A grain silo has a cylindrical shape. Its diameter is 14 ft, and its height is 29 ft. What is the volume of the silo?

The area of the tile which is trapezoid is  70 cm².

A trapezoid is a four-sided geometric shape with one pair of parallel sides.

The two non-parallel sides are usually referred to as the "legs" and the other two sides are the "bases".

A trapezoid can be either isosceles or non-isosceles depending on the angles of the legs.

A trapezoid can also be equilateral if all four sides have equal lengths.

The formula for the area of a trapezoid is (base 1 + base 2) x height/2.

In this case, the base 1 is 3 cm and the base 2 is 6 cm and the height is 4 cm.

Plugging these values into the equation

we get (3 cm + 6 cm) x 4 cm/2 = 70 cm².

Therefore, the area of the tile shown is 70 cm².

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The two numbers whose difference is 132 and whose product is a minimum are 66 and 198.

Let x and y be the two numbers. We are given that their difference is 132, so we can write:

y - x = 132

We want to minimize their product, which is given by:

P = xy

We can solve for one of the variables in terms of the other using the first equation:

y = x + 132

Substituting this expression for y in the equation for P, we get:

P = x(x + 132)

Expanding this expression and simplifying, we get:

P = x^2 + 132x

To find the minimum value of P, we can take the derivative of P with respect to x and set it equal to zero:

dP/dx = 2x + 132 = 0

Solving for x, we get:

x = -66

Since we want the two numbers to be positive, we take the absolute value of x and add 132 to get y:

x = 66

y = x + 132 = 198

Therefore, the two numbers whose difference is 132 and whose product is a minimum are 66 and 198.

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The expressions are simplified to;

1. x = 118

4. 88

5. 123

Percentage can simply be defined as the fraction between a given value and hundred.

It is represented with the symbol, '%'

Also note that algebraic expressions are expressions with factors, variables, constants, terms and coefficients.

From the information given, we have that;

1. x increased by 25%

x + 25%, then decreased by 15%

x + 2. 5 - 1.5 = 119

collect the like terms

x = 118

4. x + 25% + 15% = 92

x + 2.5 + 1.5 = 92

collect like terms

x = 88

5. x - 35% - 20% = 117

x - 3.5 - 2.5 = 117

collect the like terms

x = 117 + 6

x = 123

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Using a chi-square table or calculator, we find that this probability is approximately 0.025.

To answer this question, we need to use the chi-square distribution, which is used to find probabilities for sample variances.

a) For a random sample of size n = 16, we use the formula:
Chi-Square = (n-1) * sample variance / population variance
Chi-Square = 15 * 7.442 / 5
Chi-Square = 22.326

The probability of a sample variance being greater than or equal to 7.442 is the same as the probability of a chi-square value of 22.326 or more. Using a chi-square table or calculator, we find that this probability is approximately 0.05.

The probability of a sample variance being less than or equal to 2.56 is the same as the probability of a chi-square value of 7.692 or less. Using a chi-square table or calculator, we find that this probability is approximately 0.025.

b) For a random sample of size n = 30, we use the formula:
Chi-Square = (n-1) * sample variance / population variance
Chi-Square = 29 * 7.442 / 5
Chi-Square = 41.256

The probability of a sample variance being greater than or equal to 7.442 is the same as the probability of a chi-square value of 41.256 or more. Using a chi-square table or calculator, we find that this probability is approximately 0.005.

The probability of a sample variance being less than or equal to 2.56 is the same as the probability of a chi-square value of 13.767 or less. Using a chi-square table or calculator, we find that this probability is approximately 0.025.

c) Comparing the probabilities in parts (a) and (b) for the sample variance being greater than or equal to 7.442, we see that the probability decreases with increased sample size. This is because as the sample size increases, the sample variance is more likely to be closer to the population variance, resulting in a smaller chi-square value.

d) Comparing the probabilities in parts (a) and (b) for the sample variance being less than or equal to 2.56, we see that the probability remains the same regardless of sample size. This is because a smaller sample variance is always more likely than a larger one, regardless of the sample size.

In a normal population with a known mean (µ) of 75 and variance (σ²) of 5, we want to find the approximate probability that the sample variance is greater than or equal to 7.442 and less than or equal to 2.56 for random samples of size n=16 and n=30.

a) For a random sample of size n=16, the chi-square distribution with degrees of freedom (df) = n-1 = 15 is used to calculate the probability.

b) For a random sample of size n=30, the chi-square distribution with degrees of freedom (df) = n-1 = 29 is used to calculate the probability.

c) Comparing the answers to parts (a) and (b) for the approximate probability that the sample variance is greater than or equal to 7.44, it is observed that the tail probability may either increase or decrease with an increased sample size, depending on the underlying distribution of the population.

d) Comparing the answers to parts (a) and (b) for the approximate probability that the sample variance is less than or equal to 2.56, it is observed that the tail probability may either increase or decrease with an increased sample size, again depending on the underlying distribution of the population.

The actual probabilities will depend on the specific calculations made using the chi-square distribution and the given parameters.

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The two statements that also describe features of a binomial experiment are: "The random variable counts the number of successes in a fixed number of trials" and "The probability of success stays the same for each trial."

Binomial experiments also have independent trials, which means that the outcome of one trial does not affect the outcome of another trial. Additionally, binomial experiments can only have two possible outcomes - success or failure - for each trial. The distribution of a binomial experiment is not always asymmetric in shape, as it can be symmetrical or skewed depending on the parameters of the experiment.

Finally, subsequent trials in a binomial experiment are not conditional probabilities, as each trial is independent and the probability of success remains constant.
Based on your question and the terms provided, the two statements that describe features of a binomial experiment are:

1. The random variable counts the number of successes in a fixed number of trials.
2. The probability of success stays the same for each trial.

A binomial experiment has independent trials with a constant probability of success, and it focuses on counting the number of successes within a specific number of trials.

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By definint a linear relation, we can see that after 120 minutes of driving the distance will be 180 miles.

We know that the initial distance is 300 miles, so we can define the point of the form (time, distance) as (0, 300)

The second point that we have is 30 minutes and 270 miles, (30,270)

The relation between tiime and distance is linear, then the rate of change is:

R = (270 - 300)/(30 - 0) = -1

Then the distance as a function of time can be written as:

d = -t + 300

With d the distance in miles and t the time in minutes.

The time such that the distance left is 180 miles is given by:

180 = -t + 300

t = 300 - 180 = 120

t = 120

After 120 minutes the distance left is 180 miles.

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Answer: I cannot solve this because I do not have the figure

Step-by-step explanation:

The number of seeds Kerri plants is a multiple of 8

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

Kerry plants some sunflower seeds in equal rows of 8 seeds each.

Represent the number of rows with x

So, the number of seeds is

Seed = 8x

This means that the number of seeds Kerri plants is a multiple of 8

And examples are 8, 16, 24, 32 and so on

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True, a box can be held in position by a cable along a frictionless incline.

When the tension force in the cable is equal to the component of the gravitational force rate acting parallel to the incline, the box will remain in a stationary position.

force which prevents one solid item from rolling or slipping over another. Although frictional forces can be advantageous, such as the traction required to walk without slipping, they can provide a significant amount of resistance to motion.

What are the 4 different forms of friction?

It opposes the sliding motion of both layers of fluid and solid matter. Friction comes in four flavors: flowing, rolling, sliding, and static.

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For options b and d, a proof by contraposition is a better approach than a direct approach.

The proofs by contraposition and direct approach are both valid methods for proving statements. However, for some statements, one approach may be more efficient or straightforward than the other.

For the given statements, a proof by contraposition would be a better approach for (a) and (d).

(a) If n is odd, then n^3 + 1 is even. To prove this statement directly, we would need to show that for every odd n, n^3 + 1 is even. This can be quite challenging, as there are infinitely many odd numbers to consider. However, if we take the contrapositive of the statement, we get: If n^3 + 1 is odd, then n is even. This is much easier to prove directly, as there are only two possibilities for the parity of n^3 + 1.

(d) If 3n + 2 is odd, then n is odd. To prove this statement directly, we would need to show that for every even n, 3n + 2 is even. Again, this can be challenging to do for all even n. However, if we take the contrapositive of the statement, we get: If n is even, then 3n + 2 is even. This is straightforward to prove directly, as we can simply factor out 2 from the expression 3n + 2.

For (b) and (c), a direct approach would be more appropriate.

(b) Prove that if 1/x is irrational, then x is irrational. This statement is already in a direct form, so there is no need to use contraposition.

(c) If a is odd and b is odd, then ab is odd. To prove this statement by contraposition, we would need to show that if ab is even, then either a or b is even. This may be more challenging than simply proving the statement directly, by showing that the product of two odd numbers is odd.

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Answer:

C) 6x + 12

Step-by-step explanation:

3 × 2x = 6x

3 × 4 = 12

Answer:  D

Step-by-step explanation:

A) Incorrect.  The y-intercept is when x=1  for f(x) the y-intercept is (0, -1)

    For g(x) the y-intercept is (0, 1)

B) Incorrect.  There are 2 points that are the same (-1, 0) and (1,0), not 2 points

C) Incorrect.  the min value for f(x) is -1 but there are smaller numbers for g(x)

D) Correct.  The x-intercepts are the same 2 points that intersect discussed in B

Answer:

A) Incorrect.  The y-intercept is when x=1  for f(x) the y-intercept is (0, -1)    For g(x) the y-intercept is (0, 1)B) Incorrect.  There are 2 points that are the same (-1, 0) and (1,0), not 2 pointsC) Incorrect.  the min value for f(x) is -1 but there are smaller numbers for g(x)D) Correct.  The x-intercepts are the same 2 points that intersect discussed in B

Step-by-step explanation:

The value of y in the parallelogram is 37

A parallelogram is a quadrilateral with two pairs of parallel sides.These are some of properties of a parallelogram.

1. The opposite sides of a parallelogram are equal in length,

2. The opposite angles are equal in measure.

3. The sum of adjascent angles is 180°

This means that;

4y - 42+ 2y = 180°

collecting like terms

4y +2y = 180+42

6y = 222

divide both sides by 6

y = 222/6

y = 37

therefore the value of y Is 37

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The pattern of association for the scatter plot is a strong, negative nonlinear association.

We have,

A scatter plot is a type of graph used to display the relationship between two variables. It is also known as a scatter diagram, scatter chart, or scattergram. In a scatter plot, each observation consists of a pair of values, one for each variable, and is represented by a single point on the graph.

Looking at the scatter plot, we can observe that the points do not form a straight line, indicating that there is a nonlinear association between the number of cupcakes and the cost per cupcake.

We can also see that as the number of cupcakes ordered increases, the cost per cupcake generally decreases until it reaches a minimum value, after which it remains relatively constant.

Therefore, the pattern of association for the scatter plot is a strong, negative nonlinear association.

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The p-value is approximately 0.27, which is greater than 0.05. Therefore, we fail to reject the null hypothesis. We do not have sufficient evidence to conclude that the percentage today differs from 73% at a 5% level of significance.

To determine whether it can be concluded that the percentage today differs from 73%, we need to perform a hypothesis test.

Let p be the true proportion of Americans who prefer to purchase an American automobile today. The null hypothesis is that p = 0.73, and the alternative hypothesis is that p is not equal to 0.73.

We can use a normal approximation to the binomial distribution because the sample size is sufficiently large (n = 47) and the success-failure condition is satisfied (at least 10 successes and failures). The test statistic is calculated as:

z = (P - p) / √(p(1-p) / n)

where P is the sample proportion, p is the hypothesized population proportion, and n is the sample size.

Plugging in the values from the problem, we have:

P = 36/47 ≈ 0.766

p = 0.73

n = 47

The calculated value of the test statistic is:

z = (0.766 - 0.73) / √(0.73(1-0.73) / 47) ≈ 1.11

Using a standard normal distribution table or a calculator, we can find the p-value associated with this test statistic. For a two-tailed test with a significance level of 0.05, the critical values are ±1.96. The rejection region is outside of this range.

The p-value is the probability of getting a test statistic at least as extreme as the one observed, assuming the null hypothesis is true. Since the alternative hypothesis is two-sided, we need to double the area in the tail of the normal distribution that corresponds to the observed test statistic.

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The expected value for this game is $0.80.

The expected value for this game is calculated using  the formula below:

Data given:

If you pull a green candy you will have to pay them $1.00 and there is a 0.4 probability that you pull a green candy

If you pull a red candy you will have to pay them $2.00 and there is a 0.6 probability that you pull a red candy.

Expected value = (0.6 * $2.00) + (0.4 * -$1.00)

Expected value  = $1.20 - $0.40

Expected value = $0.80

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The coefficient of determination is a statistical measure that indicates the proportion of variability in the dependent variable that can be explained by the independent variable(s) in a regression model. It is also known as R-squared and is expressed as a fraction between 0 and 1. The closer the value is to 1, the better the fit of the model.

The coefficient of determination can be thought of as the fraction of variability that can be accounted for by the slope of the regression model. The slope is the change in the dependent variable per unit change in the independent variable. In other words, it represents the rate of change in the dependent variable due to a change in the independent variable.

Therefore, a higher coefficient of determination means that a larger proportion of the variability in the dependent variable is explained by the slope of the regression model. This is important because it provides information on the accuracy and usefulness of the model. If the coefficient of determination is low, it may indicate that the model is not a good fit for the data and needs to be revised.
In conclusion, the coefficient of determination is a crucial measure in regression analysis that helps to assess the proportion of variability in the dependent variable that can be explained by the slope of the regression model. It is expressed as a fraction between 0 and 1 and provides important information on the accuracy and usefulness of the model.
In other words, it represents the proportion of the total variability in the dataset that the model is able to explain.

The coefficient of determination ranges from 0 to 1, with values closer to 1 indicating that the regression model is better at explaining the variability in the data. When interpreting R-squared, keep in mind that a higher value doesn't always imply a good model, as it can sometimes be due to overfitting.

To calculate R-squared, you would first fit a regression model to your data. The regression model typically consists of a slope, which represents the rate of change between the independent variable (x-value) and dependent variable (response), and an intercept, which is the point where the regression line crosses the y-axis.

Once the model is fit, you can compute the sum of squares due to regression (SSR) and the total sum of squares (SST). The coefficient of determination is then found by dividing SSR by SST.

R-squared = SSR / SST

By understanding the coefficient of determination, you can evaluate the effectiveness of a regression model in accounting for the variability in the data and make informed decisions based on its performance.

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The difference in the total cost between the two mortgages is $515,645.

After calculation, we arrive at a monthly payment value of $2,762.81.

It should be noted that to obtain an accurate total for a fixed-rate mortgage plan, multiply these payments by 360, which will produce a final result of $993,411.60.

Subtracting the total fixed-rate amount from that of the adjustable-rate ($1,509,056.80), there exists a disparity of roughly $515,645.20.

Difference = $1,509,056.80 - $993,411.60 = $515,645.20.

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a) The probability that the first two you choose are both good is 0.341.

b) The probability that at least one of the first three batteries works is 0.911.

c) The probability that the first four batteries picked all work is 0.071.

d) The probability that you have to pick five batteries to find one that works is 0.011.

a) The probability that the first two you choose are both good.:

P(choosing 2 good batteries) = P(1st battery is good) * P(2nd battery is good given the 1st battery was good)

P(1st battery is good) = 8/14 (since there are 8 good batteries out of 14 total)

P(2nd battery is good given the 1st battery was good) = 7/13

Hence,

P(choosing 2 good batteries) = (8/14) * (7/13)

P(choosing 2 good batteries) = 0.341

b) The probability that at least one of the first three works.

P(at least one of the first three batteries works) = 1 - P(none of the first three batteries work)

P(none of the first three batteries work) = (6/14) * (5/13) * (4/12)

P(none of the first three batteries work) = 0.089

P(at least one of the first three batteries works) = 1 - 0.089

P(at least one of the first three batteries works) = 0.911

c) The probability that the first four you pick all work

P(the first four batteries picked all work) = (8/14) * (7/13) * (6/12) * (5/11)

P(the first four batteries picked all work) = 0.071

d) The probability that you have to pick five batteries to find one that works

P(having to pick five batteries to find one that works) = P(first four batteries are all dead) * P(the fifth battery is good)

P(first four batteries are all dead) = (6/14) * (5/13) * (4/12) * (3/11)

P(first four batteries are all dead) = 0.034

P(the fifth battery is good) = 8/10

Hence,

P(having to pick five batteries to find one that works) = (6/14) * (5/13) * (4/12) * (3/11) * (8/10)

P(having to pick five batteries to find one that works) = 0.011

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The overall probability is (3/4)^4 * 1/4 = 81/1024, or approximately 0.079.

The probability that Nancy will randomly guess the correct answer for any one of the 5 questions is 1/4 (since there are 4 choices for each question). Since Nancy has not studied at all, her guesses for each question are independent events.

Therefore, the probability that the first question she gets right is question number 5 is the probability that she guesses incorrectly for the first 4 questions (which has a probability of (3/4)^4) and then guesses correctly for question number 5 (which has a probability of 1/4).

Therefore, the overall probability is (3/4)^4 * 1/4 = 81/1024, or approximately 0.079.

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The proportion is solved and the number of men , women and children are 600 men, 1080 women, and 1200 children respectively

Given data ,

Let the proportion be represented as A

Now , the value of A is

Ratio of men : women : children = 5 : 9 : 10

And , Men:Women:Children = 5x : 9x : 10x

It is also given that there are 480 more women than men.

Since the ratio of men to women is 5:9, we can set up the equation:

9x - 5x = 480

Simplifying, we get:

4x = 480

Dividing both sides by 4, we get:

x = 120

Now we can substitute the value of x back into the ratio to find the actual number of men, women, and children.

(a) Men = 5x = 5 x 120 = 600

(b) Women = 9x = 9 x 120 = 1080

(c) Children = 10x = 10 x 120 = 1200

Hence , there are 600 men, 1080 women, and 1200 children

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The slant height of the roof is x = 10m

The diagram can be seen in the image at the end, here we want to find x which is the hypotenuse of a triangle whose legs are:

6m and (16/2)m = 8m

So we know the two cathetus and we want to find the hypotenuse, thus, we need to use Pythagorean's theorem, it says that the sum of the squares of the legs is equal to the square of the hypotenuse, then:

x² = (6m)² + (8m)²

x = √(100 m²) = 10m

That is the slant height.

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The correct answer is c.

A 95% confidence interval for μ will exclude the value 1.

When the p-value is 0.07, it means there is a 7% chance of observing a sample mean as extreme as the one obtained if the null hypothesis (μ = 1) is true. This is not considered strong enough evidence to reject the null hypothesis at the usual significance level of 0.05.

However, a confidence interval can provide a range of plausible values for the population mean μ. A 95% confidence interval means that if we were to repeat the experiment many times, 95% of the intervals constructed would contain the true population mean.

Using a standard normal distribution table or calculator, we can find that the critical values for a 95% confidence level are ±1.96. We can then use the formula for a confidence interval:

sample mean ± (critical value) x (standard error)

The standard error, in this case,

is σ/√n, where n is the sample size. Since the sample size is not given in the question, we cannot calculate the exact confidence interval. However, we can say that a 95% confidence interval will have a wider margin of error than a 90% or 92% confidence interval, and a narrower margin of error than a 99% confidence interval.

Therefore, we can conclude that a 95% confidence interval for μ will exclude the value 1.

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Answer:

The answer is D

Step-by-step explanation:

You just find the cubed root of each value (ex. the cubed root of 27 is 3)

To check your answer, give x y and z value (I did x=2 y=3 and z=4)

Then solve both equations (your answer and the original equation)

If it matches you are right

Note that the percentage of the students who plant ot use earthen ware clay and also play to use acrylic paint are 38.4%

Out of 73 students,
28 plan to use acrylic paint

Percentage who plan tot use both earthen ware clay and acrylic is

(28/73  ) x 100 = 34.8%

Thus the percentage of students that meet teh above description is 38.4%

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Full Question:

The freshman classes at mountain view high school are starting a pottery project next month. The art teacher needs to preorder supplies, so she asked each student to choose one type of clay and one type of paint to use for the project . This table summarizes their choices.

What percentage of students who plan to use earthenware clay also plan to use acrylic paint?

The table is :

                                                 Oxide Stain     Glaze   Acrylic Paint     Total

Earthenware clay                  14                        31              28                   73

Stoneware clay                      9                           26                17                  52

Total                                            23                         57                 45               125

Answer:

[tex]a=\dfrac{1}{2},\;\;b=\dfrac{1}{2}[/tex]

Step-by-step explanation:

A function f is continuous at x = a when:

    [tex]\bullet\quad\textsf{$f(a)$\;is\;d\:\!efined.}[/tex]

    [tex]\bullet\quad\textsf{$\displaystyle \lim_{x \to a} f(x)$\;exists.}[/tex]

    [tex]\bullet\quad\displaystyle \lim_{x \to a} f(x) = f(a)[/tex]

To ensure that f(x) is continuous at x = 2 and x = 3, we need to make sure that the limit of f(x) as x approaches 2 from the left is equal to the limit of f(x) as x approaches 2 from the right, and similarly for x = 3.

First, factor the numerator and simplify the rational function:

[tex]f(x)=\dfrac{x^2-4}{x-2}=\dfrac{(x+2)(x-2)}{x-2}=x+2[/tex]

As x approaches 2 from the left, x < 2. Therefore, to find the limit as x approaches 2 from the left, substitute x = 2 into the first sub-function:

[tex]\displaystyle \lim_{x \to 2^{-}} f(x)=2+2=4[/tex]

As x approaches 2 from the right, x > 2. Therefore, to find the limit as x approaches 2 from the right, substitute x = 2 into the second sub-function:

[tex]\begin{aligned}\displaystyle \lim_{x \to 2^{+}} f(x)&=a(2)^2-b(2)+3\\&=4a-2b+3\end{aligned}[/tex]

To ensure continuity at x = 2, equate the limits:

[tex]4=4a - 2b + 3[/tex]

Solve for b in terms of a:

[tex]\begin{aligned}4&=4a - 2b + 3&\\ 2b+4&=4a+3\\2b&=4a-1\\b&=2a-\dfrac{1}{2}\end{aligned}[/tex]

Now, we need to find a and b so that f(x) is continuous at x = 3.

As x approaches 3 from the left, x < 3. Therefore, to find the limit as x approaches 3 from the left, substitute x = 3 into the second sub-function:

[tex]\begin{aligned}\displaystyle \lim_{x \to 3^{-}} f(x)&=a(3)^2 - b(3) + 3\\&= 9a - 3b + 3\end{aligned}[/tex]

As x approaches 3 from the right, x > 3. Therefore, to find the limit as x approaches 3 from the right, substitute x = 3 into the third sub-function:

[tex]\begin{aligned}\displaystyle \lim_{x \to 3^{+}} f(x)&= 2(3) - a + b\\&= 6 - a + b\end{aligned}[/tex]

To ensure continuity at x = 3, equate the limits:

[tex]9a - 3b + 3 = 6-a+b[/tex]

Solve for b in terms of a:

[tex]\begin{aligned}9a - 3b + 3 &= 6-a+b\\10a-3b+3&=6+b\\10a+3&=6+4b\\10a-3&=4b\\4b&=10a-3\\b&=\dfrac{5}{2}a-\dfrac{3}{4}\end{aligned}[/tex]

Substitute this expression for b into the equation obtained from continuity at x = 2:

[tex]\dfrac{5}{2}a-\dfrac{3}{4}=2a-\dfrac{1}{2}[/tex]

Solve for a:

[tex]\begin{aligned}\dfrac{5}{2}a-\dfrac{3}{4}&=2a-\dfrac{1}{2}\\\\\dfrac{1}{2}a-\dfrac{3}{4}&=-\dfrac{1}{2}\\\\\dfrac{1}{2}a&=\dfrac{1}{4}\\\\a&=\dfrac{1}{2} \end{aligned}[/tex]

Substitute the found value of a into the expression for b and solve for b:

[tex]\begin{aligned}b&=2\left(\dfrac{1}{2}\right)-\dfrac{1}{2}\\b&=1-\dfrac{1}{2}\\b&=\dfrac{1}{2}\end{aligned}[/tex]

Therefore, the values of a and b that make f(x) continuous at all points are:

[tex]a=\dfrac{1}{2},\;\;b=\dfrac{1}{2}[/tex]

So the function f(x) is:

[tex]f(x)=\begin{cases} \dfrac{x^2-4}{x-2}&\text{if}\;\;x < 2\\\\\dfrac{1}{2}x^2-\dfrac{1}{2}x+3\quad&\text{if}\;\;2 \leq x < 3\\\\2x&\text{if}\;\;x \geq 3\end{cases}[/tex]

The range of brain volume is 572 cm^3.

To obtain the range, simply subtract the minimum value from the maximum.

Range equals High minus Low:

Range = 1484 cubic centimeters minus 912 cubic centimeters,

producing a difference of 572 cubic centimeters.

Thus, the range for brain volume is verified at exactly 572 cm³.

The range of a set of data in statistics is the difference between the largest and smallest values, calculated by subtracting the sample maximum and minimum. It is given in the same units as the data.

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Given that the brain volume varies from a low of 912 cm^3 to a high of 1484 cm^3, what is the range of brain volume?

The statement is true. The mean one-way commute time for the 30 largest U.S. cities is 25.8 minutes, and New York City has the longest mean travel time at 37.5 minutes, with a normal probability distribution and a standard deviation of 6.5 minutes.

True. The question states that among the 30 largest U.S. cities, the mean one-way commute time to work is 25.8 minutes. This means that on average, the commute time for these 30 cities is 25.8 minutes. However, the question also states that the longest one-way travel time is in New York City, where the mean time is 37.5 minutes. This means that New York City has a longer commute time compared to the other 29 cities.

Assuming the distribution of travel times in New York City follows the normal probability distribution and the standard deviation is 6.5 minutes, it is possible to calculate the probability of having a certain commute time. For example, the probability of having a commute time between 30 and 40 minutes can be calculated using the normal distribution formula.

Overall, it is true that among the 30 largest U.S. cities, the mean one-way commute time to work is 25.8 minutes and the longest one-way travel time is in New York City, where the mean time is 37.5 minutes.

True. Among the 30 largest U.S. cities, the mean one-way commute time to work is 25.8 minutes. New York City, known for its extensive public transportation system and traffic congestion, has the longest one-way travel time with a mean time of 37.5 minutes. Since the distribution of travel times in New York City follows the normal probability distribution, we can use this information to understand the variation in commute times for its residents.

The standard deviation for this distribution is 6.5 minutes, which indicates how spread out the travel times are from the mean. A smaller standard deviation would mean that most commute times are closer to the mean, while a larger standard deviation signifies that the data is more spread out, with some individuals having much shorter or longer commutes than the average.

In conclusion, the statement is true. The mean one-way commute time for the 30 largest U.S. cities is 25.8 minutes, and New York City has the longest mean travel time at 37.5 minutes, with a normal probability distribution and a standard deviation of 6.5 minutes.

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The building is 51 feet tall

The value of x is 1.5

The length of the building is solved by comparing the building's height by John's height as this forms similar triangles

The comparison is done using the proportions as below

John's shadow / John's height = building's shadow / building's height

6 / 4.5 = 68 / building's height

cross multiplying

building's height x 6 = 4.5 * 68

building's height = 4.5 x 68 / 6

building's height = 51 feet

Solving for x

Using proportions

15 / 10 = 23x / 20x - 8

cross multiplying

(20x - 8) * 15 = 22x * 10

300x - 120 = 220x

300x - 220x = 120

80x = 120

x = 1.5

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He would fail to reject the null hypothesis and conclude that there is not enough evidence to support the claim.

What is null hypothesis?

The null hypothesis is:

H0: p <= 0.58

The alternative hypothesis is:

Ha: p > 0.58

Where p represents the true proportion of adults who take a daily multivitamin.

The medical adviser could conduct a hypothesis test using a significance level (alpha) of 0.05. He would need to collect a sample of adults and determine the proportion who take a daily multivitamin. He could then calculate the test statistic, which in this case would be a one-sample z-test, using the following formula:

z = (p - p0) / sqrt(p0(1 - p0) / n)

Where p is the sample proportion, p0 is the hypothesized proportion under the null hypothesis, and n is the sample size.

If the test statistic falls in the rejection region (i.e. if the p-value is less than the significance level), the medical adviser would reject the null hypothesis and conclude that there is evidence to support the claim that the proportion of adults who take a daily multivitamin is more than 0.58. If the test statistic does not fall in the rejection region, he would fail to reject the null hypothesis and conclude that there is not enough evidence to support the claim.

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Based on the number of doctors at the hospital who obtained results as extreme or more extreme than the results from the study,  since 13 out of 20 samples have more than 7 adults who take a daily multivitamin, there is NOT evidence to suggest that the proportion of adults who take a multivitamin is more than 58%. the correct answer is b.

To determine whether there is evidence to suggest that more than 58% of adults take a daily multivitamin, we need to analyze the results from the 20 samples taken by the doctors.

The statement mentions that 13 out of the 20 samples have more than 7 adults who take a daily multivitamin. This means that in these 13 samples, the proportion of adults taking a multivitamin is higher than 7/12, which is equivalent to 58%.

To determine whether this difference is statistically significant, we typically perform a hypothesis test. The null hypothesis (H0) in this case is that the proportion of adults taking a multivitamin is 58% or less (p ≤ 0.58). The alternative hypothesis (Ha) is that the proportion is more than 58% (p > 0.58).

If the observed results are significantly different from what would be expected under the null hypothesis, we reject the null hypothesis and conclude that there is evidence to support the alternative hypothesis.

Since 13 out of 20 samples have more than 7 adults who take a daily multivitamin, there is NOT evidence to suggest that the proportion of adults who take a multivitamin is more than 58% because it acknowledges that the observed results are not significantly different from the original study. The correct answer is B.

In hypothesis testing, we typically set a significance level (e.g., 0.05) to determine if the evidence is statistically significant. If the p-value (the probability of obtaining results as extreme or more extreme than the observed results) is less than the significance level, we reject the null hypothesis.

Your question is incomplete but probably your full question was attached below

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