may not accurately reflect the characteristics of the entire population. Finally, if the sample is truly representative of the entire high school, any conclusions drawn from the sample should be applicable to the population as a whole.

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According to the given inductive definition of Ackermann's function, we can find the values of the function as follows:

A(2,1) = A(1, A(2,0)) = A(1, 1) = A(0, A(1,0)) = A(0, 2) = 2

A(1,2) = A(0, A(1,1)) = A(0, A(0, A(1,0))) = A(0, A(0, 2)) = A(0, 4) = 6

A(1,0) = A(0, A(1,-1)) = A(0, A(0, 0)) = A(0, 1) = 2^1 = 2

A(0,1) = 2^1 = 2

A(3,0) = A(2, A(3,-1)) = A(2, A(2, A(3,-2))) = A(2, A(2, A(2, A(3,-3)))) = A(2, A(2, A(2, 1))) = A(2, A(2, 2)) = A(2, 2^2) = A(2, 4) = 2^4 = 16

A(3,3) = A(2, A(3,2)) = A(2, A(2, A(3,1))) = A(2, A(2, A(2, A(3,0)))) = A(2, A(2, A(2, 1))) = A(2, A(2, 2)) = A(2, 2^2) = A(2, 4) = 2^4 = 16

Therefore, the values of Ackermann's function are:

A(2,1) = 2

A(1,2) = 6

A(1,0) = 2

A(0,1) = 2

A(3,0) = 16

A(3,3) = 16
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Answer:

B

Step-by-step explanation:

The quadratic formula is used to solve quadratic equations in the form ax^2 + bx + c = 0.

Looking at the given options, we can see that option B can be written in this form as 3x^2 - 8x - 14 = 0. Therefore, the equation that could be solved using the quadratic formula is option B.

The weight of a small Starbucks coffee that is heavier than 480 grams corresponds to a probability of 0.0062.

To find the weight that corresponds to each event, we'll need to use the normal distribution formula:

Z = (X - μ) / σ where Z is the standard score (or z-score), X is the observed value, μ is the mean, and σ is the standard deviation.

We can use this formula to convert the weight of a small Starbucks coffee into a z-score, and then use a standard normal distribution table (such as Appendix C) to find the corresponding probability (or vice versa).

Here are the specific events and their corresponding weights:

1. The weight of a small Starbucks coffee that is lighter than 400 grams. First, we need to convert the weight of 400 grams into a z-score:

Z = (400 - 420) / 24 = -0.83 Using Appendix C or Excel.

we can find that the probability of a z-score being less than -0.83 is 0.2033.

Therefore, the weight of a small Starbucks coffee that is lighter than 400 grams corresponds to a probability of 0.2033.

2. The weight of a small Starbucks coffee that is between 420 and 450 grams. To find the z-scores corresponding to these weights, we need to use the formula twice: For 420 grams: Z = (420 - 420) / 24 = 0 For 450 grams: Z = (450 - 420) / 24 = 1.25 Using Appendix C or Excel, we can find that the probability of a z-score being between 0 and 1.25 is 0.3944.

Therefore, the weight of a small Starbucks coffee that is between 420 and 450 grams corresponds to a probability of 0.3944.

3. The weight of a small Starbucks coffee that is heavier than 480 grams. Again, we need to convert the weight of 480 grams into a z-score:

Z = (480 - 420) / 24 = 2.50 Using Appendix C or Excel, we can find that the probability of a z-score being greater than 2.50 is 0.0062.

Therefore, the weight of a small Starbucks coffee that is heavier than 480 grams corresponds to a probability of 0.0062.

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The function that will return the value of x, rounded to the nearest whole number is option (c) round(x)

This function rounds the value of x to the nearest integer. For example, if x = 3.4, round(x) will return 3, and if x = 3.6, round(x) will return 4.

Option (a) abs(x) returns the absolute value of x, which means it returns the positive value of x regardless of its sign. For example, if x = -3, abs(x) will return 3.

Option (b) fmod(x) returns the remainder of x divided by another number, so it does not round x to the nearest whole number.

Option (d) whole(x) is not a standard math function, so it is unclear what it would do.

Option (e) sqrt(x) returns the square root of x, so it does not round x to the nearest whole number.

Therefore, the correct answer to this question is option (c) round(x).

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The 15 times the probability of pulling socks of different colors every day is 6/5 or 1.2.

What is probability?

Probability is a measure of the likelihood or chance of an event occurring. It is a number between 0 and 1, with 0 representing an impossible event and 1 representing a certain event. The probability of an event is calculated by dividing the number of ways the event can occur by the total number of possible outcomes.

The total number of socks in the drawer is 2 + 2 + 2 = 6.

On the first day, any sock can be chosen, so the probability of selecting a sock of a particular color is 2/6 = 1/3.

On the second day, there are only 5 socks left, so the probability of selecting a sock of a different color from the first day is 4/5.

On the third day, there are only 4 socks left, so the probability of selecting a sock of a different color from the first two days is 2/4 = 1/2.

To find the probability of pulling socks of different colors on all three days, we need to multiply the probabilities of each day:

P(different colors for all 3 days) = (1/3) × (4/5) × (1/2)

P(different colors for all 3 days) = 2/25

To get the 15 times probability, we multiply by 15:

15 × 2/25 = 6/5

Therefore, the answer is 6/5 or 1.2.

Hence, the 15 times the probability of pulling socks of different colors every day is 6/5 or 1.2.

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If cholesterol level were changed to being measured in grams instead of milligrams, the correlation between fat content and cholesterol level would not be affected.

This is because correlation is a measure of the strength and direction of the linear relationship between two variables, and converting the units of measurement does not change the underlying relationship between the variables. So, the correlation coefficient of 0.75 would remain the same whether cholesterol level is measured in milligrams or grams.

The correlation between fat content and cholesterol level for the 20 different brands of American cheese slices is 0.75. If you change the measurement of cholesterol level from milligrams to grams (1 gram = 1000 milligrams), it will not affect the correlation. The correlation coefficient will remain 0.75, as it is unit-less and only represents the strength and direction of the relationship between the two variables.

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Answer:

9/10 or 0.9

Step-by-step explanation:

Slope of a line passing through two points (x1, y1) and (x2, y2) is given by
Slope m = rise/run

where
rise = y2 - y1
run = x2 - x1

Given points (- 6, - 5) and (4, 4),

rise = 4 - (-5) = 4 + 5 = 9

run = 4 - ( - 6) = 4 + 6 = 10

Slope = rise/run = 9/10 or 0.9

The resulting interval will contain 95% of all sample means. In conclusion, the interval value is 1.96.

When applying the Central Limit Theorem (CLT) to define an interval within which we expect 95% of all sample means to fall, we would use a z-value of 1.96. This is because 95% of the area under a normal distribution curve falls within 1.96 standard deviations of the mean. Therefore, using a z-value of 1.96 will give us an interval that contains 95% of all sample means.

Identify the desired confidence level. In this case, it is 95%.

Find the corresponding z-value for the desired confidence level. For a 95% confidence level, the z-value is 1.96.

Use the z-value and the standard deviation of the sample means to calculate the interval. The formula for the interval is:

mean ± (z-value)(standard deviation)

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The expression that can be added to both sides of the given quadratic equation to change it to a perfect square trinomial is [tex]\frac{b^2}{4a^2}[/tex] .

The standard form of perfect square trinomial is given as:

[tex]ax^2 + bx + c[/tex]

here,

a = coefficient of x² .

b = coefficient of x.

c = constant .

Given the quadratic equation:

[tex]x^2 + \dfrac{b}{a}x\ +\ ?= -\dfrac{c}{a}\ +\ ?[/tex]

The above equation is needed to be changed to a perfect square trinomial.

To change the quadratic equation into the perfect square, the squared of half the value of the coefficient of degree one variable can be added to both sides of the equation.

Therefore, the term to be that is needed to be added to the given quadratic equation is [tex]\frac{b^2}{4a^2}[/tex] .

Now, the quadratic equation can be written as:

[tex]x^{2} + \frac{b}{a} x + \frac{ b^{2}}{4a^{2}} = \frac{-c}{a} + \frac{ b^{2}}{4a^{2}}[/tex]

Therefore, [tex]\dfrac{b^2}{4a^2}[/tex] should be added to both sides to convert it into the perfect polynomial.

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The given question is incomplete. Probably the complete question is:

When deriving the quadratic formula by completing the square what expression can be added to both sides of the given equation to create a perfect square trinomial?

[tex]x^2 + \dfrac{b}{a}x\ +\ ?= -\dfrac{c}{a}\ +\ ?[/tex]

If 3 men build a garage in 8 days, then 4 men will be needed to build the garage in 6 days.

The amount of work required to build the garage is constant, regardless of the number of days or workers involved. We assume that each worker does the same amount of work in a day, then we use the following formula;

⇒ work = rate × time,

where rate is = amount of work done by one worker in a day, and time is = number of days worked,

Let the number of workers needed be "x". If 3-workers can build the garage in 8 days, then we have:

⇒ work = 3 workers × 8 days = 24 worker-days,

If "x" workers are needed to build the garage in 6 days, then we have:

⇒ work = (x workers) × (6 days),

Since the amount of work is same in both cases, we equate the two expressions;

⇒ 3 workers × 8 days = x workers × 6 days

⇒ x = (3 workers × 8 days)/6 days = 4 workers;

Therefore, 4 workers are needed to build the garage in 6 days.

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Answer: 121/209= 57.89% rounded

Step-by-step explanation:

total golf balls are 209

add red +  yellow balls = 121

121/209= 57.89% rounded

To complete the square for the equation x² + 7x = 4, we need to add (7/2)² or (7/2)² + 4 to both sides. (option d)

To start, let's review what it means to complete the square. Suppose we have an equation of the form x² + bx = c, where b and c are constants. Our goal is to find a value d such that the equation can be rewritten in the form (x + e)² = f, where e and f are also constants. To do this, we add and subtract the quantity (b/2)² on the left-hand side of the equation:

x² + bx + (b/2)² - (b/2)² = c

We can simplify the left-hand side by factoring the first three terms as a perfect square trinomial:

(x + b/2)² = c + (b/2)²

x² + 7x - 4 = 0

Next, we add and subtract the quantity (7/2)² on the left-hand side:

x² + 7x + (7/2)² - (7/2)² - 4 = 0

Again, we can simplify the left-hand side by factoring the first three terms as a perfect square trinomial:

(x + 7/2)² - (7/2)² - 4 = 0

We can simplify further by adding (7/2)² and 4 to both sides:

(x + 7/2)² = 33/4

Now we have completed the square, and the equation is in the form (x + e)² = f, where e = 7/2 and f = 33/4. To solve for x, we take the square root of both sides:

x + 7/2 = ±√(33/4)

Finally, we can solve for x by subtracting 7/2 from both sides:

x = -7/2 ± √(33)/2

Option (d), (7/2)², is the correct answer.

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The answer is option A. increasing the sample size.

The central limit theorem (CLT) is a statistical theory that explains the behavior of sample means when drawn from a population with any distribution, as long as the sample size is large enough. The CLT states that as the sample size increases, the sampling distribution of the means approaches a normal distribution, regardless of the shape of the original population distribution.

One implication of the CLT is that increasing the sample size makes the sampling distribution more precise and reliable, as the standard error of the mean decreases with larger samples. However, the CLT does not necessarily imply that increasing the sample size decreases the dispersion (or variability) of the sampling distribution itself.

The dispersion of the sampling distribution is determined by the variability of the original population and the sample size, but it does not change with sample size alone. For example, if the original population has a large standard deviation, the sampling distribution of the means will also have a large standard deviation, even with a large sample size. However, as the sample size increases, the means will be more tightly clustered around the population mean, which means that the precision of our estimate of the population mean increases.

Therefore, the answer is option A. increasing the sample size.

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The reasonable way to test this one is to identify the validity of the hypothesis can be tested.

The hypothesis suggests that when an electric current passes through a wire, it generates a magnetic field. If this magnetic field is strong enough, it could magnetize a non-magnetic nail that is placed nearby. To test this hypothesis, an experiment can be conducted as follows:

A non-magnetic nail, a battery, a wire, and a switch.

Connect the wire to the battery and switch in series. The other end of the wire should be wrapped around the nail multiple times. Once the apparatus is set up, turn on the switch to pass an electric current through the wire.

Before running the current through the wire, test the nail for its magnetic properties by holding it close to some iron filings or other small magnetic objects. If it does not attract any of these objects, then it is non-magnetic.

Turn on the switch and run the electric current through the wire wrapped around the nail for a few minutes.

After running the current through the wire, test the nail again for its magnetic properties. Hold it close to the iron filings or other small magnetic objects and observe if it attracts them.

Compare the results obtained before and after running the current through the wire. If the nail exhibits magnetic properties after running the current, then the hypothesis that passing an electric current through a wire can magnetize a non-magnetic nail can be considered valid.

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Answer:

The quadratic equation with roots -3 and -6 and leading coefficient 2 is:

2x2 - 8x - 12 = 0

To derive this, we use the quadratic formula:

ax2 + bx + c = 0

With:

a = 2 (leading coefficient)

b = -4 (calculated from roots: b = -2(root1 + root2) = -2(-3 - 6) = -4)

c = -12 (calculated from discriminant: c = b2/4a = -42/8 = -12)

So the full equation is:

2x2 - 4x - 12 = 0

Which simplifies to:

2x2 - 8x - 12 = 0

This has the roots -3 and -6 as requested, with a leading coefficient of 2.

Step-by-step explanation:

The proportion of infants with birth weights under 95 oz is about 0.159oz

68−95−99.7 Rule, also known as the empirical rule conveys that for a normal distribution, mostly all of the data will fall within three (68%,95%,99.7%) standard deviations of the mean. Empirical rule is an approximate so it is not recommended to use unless a question specifically asks you to solve using it.

Let X be the Birthweights

X ~ N( = 110, [tex]\sigma^2 = 15^2[/tex])

The probability of X is less than 95 is,

P(X < 95) = [tex]P(\frac{X-\mu}{\sigma} < \frac{95-\mu}{\sigma} )[/tex]

               [tex]=P(Z < \frac{95-110}{15} )[/tex]

              [tex]=P(Z < \frac{-15}{15} )[/tex]

              = P (Z < -1)

P(X < 95)    = 0.159 (using the normal table)

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[tex]ANSWER \\ (( \frac{1}{3} ) {}^{4} ) {}^{ \frac{1}{2} } \\ [/tex]

simplify the expression

[tex]( \frac{1}{3} ) {}^{ \frac{4}{1} \times } {}^{ \frac{1}{2} } \\ ( \frac{1}{3} ) {}^{ \frac{4}{2} } \\ ( \frac{1}{3} ) {}^{2} \\ = \frac{1}{9} [/tex]

~hope it helps~

have a nice day (✿^‿^)

First, we need to calculate what's inside the parentheses of the exponent.

1/3^4 = 1/81

Now, we can simplify the exponent:

(1/81)^1/2 = 1/9

Therefore, (1/3^4)^1/2 = 1/9. <⁠(⁠￣⁠︶⁠￣⁠)⁠>

The standard deviation of the resulting data set would be 14.

If each value in a data set is multiplied by a constant, the standard deviation is also multiplied by that constant.

Therefore, if each value in a data set with a standard deviation of 8 is multiplied by 1.75, the standard deviation of the resulting data set would be:

New standard deviation = 8 x 1.75 = 14

Standard deviation is a measure of the amount of variation or dispersion in a set of data. It is calculated by taking the square root of the variance, which is the average of the squared differences from the mean.

Multiplying each value in a data set by a constant will stretch or compress the data set, but it will not change the shape of the distribution. So, if the original data set had a normal distribution (i.e., a bell-shaped curve), the resulting data set will also have a normal distribution.

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