Can someone Help please

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Answer 1

Answer:

Answer:

942

Step-by-step explanation:

The formula for cone volume is V=πr²h/3. If you plug the radius and height in for the variables and use 3.14 for pi you get 942.

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The following data give the prices of seven textbooks randomly selected from a university bookstore. $93 $173 $107 $125 $56 $163 $144 a. Find the mean for these data. Calculate the deviations of the data values from the mean. Is the sum of these deviations zero? Mean = $ 123 Deviation from the mean for $173 = $ 0 Sum of these deviations = $ -433 b. Calculate the range, variance, and standard deviation. [Round your answers to 2 decimal places.] Range = $ Variance = Standard deviation = $ Click if you would like to Show Work for this question: Open Show Work LINK TO TEXT

hi can someone help me with is problem on how to break it down so I can explain it to my daughter. please.

Answers

Answer: 30

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Explanation:

Refer to the drawing below. I have a 2 by 5 grid of squares. So there are 2*5 = 10 squares total.

Four of those squares are shaded blue to represent the fraction $(4)/(10)$

If Susan used 4 blue tiles (instead of 12), then she'd have 10 tiles total. This would mean 10 would be the answer.

However, she's using 12 blue tiles. The jump from 4 to 12 is "times 3". So we'll need to multiply that 10 by 3 as well.

10*3 = 30

If Susan uses 12 blue tiles, then she has 30 tiles total.

Notice that the fraction $(4)/(10)$ is the same as $(12)/(30)$ after multiplying both top and bottom by 3.

$(4)/(10)= (4*3)/(10*3)= (12)/(30)$

If you wanted, you can split a round cake into 10 equal slices. If a person eats 4 slices, then that represents the fraction $(4)/(10)$ . Now imagine splitting each of those initial ten slices into three smaller pieces. If you manage to do so, then you'd have 30 very small slices. The four that the person ate would have effectively eaten 12 very small slices. So this is another way to see how $(4)/(10) = (12)/(30)$ . Personally, when it comes to fractions, I prefer using a grid of squares because it's a bit tricky sometimes to divide up circles perfectly.

In a basketball game, Carolyn made 14 out of 20 shots. Anna made 16 out of 24 shots. Explain how you can tell if the two players made a proportional number of shots.

Answers

Answer:

You will want to set up the ratio for each and set them equal to each other. Then you can cross multiply to verify if you get the same answer. Another strategy is to set up each ratio and then reduce to lowest terms to see if you get the same fraction.

Brainlist please?

Let the number of chocolate chips in a certain type of cookie have a Poisson distribution. We want the probability that a cookie of this type contains at least two chocolate chips to be greater than 0.99. Find the smallest value of the mean that the distribution can take.

Answers

Answer:

$\lambda \geq 6.63835$

Step-by-step explanation:

The Poisson Distribution is "a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space if these events occur with a known constant mean rate and independently of the time since the last event".

Let X the random variable that represent the number of chocolate chips in a certain type of cookie. We know that $X \sim Poisson(\lambda)$

The probability mass function for the random variable is given by:

$f(x)=(e^(-\lambda) \lambda^x)/(x!) , x=0,1,2,3,4,...$

And f(x)=0 for other case.

For this distribution the expected value is the same parameter $\lambda$

$E(X)=\mu =\lambda$

On this case we are interested on the probability of having at least two chocolate chips, and using the complement rule we have this:

$P(X\geq 2)=1-P(X<2)=1-P(X\leq 1)=1-[P(X=0)+P(X=1)]$

Using the pmf we can find the individual probabilities like this:

$P(X=0)=(e^(-\lambda) \lambda^0)/(0!)=e^(-\lambda)$

$P(X=1)=(e^(-\lambda) \lambda^1)/(1!)=\lambda e^(-\lambda)$

And replacing we have this:

$P(X\geq 2)=1-[P(X=0)+P(X=1)]=1-[e^(-\lambda) +\lambda e^(-\lambda)[]$

$P(X\geq 2)=1-e^(-\lambda)(1+\lambda)$

And we want this probability that at least of 99%, so we can set upt the following inequality:

$P(X\geq 2)=1-e^(-\lambda)(1+\lambda)\geq 0.99$

And now we can solve for $\lambda$

$0.01 \geq e^(-\lambda)(1+\lambda)$

Applying natural log on both sides we have:

$ln(0.01) \geq ln(e^(-\lambda)+ln(1+\lambda)$

$ln(0.01) \geq -\lambda+ln(1+\lambda)$

$\lambda-ln(1+\lambda)+ln(0.01) \geq 0$

Thats a no linear equation but if we use a numerical method like the Newthon raphson Method or the Jacobi method we find a good point of estimate for the solution.

Using the Newthon Raphson method, we apply this formula:

$x_(n+1)=x_n -(f(x_n))/(f'(x_n))$

Where :

$f(x_n)=\lambda -ln(1+\lambda)+ln(0.01)$

$f'(x_n)=1-(1)/(1+\lambda)$

Iterating as shown on the figure attached we find a final solution given by:

$\lambda \geq 6.63835$

Final answer:

The problem pertains to Poisson Distribution in probability theory, focusing on finding the smallest mean (λ) such that the probability of having at least two chocolate chips in a cookie is more than 0.99. This involves solving an inequality using the formula for Poisson Distribution.

Explanation:

This problem pertains to the Poisson Distribution, often used in probability theory. In particular, we're looking at the number of events (in this case, the number of chocolate chips) that occur within a fixed interval. Here, the interval under study is a single cookie. The question requires us to find the smallest value of λ (the mean value of the distribution) such that the probability of getting at least two chocolate chips in a cookie is more than 0.99.

Using the formula for Poisson Distribution, the probability of finding k copies of an event is given by:

P(X=k) = λ^k * exp(-λ) / k!

The condition here is that the probability of finding at least 2 copies is more than 0.99. Therefore, you formally need to solve the inequality:

P(X>=2) = 1 - P(X=0) - P(X=1) > 0.99

Substituting the values of P(X=0) and P(X=1) from our standard formula, you will need to calculate and find the smallest value of λ that satisfies this inequality.

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Given that a 90% confidence interval for the mean height of all adult males in Idaho measured in inches was [62.532, 76.478]. Use this to answer all parts. What was the point estimate used to estimate the mean height of all adult males in Idaho?

Answers

The point estimate used to estimate the mean height of all adult males in Idaho was 69.505 inches.

Calculation of the estimation of the point

Since Given that a 90% confidence interval for the mean height of all adult males in Idaho measured in inches was [62.532, 76.478].

So, the estimation of the point is

$= (62.532 + 76.478) / 2$

= 69.505 inches

Learn more about mean here: brainly.com/question/1863752

Answer:

The point estimate used to estimate the mean height of all adult males in Idaho was 69.505 inches.

Step-by-step explanation:

The point estimate is the halfway point of the confidence interval, that is, the lower bound added to the upper bound, and then this sum is divided by 2. So

Lower bound: 62.535

Upper bound: 76.478

Point estimate:

$P_(e) = (62.535 + 76.478)/(2) = 69.505$

The point estimate used to estimate the mean height of all adult males in Idaho was 69.505 inches.

What are the coordinates of the vertices of the polygon in the graph that are in Quadrant I? Question 7 options: A) (–3,–4) B) (1,1), (2,2), (2,5), (5,5) C) (2,–3), (3,–4), (5,–4) D) (–4,2), (–2,5)

Answers

Answer:

Answer B (1,1), (2,2), (2,5), (5,5)

Step-by-step explanation:

Notice that although the image is not shown, of the given answers, the only points that have coordinates that belong to Quadrant I , are those that show oosittive number for both coordinates (for x and for y). That is the only possible solution is:

answer B) : (1,1), (2,2), (2,5), (5,5)

Two fair dice are tossed, and the following events are defined: A: {Sum of the numbers showing is odd}
B: {Sum of the numbers showing is 9,11, or 12}
Are events A and B independent? Why?

Answers

Answer:

A and B are not independent.

Step-by-step explanation:

Two events are said to be independent if : $P(A \cap B)=P(A)P(B)$

A: {Sum of the numbers showing is odd}

B: {Sum of the numbers showing is 9,11, or 12}

Given two dice, the sample space is given as:

(1,1), (2,1), (3,1), (4,1), (5,1), (6,1)

(1,2), (2,2), (3,2), (4,2), (5,2), (6,2)

(1,3), (2,3), (3,3), (4,3), (5,3), (6,3)

(1,4), (2,4), (3,4), (4,4), (5,4), (6,4)

(1,5), (2,5), (3,5), (4,5), (5,5), (6,5)

(1,6), (2,6), (3,6), (4,6), (5,6), (6,6)

The outcomes of event A:{Sum of the numbers showing is odd} are:

(2,1), (4,1), (6,1), (1,2), (3,2),(5,2), (2,3), (4,3), (6,3)

(1,4), (3,4), (5,4), (2,5), (4,5), (6,5), (1,6), (3,6), (5,6)

P(A)=18/36

The outcomes of event B:{Sum of the numbers showing is 9,11, or 12} are:

(6,3), (5,4),(4,5) (6,5), (3,6), (5,6), (6,6)

P(B)=7/36

The intersection of A and B are:

(6,3), (5,4),(4,5) (6,5), (3,6), (5,6)

$P(A\cap B)=6/36$

We can see from the above that:

$P(A)P(B)=(7)/(36)* (18)/(36)=(7)/(72)\neq P(A\cap B)$

Therefore, events A and B are not independent.

Final answer:

The events A and B are dependent because the outcome of one event affects the probability of the other event happening.

Explanation:

The events A and B are dependent because the outcome of one event affects the probability of the other event happening. To determine if two events are independent, we need to check if the probability of the intersection of A and B is equal to the product of their individual probabilities.

Let's calculate the probabilities:

For event A, we need to find the sum of the numbers showing on the dice. In a fair die, there are 3 odd numbers (1, 3, and 5) out of 6 possible outcomes. So, the probability of event A is 3/6 or 1/2.
For event B, we need to find the sum of the numbers showing on the dice. There are three possible sums that satisfy event B: 9 (3+6, 4+5, 5+4), 11 (5+6, 6+5), and 12 (6+6). Out of the 36 possible outcomes, there are 6 outcomes that satisfy event B. So, the probability of event B is 6/36 or 1/6.
Now, let's check if events A and B are independent by calculating the probability of their intersection. The intersection of A and B is the event that both the sum is odd (event A) and the sum is 9, 11, or 12 (event B). There are no outcomes that satisfy both events A and B. So, the probability of the intersection is 0.
Finally, let's check if the product of the individual probabilities is equal to the probability of the intersection. The product of the individual probabilities is (1/2) * (1/6) = 1/12, which is not equal to 0. Therefore, events A and B are dependent.

In summary, events A and B are dependent because the outcome of one event affects the probability of the other event happening.

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