J. P. Morgan Asset Management publishes information about financial investments. Over the past years, the expected return for the S&P was with a standard deviation of and the expected return over that same period for a Core Bonds fund was with a standard deviation of (J. P. Morgan Asset Management, Guide to the Markets, 1st Quarter, ). The publication also reported that the correlation between the S&P and Core Bonds is . You are considering portfolio investments that are composed of an S&P index fund and a Core Bonds fund. a. Using the information provided, determine the covariance between the S&P and Core Bonds. Round your answer to two decimal places. If required enter negative values as negative numbers.

Answer:

Correct option: B. About 1,686.

Step-by-step explanation:

The formula to compute the order quantity (Q) is:

[tex]Q=(q_{d}\times (I+L))+(z\times\sigma_{I+L})-I_{n}[/tex]

Here

[tex]q_{d}=average\ daily\ semand=200\\I = Inventory\ review\ time=4\\L=lead\ time=5\\\sigma_{I+L}=standard\ deviation\ over\ the\ review\ and\ lead\ time=3\\I_{n}=number\ of\ units\ of\ inventory\ on\ hand=120[/tex]

Compute the order quantity as follows:

[tex]Q=(q_{d}\times (I+L))+(z\times\sigma_{I+L})-I_{n}\\=(200\times(4+5))+(1.96\times 3)-120\\=1800+5.88-120\\=1685.88\\\approx1686[/tex]

Thus, the order quantity was about 1,686.

Answer:

30.85% probability of one can less than 12 oz

Step-by-step explanation:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

In this problem, we have that:

[tex]\mu = 12.1, \sigma = 0.2[/tex]

a) What is the probability of one can less than 12 oz

This is the pvalue of Z when X = 12. So

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

[tex]Z = \frac{12 - 12.1}{0.2}[/tex]

[tex]Z = -0.5[/tex]

[tex]Z = -0.5[/tex] has a pvalue of 0.3085

30.85% probability of one can less than 12 oz

Answer:

Probability = 1

Step-by-step explanation:

The number of each type of card described in the question from within a full deck of cards is as follows;

Hearts = 13

Clubs = 13

Diamonds = 13

Spades = 13

These add up to a total of 52 cards. Since a deck only has 52 cards, these make up all the cards in the deck.

Since the probability of taking out a card from these four suits is going to be as follows:

Probability = number of ways we can take out a corresponding suit card / total number of cards

Probability = 52 / 52

Probability = 1

Thus, we can see that the probability of taking out a card belonging to one of the four suits (heart,diamond,club,spade) is 1.

Answer:

Therefore, the solutions of the quadratic equations are:

[tex]x=5,\:x=3[/tex]

The graph is also attached.

Step-by-step explanation:

The solution of the graph could be obtained by finding the x-intercept.

[tex]y=\left(x-\:4\right)^2-1[/tex]

Finding the x-intercept by substituting the value y = 0

so

[tex]y=\left(x-\:4\right)^2-1[/tex]

[tex]\:0\:=\:\left(x\:-\:4\right)^2\:-\:1[/tex]        ∵ y = 0

[tex]\left(x-4\right)^2-1=0[/tex]

[tex]\left(x-4\right)^2-1+1=0+1[/tex]

[tex]\left(x-4\right)^2=1[/tex]

[tex]\mathrm{For\:}\left(g\left(x\right)\right)^2=f\left(a\right)\mathrm{\:the\:solutions\:are\:}g\left(x\right)=\sqrt{f\left(a\right)},\:\:-\sqrt{f\left(a\right)}[/tex]

[tex]\mathrm{Solve\:}\:x-4=\sqrt{1}[/tex]

[tex]\mathrm{Apply\:rule}\:\sqrt{1}=1[/tex]

[tex]x-4=1[/tex]

[tex]x=5[/tex]

[tex]\mathrm{Solve\:}\:x-4=-\sqrt{1}[/tex]

[tex]\mathrm{Apply\:rule}\:\sqrt{1}=1[/tex]

[tex]x-4=-1[/tex]

[tex]x=3[/tex]

So, when y = 0, then x values are 3, and 5.

Therefore, the solutions of the quadratic equations are:

[tex]x=5,\:x=3[/tex]

The graph is also attached. As the graph is a Parabola. It is visible from the graph that the values of y = 0 at x = 5 and x = 3. As the graph is a Parabola.

Answer:

3 and 5 is the answer

Step-by-step explanation:

Answer:

a) The second machine is more likely to produce an acceptable cork.

b) Acceptable range for cork diameters produced by the first machine with a 90% confidence = (2.8355, 3.1645)

Step-by-step explanation:

This is a normal distribution problem

For the first machine,

Mean = μ = 3 cm

Standard deviation = σ = 0.1 cm

And we want to find which percentage of the population falls between 2.9 cm and 3.1 cm.

P(2.9 ≤ x ≤ 3.1) = P(x ≤ 3.1) - P(x ≤ 2.9)

We first standardize this measurements.

The standardized score for any value is the value minus the mean then divided by the standard deviation.

For 2.9 cm

z = (x - μ)/σ = (2.9 - 3.0)/0.1 = - 1.00

For 3.1 cm

z = (x - μ)/σ = (3.1 - 3.0)/0.1 = 1.00

P(x ≤ 3.1) = P(z ≤ 1.00) = 0.841

P(x ≤ 2.9) = P(z ≤ -1.00) = 0.159

P(2.9 ≤ x ≤ 3.1) = P(-1.00 ≤ z ≤ 1.00) = P(z ≤ 1.00) - P(z ≤ -1.00) = 0.841 - 0.159 = 0.682 = 68.2%

This means that 68.2% of the diameter of corks produced by the first machine lies between 2.9 cm and 3.1 cm.

For the second machine,

Mean = μ = 3.04 cm

Standard deviation = σ = 0.02 cm

And we want to find which percentage of the population falls between 2.9 cm and 3.1 cm.

P(2.9 ≤ x ≤ 3.1) = P(x ≤ 3.1) - P(x ≤ 2.9)

We standardize this measurements.

The standardized score for any value is the value minus the mean then divided by the standard deviation.

For 2.9 cm

z = (x - μ)/σ = (2.9 - 3.04)/0.02 = - 7.00

For 3.1 cm

z = (x - μ)/σ = (3.1 - 3.0)/0.02 = 3.00

P(x ≤ 3.1) = P(z ≤ 3.00) = 0.999

P(x ≤ 2.9) = P(z ≤ -7.00) = 0.0

P(2.9 ≤ x ≤ 3.1) = P(-7.00 ≤ z ≤ 3.00) = P(z ≤ 3.00) - P(z ≤ -7.00) = 0.999 - 0.0 = 0.999 = 99.9%

This means that 99.9% of the diameter of corks produced by the second machine lies between 2.9 cm and 3.1 cm.

Hence, we can conclude that the second machine is more likely to produce an acceptable cork.

b) Margin of error = (z-multiplier) × (standard deviation of the population)

For 90% confidence interval, z-multiplier = 1.645 (from literature and the z-tables)

Standard deviation for first machine = 0.1

Margin of error, d = 1.645 × 0.1 = 0.1645.

The acceptable range = (mean ± margin of error)

Mean = 3

Margin of error = 0.1645

Lower limit of the acceptable range = 3 - d = 3 - 0.1645 = 2.8355

Upper limit of the acceptable range = 3 + d = 3 + 0.1645 = 3.1645

Acceptable range = (2.8355, 3.1645)

Final answer:

To determine which machine is more likely to produce acceptable corks, we examine their distribution characteristics. Machine 2 may be more reliable due to its tighter control despite a slightly higher mean. To find a 90% certain acceptable range for Machine 1, we calculate using its standard deviation and the z-score for the 90th percentile.

Explanation:

The question involves comparing two machines based on their ability to produce corks within a specified acceptable diameter range using normal distribution properties, and calculating the range for diameters to ensure a 90% certainty of producing acceptable corks for the first machine.

Comparing the Two Machines

For the first machine with a mean diameter of 3 cm and a standard deviation of 0.1 cm, and the second machine with a mean diameter of 3.04 cm and a standard deviation of 0.02 cm, the question is which machine is more likely to produce corks within the acceptable range of 2.9 cm to 3.1 cm.

Machine 1 produces corks closer to the center of the acceptable range but with a wider spread (higher standard deviation), while Machine 2 produces corks that are skewed slightly larger but with a much tighter spread around their mean (lower standard deviation). To determine which machine is more likely to produce acceptable corks, we would need to calculate the z-scores for the acceptance limits for both machines and compare the probabilities. However, intuitively, Machine 2 might be seen as more reliable due to its tighter control (lower standard deviation), assuming its mean is not too far out of the acceptable range.

Finding the Acceptable Range for 90% Certainty

To ensure 90% certainty that a cork produced by Machine 1 falls within an acceptable diameter range, we need to determine d in the range of 3 − d cm to 3 + d cm. This involves finding the z-score that corresponds to the 5th and 95th percentiles due to the symmetric nature of normal distribution, then solving for d using the properties of normal distribution and the given standard deviation of 0.1 cm.

The z-score corresponding to the 5th and 95th percentiles (for a 90% certainty) typically falls around ±1.645. Using the formula for z-score, which is (X − μ) / σ, and solving for d, we can find the acceptable range of diameters for the first machine to produce an acceptable cork with 90% certainty.

Answer:

[tex]z=\frac{0.872 -0.9}{\sqrt{\frac{0.9(1-0.9)}{180}}}=-1.252[/tex]  

[tex]p_v =P(z<-1.252)=0.105[/tex]  

So the p value obtained was a very low value and using the significance level given [tex]\alpha=0.1[/tex] we have [tex]p_v>\alpha[/tex] so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 10% the proportion of students who came from Arkansas or a bordering state is not significantly lower than 0.9

b. Fail to reject H0; conclude that the new policy increases the percentage of students from states that don’t border Arkansas

Step-by-step explanation:

Data given and notation n  

n=180 represent the random sample taken

X=157 represent the students who came from Arkansas or a bordering state

[tex]\hat p=\frac{157}{180}=0.872[/tex] estimated proportion of students who came from Arkansas or a bordering state

[tex]p_o=0.9[/tex] is the value that we want to test

[tex]\alpha=0.1[/tex] represent the significance level

Confidence=90% or 0.90

z would represent the statistic (variable of interest)

[tex]p_v[/tex] represent the p value (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the true proportion is higher or not than 0.9.:  

Null hypothesis:[tex]p\geq 0.9[/tex]  

Alternative hypothesis:[tex]p < 0.9[/tex]  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

[tex]z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}[/tex] (1)  

The One-Sample Proportion Test is used to assess whether a population proportion [tex]\hat p[/tex] is significantly different from a hypothesized value [tex]p_o[/tex].

Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

[tex]z=\frac{0.872 -0.9}{\sqrt{\frac{0.9(1-0.9)}{180}}}=-1.252[/tex]  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.

The significance level provided [tex]\alpha=0.1[/tex]. The next step would be calculate the p value for this test.  

Since is a left tailed test the p value would be:  

[tex]p_v =P(z<-1.252)=0.105[/tex]  

So the p value obtained was a very low value and using the significance level given [tex]\alpha=0.1[/tex] we have [tex]p_v>\alpha[/tex] so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 10% the proportion of students who came from Arkansas or a bordering state is not significantly lower than 0.9

b. Fail to reject H0; conclude that the new policy increases the percentage of students from states that don’t border Arkansas

Answer:

"s" is the river speed  16 miles is the one-way distance

Time = distance / velocity  

2.6  =  [16 / (13 + s) ]   +  [16 / (13 -s) ]

That solves to s = 3 miles per hour

Step-by-step explanation:

Answer: the speed of the current is 3 mph

Step-by-step explanation:

Let x represent the speed of the river current.

Bob can row 13mph in still water. Assuming that while rowing upstream, he rowed against the current, this means that his total speed upstream is (13 - x) mph

Assuming that while rowing downstream, he rowed with the current, this means that his total speed downstream is (13 + x) mph.x

If the total distance downstream and back is 32 miles. Assuming the distance upstream and downstream is the same, then the distance upstream is 32/2 = 16 miles. Distance downstream is also 16 miles.

Time = Distance/speed

Time taken to row upstream is

16/(13 - x)

Time taken to row downstream is

16/(13 + x)

If total time spent is 2.6 hours, it means that

16/(13 - x) + 16/(13 + x) = 2.6

Cross multiplying, it becomes

16(13 + x) + 16(13 - x) = 2.6(13 + x)(13 - x)

= 208 + 16x + 208 - 16x = 2.6(169 - 13x + 13x - x²)

416 = 2.6(169 - x²)

416/2.6 = 169 - x²

160 = 169 - x²

x² = 169 - 160 = 9

x =√9

x = 3

Answer:

Step-by-step explanation:

Since there are 4 cities, there are (4-1)! = 6 possible routes. Half of those are the reverse of the other half, so there are 6/2 = 3 different possible routes. All of those are listed among the answer choices, along with their cost. All you need to do is choose the answer with the lowest cost:

  ACDBA, $900

__

At $960, the other two routes are higher cost.

Answer:

It would take 3 painters, a total number of 8 hours, to paint the house

Step-by-step explanation:

Let the number of hours be denoted by N, and the number of painters be denoted by P. The inverse relationship can be expressed as:

N α [tex]\frac{1}{P}[/tex]

Removing the proportionality symbol (α), introduces a constant of proportionality, which can be assumed to be C, in this example.

So, N = [tex]\frac{C}{P}[/tex]

When N = 6, P = 4

6 = [tex]\frac{C}{4}[/tex]

C = 24

So that, N = [tex]\frac{24}{P}[/tex]. This is the formula to use for determination of the other variable when one of them is known.

Now, given 3 painters, the number of hours needed can be obtained as follows:

N = [tex]\frac{24}{3}[/tex] = 8 hours

Solution:

Given that,

A supervisor must split 60 hours of overtime between five people

One employee must be assigned twice the number of hours as each of the other four employees

Let  "x" be the number of hours overtime per person.

One person does 2x hours of overtime

Which means,

(number of hours overtime per person)(6 person) = 60 hours

6x = 60

x = 10

Thus, 4 people do 10 hours and one person does 20 hours

Answer:P(O)UP(Rh)=17% while n(O)U(Rh) complement is 87%

Step-by-step explanation:

Since 43% represent those blood group O and 19% those with blood Rh,summing up gives 62%

Subtract 45% from 62%=17%

The probability that the person doesn't have either blood group is1 -17%=83%

Answer:

The probability that a person has a positive Rh factor given that he/she has type O blood is 82 percent.

There is a greater probability for a person to have a Positive Rh factor given type A blood than a person to have a positive Rh factor given type O blood.

Answer:

k=1

P(12)=256

Step-by-step explanation:

The model for population involving birth and death is given as:

[tex]\frac{dP}{dt}=(b-d)P[/tex]

where b=birth rate and d=death rate.

If the birth and death rate are inversely proportional to [tex]\sqrt{P}[/tex]

[tex]b=\frac{A}{\sqrt{P} } \\d=\frac{B}{\sqrt{P} }[/tex] where A and B are constants of variation.

Substituting b and d into our model

[tex]\frac{dP}{dt}=(\frac{A}{\sqrt{P} }-\frac{B}{\sqrt{P} })P\\\frac{dP}{dt}=\frac{k}{\sqrt{P} }P\\[/tex] where A-B=k, another constant

Simplifying using indices

[tex]\frac{dP}{dt}={k}P^{1-\frac{1}{2} }\\\frac{dP}{dt}={k}P^\frac{1}{2} \\[/tex]

Next, we Separate Variables and Integrate both sides

[tex]\frac{dP}{\sqrt{P} }={k}dt\[/tex]

[tex]\int\frac{dP}{\sqrt{P} }=\int{k}dt\[/tex]

[tex]2P^{1/2} =kt+C[/tex] where C is the constant of integration

[tex]P(t) =(\frac{kt}{2} +C)^2[/tex]

When t=0, P(t)=[tex]P_0[/tex], C=[tex]\sqrt{P_0}[/tex]

[tex]P(t) =(\frac{kt}{2} +\sqrt{P_0})^2[/tex] as required.

(b)If [tex]P_0[/tex]=100, t=6 months, P(t)=169

[tex]P(t) =(\frac{kt}{2} +\sqrt{P_0})^2[/tex]

[tex]169 =(\frac{6k}{2} +\sqrt{100})^2\\\sqrt{169} =3k+100\\13=3k+10\\3k=13-10=3\\k=1[/tex]

Since we have found the constant k, we can then calculate the population after 1 year. Note that we use 12 months since we used month earlier to get k.

[tex]P(t) =(\frac{kt}{2} +\sqrt{P_0})^2[/tex]

[tex]P(12) =(\frac{1X12}{2} +\sqrt{100})^2\\=(6+10)^2=256[/tex]

Therefore the population after a year is 256.

The population of fish after 1 year would be 285.

Let P be the population of fish at any time t months.

We are given:

We need to determine the population after 12 months.

The logistic growth model can be expressed as:

dP/dt = rP(1 - P/K)

where r is the intrinsic growth rate and K is the carrying capacity of the environment. Here, since the birth and death rates are inversely proportional to √P, we can infer that the growth rate might be proportional to √P, leading us to use a simplified logistic growth equation.

Given P(6) = 169, let’s find the intrinsic growth rate , r. From population changes between 0 and 6 months:

Let’s assume the logistic growth function in the form:

P(t) = [tex]P_0 e^{rt}[/tex]

We solve for r:

169 = [tex]100 e^{6r}[/tex]

1.69 = [tex]e^{6r}[/tex]

Taking natural logarithms:

ln(1.69) = 6r

0.524 = 6r

r = 0.0873/month

Now, to find P(12):

P(12) = [tex]100 e^{0.0873*12}[/tex]

= [tex]100 e^{1.048}[/tex]

= 100 * 2.853

= 285.3 fish

So, the population after 1 year is approximately 285 fish.

Answer:

0.249579

Step-by-step explanation:

P(rain) = 0.3

P(no rain) = 1 - 0.3 = 0.7

The event of rain falling a second time within the next 5 days is possible in these ways

1. Rain on days 1 and 2

2. Rain on days 1 and 3; none on day 2

3. Rain on days 1 and 4; none on days 2 and 3

4. Rain on days 1 and 5; none on days 2, 3 and 4

5. Rain on days 1 and 6; none on day 2, 3, 4 and 5

[tex]P(\text{second rain within 5 days}) = 0.3^2+0.3^2\times0.7+0.3^2\times0.7^2+0.3^2\times0.7^3+0.3^2\times0.7^4 = 0.3^2(1+0.7+0.7^2+0.7^3+0.7^4)= 0.09\times2.7731=0.249579[/tex]

Answer:

Please find attached file for complete answer solution and explanation of same question.

Step-by-step explanation:

In factual tests, an invalid speculation recommends that there is no importance between factors in a bunch of noticed information. In the given decisions, the assertion shows no distinction in the pace of ability improvement between school gymnasts who practice contemplation and the people who don't address the invalid speculation.

In factual theory testing, an invalid speculation is an assertion recommending that no measurable relationship and importance exists in a bunch of noticed information between factors. It expects that any noticed contrasts are because of possibility. So in the given choices, the invalid speculation is: 'There will be no distinction in the pace of expertise improvement between school gymnasts who practice contemplation and the people who don't.' This assertion proposes no effect of the variable (reflection) on the result (ability improvement), which is what an invalid theory addresses in a trial of importance.

https://brainly.com/question/32386318

#SPJ3

Answer:

The zeros of this function are 3 and -5.

Step-by-step explanation:

One note: The question says "Find the zeros of EACH function", but there seems to be only one function in the question. I hope I answered it well.

To complete the function provided, you need to get both terms inside both parenthesis to equal zero. So, if its (x-3)(x+5), the X's need to equal the opposite of the number that is being added or subtracted.

For the first parenthesis, (x-3), the number is -3, so the zero of that side is positive 3. (3-3 = 0)

For the second parenthesis, (x+5), the number is positive 5, so the zero of that side is -5. (-5+5 = 0)

Using the combinations formula C(n, r), the number of ways Maya can choose the food and drinks for the bridal shower is computed as: C(12,3) for drinks * C(12,3) for appetizers * C(10,3) for desserts.

The subject of this question is combinations in Mathematics. Maya has choices of 12 bottled drinks, 12 frozen appetizers, and 10 prepared desserts. She wants to pick 3 of each, and the order of selection does not matter. We can use the combination formula to calculate the number of ways she can do this:

So the total number of different ways Maya can pick the food and drinks to serve at the bridal shower is C(12,3) * C(12,3) * C(10,3).

https://brainly.com/question/24703398

#SPJ3

Answer:In a couple with a newborn baby at home, to take turns on feeding the baby at night.

Step-by-step explanation: Here both parents are willing to sacrifice a few minutes, if not hours of sleeptime with the promise to be allowed to rest the next time the baby needs to be fed. There is no certainty in how long it will take for the baby to go back to sleep or how long it will be for the baby to be awake again, but the chances are the same for both parents, so they both agree to take care of the child one at a time with the promise to be in turns, this is an example of contractarian logic.

Final answer:

Contractarian logic is exemplified in international trade agreements where nations mutually lower tariffs under the expectation of reciprocal actions, demonstrating the principle of reciprocity and mutual advantage.

Explanation:

According to contractarian logic, we should be willing to make concessions to others if they agree to make comparable and reciprocal concessions, leading to a situation where everyone benefits with a minimal level of sacrifice. A classic example illustrating this principle is international trade agreements. Nations often agree to lower tariffs and grant each other favorable trade terms under the condition that the other nation reciprocates. These agreements are founded on the expectation that both sides will adhere to the agreements, benefiting both by expanding their markets and reducing costs for consumers. Here, the benefit is mutual economic growth, and the sacrifice might involve foregoing the protection of certain domestic industries in the interest of broader gains. This scenario mirrors the foundational ideas of social contract theory where rational, self-interested agents come together to agree on a set of rules or actions that benefit all parties involved, thereby demonstrating the principle of reciprocity and mutual advantage that is central to contractarian logic.

Answer:

Step-by-step explanation:

There are three bags

Bag A

2apples and 4 oranges

P(A¹)=2/6

P(A¹)=⅓

P(O¹)=4/6

P(O¹)=⅔

Bag B

8 apples and 4 oranges

P(A²)=8/12

P(A²)=⅔

P(O²)=4/12

P(O²)=⅓

Bag C

1 apple and 3 oranges

P(A³)=¼

P(O³)=¾

Note

P(A¹) means probability of Apple in bag A

P(A²) means probability of Apple in bag B

P(A³) means probability of Apple in bag C

P(O¹) means probability of oranges in bag A.

P(O²) means probability of oranges in bag B.

P(O³) means probability of oranges in bag C.

a. The probability of picking exactly two apples can be analyzed as

Picking apple in bag A and picking apple in bag B and picking orange in bag C or picking apple in bag A and picking orange in bag B and picking apple in bag C or picking orange in bag A and picking apple in bag B and picking apple in bag C.

Then,

P(exactly two apples)=P(A¹ n A² n O³) + P(A¹ n O² n A³) + P(O¹ n A² n A³)

Since they are mutually exclusive

Then,

P(exactly two apples) =

P(A¹) P(A²)P(O³) + P(A¹)P(O²)P(A³) + P(O¹) P(A²) P(A³)

P(exactly two apples) =

(⅓×⅔×¾)+(⅓×⅓×¼)+(⅔×⅔¼)

P(exactly two apples)=1/6 +1/36 +1/9

P(exactly two apples)= 11/36

b. Probability that an apple comes from Bag A out of the two apple will be Picking apple in bag A and picking apple in bag B and picking orange in bag C or picking apple in bag A and picking orange in bag B and picking apple in bag C.

P(an apple belongs to bag A)=P(A¹ n A² n O³) + P(A¹ n O² n A³)

Since they are mutually exclusive

Then,

P(an apple belongs to bag A) =

P(A¹) P(A²)P(O³) + P(A¹)P(O²)P(A³)

P(an apple belongs to bag A) =

(⅓×⅔×¾)+(⅓×⅓×¼)

P(an apple belongs to bag A)=1/6 +1/36

P(an apple belongs to bag A)= 7/36

Answer:

Step-by-step explanation:

The detailed steps and appropriate workings is as shown in the attached file.

The question asks about reducing a second-order ODE to first-order given a known solution, which is achieved using the method of reduction of order to find a new function v(y) leading to a first-order ODE.

To reduce a second-order ordinary differential equation (ODE) to a first-order ODE, given that y1 is a solution, you can apply the method of reduction of order. This involves introducing a new function v(y) such that y can be expressed as a product of the known solution y1 and this new function v(y). Essentially, you substitute y = y1*v into the original second-order ODE and differentiate as necessary to obtain an equation in terms of v and its derivatives only, effectively transforming the equation into first-order.

The steps include (i) expressing y in terms of y1 and v, (ii) differentiating this expression to find the derivatives of y, and (iii) substituting all of this into the equation that y1 obeys. The resultant first-order equation will only involve the function v and its first derivative, v'. By solving this simplified equation, you can find v and thus the second solution to the original second-order ODE.

Answer:

The probability that there is no matching pair is 4/7 = 0.5714286.

Step-by-step explanation:

For the first glove we have no restrictions. For the second glove, we have 6 gloves that works for us and 1 that doesnt work (the one that matches the first glove), hence we have 6 possibilities out of 7. Once we pick a good second glove, for the last glove, we only have 4 cases that doesnt match the other two pairs, out of 6 total. This means that the probability that there is no matching pair is 6/7*4/6 = 4/7.

Answer:

Reliability

Step-by-step explanation:

Dylan took the Whaddayanno IQ Test today, and his IQ score was 130. Last week, his IQ score on the same test was 70. The Whaddayanno IQ Test appears to lack reliability.

Reliability can be defined as the extent to which an  experiment or test provides the same result on  repeated trials.

The huge difference in Dylan's IQ test scores in a short period of time suggests that the Whaddayanno IQ test is not reliable.  

Answer:

[tex] E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500[/tex]

In order to find the variance we need to find first the second moment given by:

[tex] E(X^2) = \sum_{i=1}^n X^2_i P(X_i)[/tex]

And replacing we got:

[tex] E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300[/tex]

The variance is calculated with this formula:

[tex] Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075[/tex]

And the standard deviation is just the square root of the variance and we got:

[tex] Sd(X) = \sqrt{0.3075}= 0.5545[/tex]

Step-by-step explanation:

Previous concepts

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).  

Solution to the problem

LEt X the random variable who represent the number of defective transistors. For this case we have the following probability distribution for X

X         0           1           2         3

P(X)    0.92     0.03    0.03     0.02

We can calculate the expected value with the following formula:

[tex] E(X) = \sum_{i=1}^n X_i P(X_i)[/tex]

And replacing we got:

[tex] E(X) = 0*0.92 + 1*0.03 +2*0.03 +3*0.02 = 0.1500[/tex]

In order to find the variance we need to find first the second moment given by:

[tex] E(X^2) = \sum_{i=1}^n X^2_i P(X_i)[/tex]

And replacing we got:

[tex] E(X^2) = 0^2*0.92 + 1^2*0.03 +2^2*0.03 +3^2*0.02 = 0.3300[/tex]

The variance is calculated with this formula:

[tex] Var(X) = E(X^2) -[E(X)]^2 = 0.33 -(0.15)^2 = 0.3075[/tex]

And the standard deviation is just the square root of the variance and we got:

[tex] Sd(X) = \sqrt{0.3075}= 0.5545[/tex]

The required  value of mean 0.330 and standard deviation 0.5545 for the defective transistors.

Given that,

A company has found that in carton of transistors: 92% contain no defective transistors,

3% contain one defective transistor, 3% contain two defective transistors,

and 2% contain three defective transistors.

We have to find,

Calculate the mean and variance for the defective transistors. Mean = Variance.

According to the question,

Let,  X the random variable who represent the number of defective transistors.

The following probability distribution for X,

X         0           1           2         3

P(X)   0.92     0.03    0.03     0.02

To calculate the expected value with the following formula:

[tex]E(X) = \sum^{n}_{i=1} X_i. P.(X_i)[/tex]

On substitute all the values in the formula,

[tex]E(X) = 0\times0.92 + 1\times0.03+2\times0.03 + 3\times0.02\\\\E(X) = 0.15[/tex]

To find the variance first the second moment given by:

[tex]E(X^2) = \sum^{n}_{i=1} X_i^2. P.(X_i)[/tex]

On substitute all the values in the formula;

[tex]E(X) = 0^2\times0.92 + 1^2\times0.03+2^2\times0.03 + 3^2\times0.02\\\\E(X) = 0.330[/tex]

Therefore, The variance is calculated with this formula:

[tex]Var(X) = E(X)^2 - (E(X))^2 = 0.33 - (0.15)^2 = 0.3075[/tex]

And the standard deviation is just the square root of the variance,

[tex]Standard \ deviation = \sqrt{0.0375} = 0.5545[/tex]

Hence, The required  value of mean 0.330 and standard deviation 0.5545 for the defective transistors.

To know more about Mean click the link given below.

https://brainly.com/question/15167067

Answer:

The point estimate of population mean is 21.6.

Step-by-step explanation:

A point estimate is a numerical value that is used to estimate the value of the parameter under study.

The point estimate is calculated using the sample values.

For example, sample ([tex]\bar x[/tex]) is the point estimate of population mean (μ), sample standard deviation (s) is the point estimate of population standard deviation (σ), sample proportion ([tex]\hat p[/tex]) is the point estimate of population proportion (p).

It is provided that the sample mean of 100 items is,

[tex]\bar x=21.6[/tex]

Then the point estimate of population mean is:

[tex]\mu=\bar x=21.6[/tex]

Thus, the point estimate of population mean is 21.6.

Answer:

See the attached pictures for answer.

Step-by-step explanation:

See the attached picture for detailed explanation.

Answer:

2.03 × 10¹⁴ different possibilities.

Step-by-step explanation:

We want to know the different ways 1000 people can come out to watch a movie at 6 different times of the day.

This is a permutation and combination problem.

Dividing 1000 people amongst 6 movie showings = 1005C5 = 1005!/(1005-5)!5!

= (1005×1004×1003×1002×1001×1000!)/(1000!5!) = (1005×1004×1003×1002×1001)/5! = 2.03 × 10¹⁴ different possibilities.

Answer:

20 m

Step-by-step explanation:

We are given that

Initial horizontal speed ,[tex]u_x=15 m/s[/tex]

Time, t=2 s

Initial vertical velocity, [tex]u_y=0[/tex]

We know that

[tex]h=u_yt+\frac{1}{2}gt^2[/tex]

Where [tex]g=-9.8m/s^2[/tex]

Using the formula

[tex]h=0(2)+\frac{1}{2}(-9.8)(2)^2[/tex]

[tex]h=-19.6 m\approx -20 m[/tex]

The negative sign indicates that the displacement of stone  is in downward direction.

Hence, the height of the cliff is closest to 20 m

Answer:

a) [tex]P(X=5)=(10C5)(0.8)^5 (1-0.8)^{10-5}=0.0264[/tex]

b) [tex] P(X<4) = P(X \leq 3) = P(X=0) +P(X=1) +P(X=2) +P(X=3)[/tex]

[tex]P(X=0)=(10C0)(0.8)^0 (1-0.8)^{10-0}=1.024x10^{-7}[/tex]

[tex]P(X=1)=(10C1)(0.8)^1 (1-0.8)^{10-1}=4.096x10^{-6}[/tex]

[tex]P(X=2)=(10C2)(0.8)^2 (1-0.8)^{10-2}=7.37x10^{-5}[/tex]

[tex]P(X=3)=(10C3)(0.8)^3 (1-0.8)^{10-3}=0.000786[/tex]

And adding we got:

[tex] P(X<4) =0.000864[/tex]

c) [tex] P(X \geq 6) = 1-P(X<6) = 1-P(X\leq 5) =1-[P(X=0) +....+P(X=5)][/tex]

[tex]P(X=0)=(10C0)(0.8)^0 (1-0.8)^{10-0}=1.024x10^{-7}[/tex]

[tex]P(X=1)=(10C1)(0.8)^1 (1-0.8)^{10-1}=4.096x10^{-6}[/tex]

[tex]P(X=2)=(10C2)(0.8)^2 (1-0.8)^{10-2}=7.37x10^{-5}[/tex]

[tex]P(X=3)=(10C3)(0.8)^3 (1-0.8)^{10-3}=0.000786[/tex]

[tex]P(X=4)=(10C4)(0.8)^4 (1-0.8)^{10-4}=0.0055[/tex]

[tex]P(X=5)=(10C5)(0.8)^5 (1-0.8)^{10-5}=0.0264[/tex]

And replacing we got:

[tex] P(X \geq 6) = 1- 0.0328= 0.967[/tex]

d) [tex] P(5 \leq X \leq 7) = P(X=5) +P(X=6) +P(X=7)[/tex]

[tex]P(X=5)=(10C5)(0.8)^5 (1-0.8)^{10-5}=0.0264[/tex]

[tex]P(X=6)=(10C6)(0.8)^6 (1-0.8)^{10-6}=0.088[/tex]

[tex]P(X=7)=(10C7)(0.8)^7 (1-0.8)^{10-7}=0.2013[/tex]

And replacing we got:

[tex] P(5 \leq X \leq 7) = P(X=5) +P(X=6) +P(X=7)=0.0264 +0.088+0.2013=0.316 [/tex]

e) [tex] E(X) = n*p = 10*0.8 =8[/tex]

Step-by-step explanation:

Previous concepts

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".

Solution to the problem

Let X the random variable of interest, on this case we now that:

[tex]X \sim Binom(n=10, p=0.8)[/tex]

The probability mass function for the Binomial distribution is given as:

[tex]P(X)=(nCx)(p)^x (1-p)^{n-x}[/tex]

Where (nCx) means combinatory and it's given by this formula:

[tex]nCx=\frac{n!}{(n-x)! x!}[/tex]

Part a

We want to find this probability:

[tex] P(X=5)[/tex]

And using the pmf we got:

[tex]P(X=5)=(10C5)(0.8)^5 (1-0.8)^{10-5}=0.0264[/tex]

Part b

[tex] P(X<4) = P(X \leq 3) = P(X=0) +P(X=1) +P(X=2) +P(X=3)[/tex]

[tex]P(X=0)=(10C0)(0.8)^0 (1-0.8)^{10-0}=1.024x10^{-7}[/tex]

[tex]P(X=1)=(10C1)(0.8)^1 (1-0.8)^{10-1}=4.096x10^{-6}[/tex]

[tex]P(X=2)=(10C2)(0.8)^2 (1-0.8)^{10-2}=7.37x10^{-5}[/tex]

[tex]P(X=3)=(10C3)(0.8)^3 (1-0.8)^{10-3}=0.000786[/tex]

And adding we got:

[tex] P(X<4) =0.000864[/tex]

Part c

For this case we can use the complement rule like this:

[tex] P(X \geq 6) = 1-P(X<6) = 1-P(X\leq 5) =1-[P(X=0) +....+P(X=5)][/tex]

[tex]P(X=0)=(10C0)(0.8)^0 (1-0.8)^{10-0}=1.024x10^{-7}[/tex]

[tex]P(X=1)=(10C1)(0.8)^1 (1-0.8)^{10-1}=4.096x10^{-6}[/tex]

[tex]P(X=2)=(10C2)(0.8)^2 (1-0.8)^{10-2}=7.37x10^{-5}[/tex]

[tex]P(X=3)=(10C3)(0.8)^3 (1-0.8)^{10-3}=0.000786[/tex]

[tex]P(X=4)=(10C4)(0.8)^4 (1-0.8)^{10-4}=0.0055[/tex]

[tex]P(X=5)=(10C5)(0.8)^5 (1-0.8)^{10-5}=0.0264[/tex]

And replacing we got:

[tex] P(X \geq 6) = 1- 0.0328= 0.967[/tex]

Part d

[tex] P(5 \leq X \leq 7) = P(X=5) +P(X=6) +P(X=7)[/tex]

[tex]P(X=5)=(10C5)(0.8)^5 (1-0.8)^{10-5}=0.0264[/tex]

[tex]P(X=6)=(10C6)(0.8)^6 (1-0.8)^{10-6}=0.088[/tex]

[tex]P(X=7)=(10C7)(0.8)^7 (1-0.8)^{10-7}=0.2013[/tex]

And replacing we got:

[tex] P(5 \leq X \leq 7) = P(X=5) +P(X=6) +P(X=7)=0.0264 +0.088+0.2013=0.316 [/tex]

Part e

The expected number is given by:

[tex] E(X) = n*p = 10*0.8 =8[/tex]

This answer provides step-by-step explanations for finding probabilities of professors with doctoral degrees and the expected number of professors with doctoral degrees.

Expected number of college professors with a doctoral degree:

Find the probability that five have a doctoral degree: Using the binomial probability formula, [tex]P(X = 5) = 10C5 * 0.8^5 * 0.2^5[/tex]

Find the probability that fewer than 4 have a doctoral degree: Calculate P(X < 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3).

Find the probability that at least 6 have a doctoral degree: Calculate P(X ≥ 6) = 1 - (P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5)).

Find the probability that between 5 and 7 inclusive have a doctoral degree: Calculate P(5 ≤ X ≤ 7) = P(X = 5) + P(X = 6) + P(X = 7).

Expected number of professors with a doctoral degree: Multiply the total number of professors by the probability (0.8).

Answer:

Probability that at least one of them suffers from arachnophobia is 0.5160.

Step-by-step explanation:

We are given that a 2005 survey found that 7% of teenagers (ages 13 to 17) suffer from an extreme fear of spiders (arachnophobia).

Also, At a summer camp there are 10 teenagers sleeping in each tent.

Firstly, the binomial probability is given by;

[tex]P(X=r) =\binom{n}{r}p^{r}(1-p)^{n-r} for x = 0,1,2,3,....[/tex]

where, n = number of trials(teenagers) taken = 10

           r = number of successes = at least one

          p = probability of success and success in our question is % of

                the teenagers suffering from arachnophobia, i.e. 7%.

Let X = Number of teenagers suffering from arachnophobia

So, X ~ [tex]Binom(n= 10,p=0.07)[/tex]

So, probability that at least one of them suffers from arachnophobia

= P(X >= 1) = 1 - probability that none of them suffers from arachnophobia

= 1 - P(X = 0) = 1 - [tex]\binom{10}{0}0.07^{0}(1-0.07)^{10-0}[/tex]

                       = 1 - (1 * 1 * [tex]0.93^{10}[/tex] ) = 1 - 0.484 = 0.5160 .

Therefore, Probability that at least one of them suffers from arachnophobia is 0.5160 .

Answer and Step-by-step explanation:

The answer is attached below

The expected pay-off for a₃ is maximum. Then the decision a₃ (study all night) is considered.

Statistics is the study of collection, analysis, interpretation, and presentation of data or to discipline to collect, summarise the data.

Hank is an intelligent student and usually makes good grades, provided that he can review the course material the night before the test.

For tomorrow's test, Hank is faced with a small problem: His fraternity brothers are having an all-night party in which he would like to participate.

Hank has three options:

a₁ - party all night

a₂ - divide the night equally between studying and partying

a₃ - study all night

Tomorrow's exam can be easy (S₁), moderate (S₂) or tough (S₃), depending on the professor's unpredictable mood. Hank anticipates the following scores:

             S₁               S₂             S₃

a₁          85              60             40

a₂         92              85             81

a₃        100              88             82

Decision under uncertainty

1.  For maximum criterion when the exam is tough.

a₁  = 40, a₂ = 81, and a₃ = 82

Since 82 is the maximum out of the minimum. Then the optional action is a₃ (study all night).

2.  For maximum criterion when the exam is easy.

a₁  = 85, a₂ = 92, and a₃ = 100

Since 82 is the maximum out of the maximum. Then the optional action is a₃ (study all night).

3.  Regret criterion

First, find the regret matrix.

             S₁               S₂             S₃         Max. regret

a₁          15              28             42                 42

a₂          8                3                1                   8

a₃          0                0               0                   0

From the maximum regret column, we find that the regret corresponding to the course of action is a₃ is minimum. Therefore, decision a₃ (study all night) will be considered.

4.  Laplace criterion

The probability of occurrence is 1/3.

Therefore, the expected pay-off for each decision will be

E(a₁) = 61.67, E(a₂) = 86, and E(a₃) = 90

Therefore, the expected pay-off for a₃ is maximum.

Thus, decision a₃ (study all night) is considered.

More about the statistics link is given below.

https://brainly.com/question/10951564