A short quiz has two true-false questions and one multiple-choice question with four possible answers. A student guesses at each question. Assuming the choices are all equally likely and the questions are independent of each other, the following is the probability distribution of the number of answers guessed correctly. What is the Probability of getting less than all three right

Answer:

Part a: The equation is [tex]N=N_{0}e^{-kt}[/tex]

Part b: The half life of the material is 2.4 days.

Step-by-step explanation:

Part a

The relation is given as

[tex]\frac{dN}{dt}=-kN[/tex]

Rearranging the equation gives

[tex]\frac{dN}{N}=-kdt[/tex]

Integrating and simplifying the equation as

                 [tex]\int \frac{dN}{N}=\int (-kdt)\\ln N=-kt+lnC\\N=e^{-kt+lnC}\\N=Ce^{-kt}[/tex]

This is the equation of radioactive decay of the radioactive material. For estimation of C consider following IVP where t=0,N=N_o so the equation becomes

[tex]N=Ce^{-kt}\\N_0=Ce^{-k(0)}\\N_0=Ce^{0}\\N_0=C[/tex]

Now substituting the value of C in the equation gives

[tex]N=N_{0}e^{-kt}[/tex]

This is the relation of concentration of unstable radioactive material at a given time .

Part b

From the given data the equation becomes as

                                       [tex]N=N_{0}e^{-kt}\\9=12\times e^{-k*1}\\e^{-k}=\frac{9}{12}[/tex]

Now half like is defined as the time when the quantity is exact half, i.e. N/N_o =0.5 so

                                      [tex]N=N_{0}e^{-kt}\\6=12\times e^{-k*t}\\e^{-kt}=\frac{6}{12}\\{e^{-k}}^t}=0.5\\(0.75)^t=0.5\\So\, t\, is\, given\, as \\t=\frac{ln 0.5}{ln 0.75}\\t=2.4 \, days[/tex]

So the half life of the material is 2.4 days.

Answer:

Step-by-step explanation:

given that a computer sends a packet of information along a channel and waits for a return signal acknowledging that the packet has been received. If no acknowledgment is received within a certain time, the packet is re-sent

Let X represent the number of times the packet is sent. Assume that the probability mass function of X is given by

p(x)={ cx for x=1,2,3,4, or 5

{ 0 otherwise

where c is a constant.

Let us write pdf as follows

x             1              2            3            4           5              Total

p             c             2c           3c         4c         5c              15c

Since total probability = 1

we get

[tex]c=\frac{1}{15}[/tex]

P(X=2)=2c = [tex]\frac{2}{15}[/tex]

Answer: Convenience sample.

Step-by-step explanation:

Convenience sample is also known as grab or accident or opportunity samples. It is a example of non probability sample that involves selecting of subjects because of the proximity, convenience and accessibility a researcher as to them. This type of samples are not reliable for data gathering when it involves a very large sample space, let's say a global audience.

Answer:

OUR ANSWER IS =0.0467  

Step-by-step explanation:

P(detect/defect)=0.98

P(detect/not defect)=0.01

P(defect)=1/2000=0.0005

P(not defect)=1-0.0005=0.9995

P(defect/detect)=P(detect/defect)*P(defect)/[P(detect/defect)*P(defect)+P(detect/not defect)*P(not defect)]

=0.98*0.0005/[0.98*0.0005+0.01*0.9995]

=0.00049/[0.00049+0.009995]

=0.00049/0.010485

=0.0467

Answer:

[tex]Z = -1.63[/tex]

Step-by-step explanation:

The z-score measures how many standard deviation a score X is above or below the mean.

it is given by the following formula:

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

In which

[tex]\mu[/tex] is the mean, [tex]\sigma[/tex] is the standard deviation

In this problem, we have that:

Mean weight of all students in a class is 165 pounds, so [tex]\mu = 165[/tex]

Variance of 234.09 square pounds. The standard deviation is the square root of the variance. So [tex]\sigma = \sqrt{234.09} = 15.3[/tex]

What is the z-value associated with a student whose weight is 140 pounds?

Z when X = 140. So

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

[tex]Z = \frac{140 - 165}{15.3}[/tex]

[tex]Z = -1.63[/tex]

To find the z-value associated with a student whose weight is 140 pounds, use the formula for calculating z-score. Substitute the values of mean, standard deviation, and the student's weight into the formula.

To find the z-value associated with a student whose weight is 140 pounds, we need to use the formula for calculating z-score:

z = (x - μ) / σ

The z-value associated with a student whose weight is 140 pounds can be calculated using the given formula and the information provided.

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Answer:

For this case the strongest linear association is given by the greatest correlation coeffcient in absolute value from the list provided. We have:

[tex] |r_3|>|r_2| > |r_4| > |r_1|[/tex]

So on this case we can conclude that the strongest linear association with number of wins is for runs allowed.

Step-by-step explanation:

Previous concepts

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.

And in order to calculate the correlation coefficient we can use this formula:  

[tex]r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}[/tex]  

Solution to the problem

For this case we have a list of correlation coefficients given:

[tex] r_1 = 0.51[/tex] represent the correlation between number of wins and shutouts

[tex] r_2 = 0.61[/tex] represent the correlation between number of wins and hits made

[tex] r_3 = -0.7[/tex] represent the correlation between number of wins and runs allowed

[tex] r_4 = -0.56[/tex] represent the correlation between number of wins and homeruns allowed

When we analyze linear association we are interested just in the absolute value for r since if r is near to +1 we have positive linear association but on the case that r is near to -1 we have an strong linear association but inversely proportional.

For this case the strongest linear association is given by the greatest correlation coeffcient in absolute value from the list provided. We have:

[tex] |r_3|>|r_2| > |r_4| > |r_1|[/tex]

So on this case we can conclude that the strongest linear association with number of wins is for runs allowed.

In relation to the number of wins for 14 baseball teams, the variable 'runs allowed' holds the strongest linear association. This is represented by its correlation coefficient of -0.70, indicating a strong inverse relationship. As 'runs allowed' increase, the 'number of wins' decrease.

In context of these 14 baseball teams, correlations are being determined with the number of wins in the regular season and four variables: shutouts, hits made, runs allowed, and homeruns allowed. The correlation coefficient represents the strength and direction of a linear relationship between two variables. Coefficients close to +1 or -1 indicate a strong linear association, while those near 0 suggest a weak association. The sign of the correlation indicates the direction of the relationship, either positive or negative.

The variable with the strongest linear association with the number of wins is 'runs allowed', which bears a correlation of -0.70. This implies a strong inverse relationship where as 'runs allowed' increase, the 'number of wins' tends to decrease.

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Answer:

336 different predictions.

1/336 probability of making the correct prediction by​ chance

Step-by-step explanation:

The order is important.

For example, Team A, B and C is a different outcome than team B, A, C.

So we use the permutations formula to solve this problem:

Permutations formula:

The number of possible permutations of x elements from a set of n elements is given by the following formula:

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

In this problem, we have that:

Permutations of 3 from a set of 8. So

[tex]P_{(8,3)} = \frac{8!}{(8-3)!} = 336[/tex]

What is the probability of making the correct prediction by​ chance?

There are 336 possible outcomes.

By chance, you predict 1.

So there is a 1/336 probability of making the correct prediction by​ chance

Final answer:

You can make 336 different predictions for the top 3 soccer teams out of 8, and the chance of making the correct prediction by chance is approximately 0.298%.

Explanation:

To calculate the number of different predictions you could make for the top 3 teams out of 8, without considering ties, you use permutations since the order matters. The formula for permutations is P(n, r) = n! / (n-r)!, where n is the total number of teams and r is the number of positions to fill.

In this case, n = 8 teams and r = 3 positions. Therefore, the calculation is P(8, 3) = 8! / (8-3)! = 8 x 7 x 6 = 336 different predictions.

To find the probability of making the correct prediction by chance, since there is only one correct prediction out of all possible predictions, the probability is 1 / 336. Thus, the probability is approximately 0.00298, or 0.298%.

Answer:

The question is incomplete as some details are missing; Here is the complete question; If vector u = 3i and v = 4i + 4j, Find the measure of the angle θ between u and v. Express the answer in radians rounded to two decimal places, if it is not possible to express it exactly.

The measure of the angle θ between u and v = 0.785radians

Step-by-step explanation:

The detailed steps is as shown in the attachment.

Answer:

The number of different lab groups possible is 84.

Step-by-step explanation:

Given:

A class consists of 5 engineers and 4 non-engineers.

A lab groups of 3 are to be formed of these 9 students.

The problem can be solved using combinations.

Combinations is the number of ways to select k items from a group of n items without replacement. The order of the arrangement does not matter in combinations.

The combination of k items from n items is: [tex]{n\choose k}=\frac{n!}{k!(n-k)!}[/tex]

Compute the number of different lab groups possible as follows:

The number of ways of selecting 3 students from 9 is = [tex]{n\choose k}={9\choose 3}[/tex]

                                                                                         [tex]=\frac{9!}{3!(9 - 3)!}\\=\frac{9!}{3!\times 6!}\\=\frac{362880}{6\times720}\\ =84[/tex]

Thus, the number of different lab groups possible is 84.

Answer:

The balance will be $2,731.82.

Step-by-step explanation:

This problem can be solved by the following formula:

[tex]A = P(1 + r)^{t}[/tex]

In which A is the final amount(balance), P is the principal(the deposit), r is the interest rate and t is the time, in years.

In this problem, we have that:

[tex]P = 2500, r = 0.03 t = 3[/tex]

We want to find A

So

[tex]A = P(1 + r)^{t}[/tex]

[tex]A = 2500(1 + 0.03)^{3}[/tex]

[tex]A = 2,731.82[/tex]

The balance will be $2,731.82.

Answer:

2731.8

Step-by-step explanation:

2500 deposited at 3 percent interest annually equation form

2500(1+(3/100))

for 3 years power the bract by 3

2500(1+(3/100))^3=2731.81

aka 2732

The exact solution to given differential equation is y(x) = Ce^(x^2/2). Using Euler's method with step size of 0.2, the solution approximates to 1.696 at x = 1.4; while the exact solution gives y(1.4) ~= 7.63.

The differential equation given is of the form dy/dx = x*y. The exact solution to this equation can be found using the method of separation of variables. Integrating both sides, we get y(x) = Ce^(x^2/2) where C is the integration constant. Given that y(0.2) = 7, we can find C = 7*exp(-0.02).

Moving on to Euler's method, the next stage can be found via the algorithm x(n+1) = x(n) + h and y(n+1) = y(n) + h*f(x(n), y(n)). The function f(x,y) = x / y is provided. Completing the table for x = 1, y can be calculated as y(1) = y(0.8) + h*f(0.8, y(0.8)) = 1.22814 + 0.2(0.8/1.22814) = 1.3924. Following the same steps until x = 1.4 gives y(1.4) ~= 1.696.

In part 2), with x = 1.4 in the exact solution we found earlier, y(1.4) = 7*exp(-0.02) * exp(1.4^2/2) ~= 7.63.

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Answer:

0.0369 = 3.69% probability that all six cells of the selected cells are able to replicate.

Step-by-step explanation:

A probability is the number of desired outcomes divided by the number of total outcomes

The combinations formula is important in this problem:

[tex]C_{n,x}[/tex] is the number of different combinations of x objects from a set of n elements, given by the following formula.

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

Desired outcomes

31 cells

19 are able to replicate.

We pick six.

The order is not important, that is, if it had been 2 cells, cell A and cell B would be the same outcome as cell B and cell A. So we use the combinations formula to find the number of desired outcomes.

It is a combination of 6 from 19(cells who are able to replicate).

[tex]D = C_{19,6} = \frac{19!}{6!(19 - 6)!} = 27132[/tex]

Total outcomes

31 cells

6 are picked.

[tex]T = C_{31,6} = \frac{31!}{6!(31 - 6)!} = 736281[/tex]

What is the probability that all six cells of the selected cells are able to replicate?

[tex]P = \frac{D}{T} = \frac{27132}{736281} = 0.0369[/tex]

0.0369 = 3.69% probability that all six cells of the selected cells are able to replicate.

Answer:

The answer would be 98.8

Step-by-step explanation:

Resin being you must round simply to the nearest hundreds

Answer:

a) [tex] T(t) = \frac{<-5 sin(5t), 5cos(5t)>}{5}= <-sin(5t), cos(5t)>[/tex]

[tex] T(4) = <-sin(20), cos(20)>[/tex]

b) [tex] T(t) = \frac{<t^2, 3t^2>}{8\sqrt{37}}[/tex]

[tex] T(4) = <\frac{2\sqrt{37}}{37},\frac{6\sqrt{37}}{37} >[/tex]

c) [tex] T(t) = \frac{<5e^{5t}, -4e^{-4t}, 1>}{2425825977}[/tex]

[tex] T(4) = \frac{1}{2425825977}<5e^{50}, -4e^{-16},1 >[/tex]

Step-by-step explanation:

The tangent vector is defined as:

[tex] T(t) = \frac{r'(t)}{|r'(t)|}[/tex]

Part a

For this case we have the following function given:

[tex] r(t) = <cos(5t), sin(5t)>[/tex]

The derivate is given by:

[tex] r'(t) = <-5 sin(5t), 5cos(5t)>[/tex]

The magnitude for the derivate is given by:

[tex] |r'(t)| = \sqrt{25 sin^2(5t) +25 cos^2 (5t)}= 5\sqrt{cos^2 (5t) + sin^2 (5t)} =5[/tex]

And then the tangent vector for this case would be:

[tex] T(t) = \frac{<-5 sin(5t), 5cos(5t)>}{5}= <-sin(5t), cos(5t)>[/tex]

And for the case when t=4 we got:

[tex] T(4) = <-sin(20), cos(20)>[/tex]

Part b

For this case we have the following function given:

[tex] r(t) = <t^2, t^3>[/tex]

The derivate is given by:

[tex] r'(t) = <2t, 3t^2>[/tex]

The magnitude for the derivate is given by:

[tex] |r'(t)| = \sqrt{4t^2 +9t^4}= t\sqrt{4 + 9t^2} [/tex]

[tex] |r'(4)| = \sqrt{4(4)^2 +9(4)^4}= 4\sqrt{4 + 9(4)^2} = 4\sqrt{148}= 8\sqrt{37}[/tex]

And then the tangent vector for this case would be:

[tex] T(t) = \frac{<t^2, 3t^2>}{8\sqrt{37}}[/tex]

And for the case when t=4 we got:

[tex] T(4) = <\frac{2\sqrt{37}}{37},\frac{6\sqrt{37}}{37} >[/tex]

Part c

For this case we have the following function given:

[tex] r(t) = <e^{5t}, e^{-4t} ,t>[/tex]

The derivate is given by:

[tex] r'(t) = <5e^{5t}, -4e^{-4t}, 1>[/tex]

The magnitude for the derivate is given by:

[tex] |r'(t)| = \sqrt{25e^{10t} +16e^{-8t} +1} [/tex]

[tex] |r'(t)| = \sqrt{25e^{10*4} +16e^{-8*4} +1} =2425825977 [/tex]

And then the tangent vector for this case would be:

[tex] T(t) = \frac{<5e^{5t}, -4e^{-4t}, 1>}{2425825977}[/tex]

And for the case when t=4 we got:

[tex] T(4) = \frac{1}{2425825977}<5e^{50}, -4e^{-16},1 >[/tex]

To compute the unit tangent vector T(t) for the given position vector r(t) at a given value t, take the derivative of r(t) with respect to t and divide the resulting vector by its magnitude.

To compute the unit tangent vector T(t) for the given position vector r(t) at a given value t, we need to take the derivative of r(t) with respect to t and then divide the resulting vector by its magnitude.

For part A, r(t) = (cos(5t), sin(5t)), so r'(t) = (-5sin(5t), 5cos(5t)). Plugging in t = -4, we get r'(-4) = (-5sin(-20), 5cos(-20)). To find T(-4), we divide r'(-4) by its magnitude.

T(-4) = (-5sin(-20)/sqrt((-5sin(-20))^2 + (5cos(-20))^2), 5cos(-20)/sqrt((-5sin(-20))^2 + (5cos(-20))^2)).

Answer:

a)

A={RRR,SSS,LLL}

b)

B={RSL,SLR,LRS,RLS,SRL,LSR}

c)

C={RRL,RLR,LRR,RRS,SRR,RSR}

d)

D={RRL, RRS, RLR, RLL, RSR, RSS, LRR, LRL, LLR, LLS, LSL, LSS, SRR, SRS, SLL, SLS, SSR, SSL}

e)

D'={RRR, RLS, RSL, LRS, LLL, LSR, SRL, SLR, SSS}

Step-by-step explanation:

Sample space=S= {RRR, RRL, RRS, RLR, RLL, RLS, RSR, RSL, RSS, LRR, LRL, LRS, LLR, LLL, LLS, LSR, LSL, LSS, SRR, SRL, SRS, SLR, SLL, SLS, SSR, SSL, SSS}

a)

Let A be the event that all three vehicles go in same direction. It means that the all three vehicles go to right or left or straight. Thus, event A can be represented as

A={RRR,SSS,LLL}

b)

Let B be the event that all three vehicles go in different direction. It means that the three vehicles can go to

1. Right, Straight, Left

2. Straight, Left, Right

3. Left, Right, Straight

4. Right, Left, Straight

5. Straight, Right, Left

6.  Left, Straight, Right

Thus, event B can be represented as

B={RSL,SLR,LRS,RLS,SRL,LSR}

c)

Let C be the event that exactly two of three vehicles turn right. It means that the three vehicles can go to

1. Right, Right , Left

2. Right , Left, Right

3. Left, Right, Right

4. Right, Right , Straight

5. Straight, Right,Right

6.  Right , Straight, Right

Thus, event C can be represented as

C={RRL,RLR,LRR,RRS,SRR,RSR}

d)

Let D be the event that exactly two of three vehicles go in same direction. It means that the three vehicles can go to

1. Right,  Right, Left

2. Right, Right, Straight

3. Right, Left,  Right

4. Right, Left, Left

5. Right, Straight, Right

6. Right, Straight, Straight

7.  Left,  Right, Right

8. Left,  Right, Left

9. Left, Left, Right

10. Left, Left, Straight

11. Left, Straight, Left

12. Left, Straight, Straight

13. Straight, Right, Right

14. Straight, Right, Straight

15. Straight, Left, Left

16. Straight, Left, Straight

17. Straight, Straight, Right

18.Straight,Straight, Left

Thus, event D can be represented as

D={RRL, RRS, RLR, RLL, RSR, RSS, LRR, LRL, LLR, LLS, LSL, LSS, SRR, SRS, SLL, SLS, SSR, SSL}

e)

D'=S-D= {RRR, RRL, RRS, RLR, RLL, RLS, RSR, RSL, RSS, LRR, LRL, LRS, LLR, LLL, LLS, LSR, LSL, LSS, SRR, SRL, SRS, SLR, SLL, SLS, SSR, SSL, SSS} -{RRL, RRS, RLR, RLL, RSR, RSS, LRR, LRL, LLR, LLS, LSL, LSS, SRR, SRS, SLL, SLS, SSR, SSL}

D'={RRR, RLS, RSL, LRS, LLL, LSR, SRL, SLR, SSS}

Final answer:

For a freeway exit where vehicles can go right, left, or straight, we determine the combination of directions for various events: Event A with all vehicles going the same direction has 3 outcomes; Event B with all vehicles taking different directions has 6 outcomes; Event C with two vehicles turning right has 6 outcomes; Event D with two vehicles going in the same direction has several outcomes depending on combinations; Event D' coincides with Event B.

Explanation:

When analyzing the outcomes of three successive vehicles taking different actions at a freeway exit, we can approach the given scenarios methodically:

To further explain, for (a), since there are three options for direction and all must be the same, we have exactly three outcomes when they are all identical. For (b), all vehicles must take a unique direction, and since there are three vehicles and three directions, we have 3! (factorial) permutations of the outcome, resulting in 6 possibilities. For (c), two vehicles must turn right and the third vehicle must take either of the two remaining directions, which can be arranged in 3 choose 2 (3C2 = 3) ways for each of the two non-right directions, making 6 outcomes total. For (d), it's similar to (c), but we include all same-direction pairs, resulting in 3C2 combinations for each pair of directions. Lastly, (e) is simply the case where no two outcomes are the same, hence it is the same as (b).

Answer:

a. Exercise is a suppressor.

Step-by-step explanation:

A variable that diminishes the effect of another variable on the outcome is known as a suppressor. In this particular experiment, when exercise is introduced, it was observed that when exercise was introduced, there was a decrease on the effect of sugar intake on weight. Therefore, exercise is a suppressor.

Answer:

0.19

Step-by-step explanation:

The are three candidate running for president and we know that probability of winning for first candidate and the probability of winning for second candidate and we have to find the probability of winning for third candidate

P(C1)=0.37

P(C2)=0.44

P(C3)=?

We know that sum of probabilities is always 1. So,

P(C1)+P(C2)+P(C3)=1

0.37+0.44+P(C3)=1

P(C3)=1-0.37-0.44

P(C3)=0.19

Thus, the probability of winning for third candidate is 0.19.

Answer:

The correct option is d i.e. scatter plot

Step-by-step explanation:

The correct option is d i.e. scatter plot

scatter plot will be the best option to display the variation of expenditure with respect to annual income.

on one axis annual income is used and on the other expenditure of the family. hence for a particular change in annual income, an impact on expenditure will easily be predicted.

A scatterplot would be a meaningful graphical display for studying the relationship between annual income and entertainment spending.

A meaningful graphical display of the relationship between the annual income of a family and the amount of money the family spends on entertainment would be a scatterplot.

A scatterplot shows the relationship between two variables by plotting each data point as a dot on a graph. In this case, the x-axis would represent the annual income and the y-axis would represent the amount spent on entertainment. Each dot on the scatterplot would represent a family and its corresponding values for income and entertainment spending.

By examining the scatterplot, it can be determined whether there is a correlation between income and entertainment spending. For example, if most dots are clustered around a certain line or pattern, it suggests a relationship between the two variables.

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Answer:

Option 4) Type I error is convicting an innocent person.

Step-by-step explanation:

We are given the following in the question:

[tex]H_{0}: \text{ Innocent}\\H_A: \text{ Guilty}[/tex]

Type II error:

Thus, with the given scenario type II error will be freeing a guilty person.

That is acquitting a guilty person.

Type I error:

Thus, with respect to given scenario type I error is convicting an innocent person.

Thus, the correct answer is:

Option 4) Type I error is convicting an innocent person.

Answer: 126 orderings

Step-by-step explanation:

Here let's suppose that total devices is given by n= 12

and defective ones are given by m= 4

Now, to find the number of orderings in which no two defective devices are consecutive is given by following relation.

¹²⁻⁴⁺¹₄C

= ⁹₄C

= 126 orderings

Answer:

B. stratification

Step-by-step explanation:

Stratification of data is a process in which data is agrupated into some groups or strats depending on its value.

This action is helpful when the person has a lot of data that can be clasified on several variables that will make their analysis easier to manage.

Answer:convenience sampling

Step-by-step explanation:

This is the type of sampling where the first available primary data source will be used without additional requirements.

Answer:

a) P=1/116280

b) P=143/38760

c) P=441/2584

Step-by-step explanation:

We have seven of these telephones are cellular, seven are cordless, and the other seven are corded phones.

a)  We calculate the number of possible combinations

{21}_C_{14}=\frac{21!}{14! · (21-14)!}=116280

The number of favorable combinations is 1.

Therefore, the probability is

P=1/116280

b) We calculate the number of possible combinations

{21}_C_{14}=\frac{21!}{14! · (21-14)!}=116280

We calculate  the number of favorable combinations  

{14}_C_{7}=\frac{14!}{7! · (14-7)!}=429

Therefore, the probability is

P=429/116280

P=143/38760

c) We calculate the number of possible combinations

{21}_C_{6}=\frac{21!}{6! · (21-6)!}=54264

We calculate  the number of favorable combinations  

{7}_C_{2} · {7}_C_{2} · {7}_C_{2} =

=\frac{7!}{2!·(7-2)!} · \frac{7!}{2!·(7-2)!}  · \frac{7!}{2!·(7-2)!}

=21 · 21 · 21=9261

Therefore, the probability is

P=9261/54264

P=441/2584

Answer:

a. 0.35197 or 35.20%; b. 0.1230 or 12.30%; c. 0.48784 or 48.78%; d. $250.20 or more.

Step-by-step explanation:

In general, we can solve this question using the standard normal distribution, whose values are valid for any normally distributed data, provided that they are previously transformed to z-scores. After having these z-scores, we can consult the table to finally obtain the probability associated with that value. Likewise, for a given probability, we can find, using the same table, the z-score associated to solve the value x of the equation for the formula of z-scores.

We know that the room rates are normally distributed with a population mean and a population standard deviation of (according to the cited source in the question):

[tex] \\ \mu = \$204[/tex] (population mean)

[tex] \\ \sigma = \$55[/tex] (population standard deviation)

A z-score is the needed value to consult the standard normal table. It is a transformation of the data so that we can consult this standard normal table to obtain the probabilities associated. The standard normal table has a mean  of 0 and a standard deviation of 1.

[tex] \\ z_{score}=\frac{x-\mu}{\sigma}[/tex]

After having all this information, we can proceed as follows:

1. We need to calculate the z-score associated with x = $225.

[tex] \\ z_{score}=\frac{225-204}{55}[/tex]

[tex] \\ z_{score}=0.381818[/tex]

[tex] \\ z_{score}=0.38[/tex]

We rounded the value to two decimals since the cumulative standard normal table (values for cumulative probabilities from negative infinity to the value x) to consult only have until two decimals for z values.

Then

2. For a z = 0.38, the corresponding probability is P(z<0.38) = 0.64803. But the question is asking for values greater than this value, then:

[tex] \\ P(z>038) = 1 - P(z<0.38)[/tex] (that is, the complement of the area)

[tex] \\ P(z>038) = 1 - 0.64803[/tex]

[tex] \\ P(z>038) = 0.35197[/tex]

So, the probability that a hotel room costs $225 or more per night is P(x>$225) = 0.35197 or 35.20%, approximately.

We follow a similar procedure as before, so:

[tex] \\ z_{score}=\frac{x-\mu}{\sigma}[/tex]

[tex] \\ z_{score}=\frac{140-204}{55}[/tex]

[tex] \\ z_{score}=\frac{140-204}{55}[/tex]

[tex] \\ z_{score}= -1.163636 \approx -1.16[/tex]

This value is below the mean (it has a negative sign). The standard normal tables does not have these values. However, we can find them subtracting the value of the probability obtained for z = 1.16 from 1, since the symmetry for normal distribution permits it. Then, the probability associated with z = -1.16 is:

[tex] \\ P(z<1.16) = 0.87698[/tex]

[tex] \\ P(z<-1.16) = 1 - 0.87698 [/tex]

[tex] \\ P(z<-1.16) = 0.12302 \approx 0.1230[/tex]

Then, the probability that a hotel room costs less than $140 per night is P(x<$140) = 0.1230 or 12.30%.

[tex] \\ z_{score}=\frac{x-\mu}{\sigma}[/tex]

The z-score and probability for x = $200:

[tex] \\ z_{score}=\frac{200-204}{55}[/tex]

[tex] \\ z_{score}= -0.072727 \approx -0.07[/tex]

[tex] \\ P(z<0.07) = 0.52790[/tex]

[tex] \\ P(z<-0.07) = 1 - 0.52790 [/tex]

[tex] \\ P(z<-0.07) = 0.47210 \approx 0.4721[/tex]

The z-score and probability for x = $300:

[tex] \\ z_{score}=\frac{300-204}{55}[/tex]

[tex] \\ z_{score}=1.745454[/tex]

[tex] \\ P(z<1.75) = 0.95994[/tex]

[tex] \\ P(z<1.75) - P(z<-0.07) = 0.95994-0.47210 [/tex]

[tex] \\ P(z<1.75) - P(z<-0.07) = 0.48784 [/tex]

Then, the probability that a hotel room costs between $200 and $300 per night is 0.48784 or 48.78%.

A way to solve this is as follows: we need to consult, using the cumulative standard normal table, the value for z such as the probability is 80%. This value is, approximately, z = 0.84. Then, solving the next equation for x:

[tex] \\ z_{score}=\frac{x-\mu}{\sigma}[/tex]

[tex] \\ 0.84=\frac{x-204}{55}[/tex]

[tex] \\ 0.84*55=x-204[/tex]

[tex] \\ 0.84*55 + 204 =x[/tex]

[tex] \\ x = 250.2[/tex]

That is, the cost of the most expensive 20% of hotel rooms in New York City are of $250.20 or more.

This answer uses the normal distribution to calculate probabilities and thresholds in hotel room rates. The main steps are to convert room rates to z-scores, look up probabilities or percentiles in the standard normal distribution, and convert back to room rates if necessary.

To answer these questions, we can use the properties of the normal distribution. First, we convert the given hotel room rate to a z-score by subtracting the mean and dividing by the standard deviation. Then we can look up these z-scores in a standard normal distribution table (or use a calculator with a normal distribution function) to get probabilities.

a. To find the probability that a hotel room costs $225 or more per night, we convert $225 to a z-score: z = ($225-$204)/$55 = 0.38. The probability of getting a z-score of 0.38 or more (which means a cost of $225 or more) is 0.3520. So the probability that a room costs $225 or more per night is 0.3520 or 35.20%.

b. To find the probability that a hotel room costs less than $140 per night, we convert $140 to a z-score: z = ($140-$204)/$55 = -1.16. The probability of getting a z-score of -1.16 or less (which means a cost of $140 or less) is 0.1230. So the probability that a room costs $140 or less per night is 0.1230 or 12.30%.

c. To find the probability that a hotel room costs between $200 and $300 per night, we convert $200 to a z-score (z1 = -0.073) and $300 to a z-score (z2 = 1.745). We then subtract the probabilities: P($200 < Rate < $300) = P(z1 < Z < z2) = P(Z < z2) - P(Z < z1) = 0.9591 - 0.4713 = 0.4878. So the probability that a room costs between $200 and $300 per night is 0.4878 or 48.78%.

d. To find the cost of the most expensive 20% of hotel rooms in New York City, we look for the z-score corresponding to the 80th percentile (because everything above this point is the top 20%). This z-score is 0.84. We then convert this z-score back to a cost using the mean and standard deviation: Cost = Mean + z*SD = $204 + 0.84*$55 = $250.20. So the cost of the most expensive 20% of hotel rooms in New York City is $250.20 per night.

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Answer:

(a) 0.56

(b) 0.06

(c) 0.94

Step-by-step explanation:

P(E1) = 0.7 and P(E2) = 0.8

(a) The probability that both bids are successful is given by the product of the probability of success of each bid:

[tex]P(E1\ and\ E2) = 0.7*0.8=0.56[/tex]

(b) The probability that neither bid is successful is given by the product of the probability of failure of each bid:

[tex]P(not\ E1\ and\ not\ E2)= (1-P(E1))*(1-P(E2))\\P(not\ E1\ and\ not\ E2)=0.3*0.2=0.06[/tex]

(c) The probability that the firm is successful in at least one of the two bids is given by the sum of the probability of success of each bid subtracted by the probability that both bids are successful:

[tex]P(E1\ or\ E2)=P(E1)+P(E2) - P(E1\ and\ E2)\\P(E1\ or\ E2)=0.7+0.8-0.56\\P(E1\ or\ E2)=0.94[/tex]

Using probability concepts, it is found that there is a:

a) 0.56 = 56% probability that both bids are successful.

b) 0.06 = 6% probability that neither bid is successful.

c) 0.94 = 94% probability that the firm is successful in at least one of the two bids.

Item a:

These two events are independent, hence, the probability of both is the multiplication of the probabilities of each, thus:

[tex]p = 0.7(0.8) = 0.56[/tex]

0.56 = 56% probability that both bids are successful.

Item b:

E1 has a 1 - 0.7 = 0.3 probability of being unsuccessful, while E2 has a 0.2 probability, hence:

[tex]p = 0.3(0.2) = 0.06[/tex]

0.06 = 6% probability that neither bid is successful.

Item c:

1 - 0.06 = 0.94

0.94 = 94% probability that the firm is successful in at least one of the two bids.

A similar problem is given at https://brainly.com/question/23855473

Answer:

0.74141

Step-by-step explanation:

There are 52 cards in total

since each card is different,

the probability = number of favorable cards / total number of outcomes

P(C₁) = number of favorable cards / total number of outcomes

     = [tex]\frac{52}{52}[/tex]

P(C₂, C₁) = number of favorable cards / total number of outcomes

   = [tex]\frac{51}{52}[/tex]

P(C₃,C₁ ∩ C₂) = [tex]\frac{50}{52}[/tex]

P(C₄,C₁ ∩ C₂ ∩ C₃) = [tex]\frac{49}{52}[/tex]

P(C₅,C₁ ∩ C₂ ∩ C₃ ∩ C₄) = [tex]\frac{48}{52}[/tex]

P(C₆,C₁ ∩ C₂ ∩ C₃ ∩ C₄ ∩ C₅) = [tex]\frac{47}{52}[/tex]

General multiplication rule

P(A) =P(C₁ ∩ C₂ ∩ C₃ ∩ C₄ ∩ C₅ ∩ C₆)

         = [tex]\frac{52}{52}. \frac{51}{52}. \frac{50}{52}. \frac{49}{52}. \frac{48}{52} .\frac{47}{52}[/tex]

         = 8,808,975 / 11,881,376

         = 0.74141

Answer:

Quota sampling

Step-by-step explanation:

Quota sampling is a type of sampling method in which a representative data is collected from a group. It is a non probability based sampling method, a type of stratified sampling. Quota sampling is required when researchers are working with limited time and are without a sampling frame. Quota sampling method helps to determine the characteristics of a subgroup under research. It is an highly accurate method of sampling.

Answer:

b. False

See explanation below

Step-by-step explanation:

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.

And in order to calculate the correlation coefficient we can use this formula:  

[tex]r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}[/tex]  

For this case we know that r =0.87. But we can't conclude that the linear correlation coefficient represent a cause-effect relationship, since the linear correlation coefficient measures the linear dependency between two variables, but we can have other types of association between the variables and that's not measured by the Pearson correlation coeffcient.

So for this case the answer woudl be

b. False

Final answer:

The claim that a correlation of 0.87 between time in prison and aggression implies causation is false because correlation does not equal causation. There may be other factors influencing aggression, and the correlation observed might be spurious.

Explanation:

The statement that a correlation of 0.87 between the length of time a person is in prison and the amount of aggression displayed means that spending a longer time in prison causes people to become more aggressive is false.

Correlation does not imply causation. Just because two variables are correlated does not mean that one variable causes the change in the other. There could be other factors or variables that contribute to the aggression, which are not accounted for in simply observing the correlation.

Negative experiences do increase aggression, as people are more prone to aggress when experiencing negative emotions such as frustration, pain, or being in a bad mood. In a prison context, the aggression could also stem from the social structure of prison life and not merely the length of time served.

The Stanford prison experiment by Philip Zimbardo is a notable study highlighting how quickly people can turn to aggressive behaviors based on the roles they are assigned within a prison environment.

Answer:

a) 0.5

b) 0.309

Step-by-step explanation:

We are given the following information in the question:

Mean, μ = 70 inches

Standard Deviation, σ = 4 inches

Formula:

[tex]z_{score} = \displaystyle\frac{x-\mu}{\sigma}[/tex]

Height of George Washington = 6 feet = [tex]6\times 12 = 72\text{ inches}[/tex]

x = 72

a) z-score

[tex]z_{score} = \displaystyle\frac{72-70}{4} = 0.5[/tex]

Interpretation:

This, mean that George Washington is 0.5 standard deviation more than the mean height of for men.

b) P(individual will be as tall or taller than George Washington)

[tex]P( x \geq 72) = P( z \geq 0.5)[/tex]

[tex]= 1 - P(z < 0.5)[/tex]

Calculation the value from standard normal z table, we have,  

[tex]P(x \geq 72) = 1 - 0.691 = 0.309 = 30.9\%[/tex]

Interpretation:

0.309 is the probability  that a randomly selected individual will be as tall or taller than George Washington.

Answer:

[tex]4 - 2.14 \frac{0.7}{\sqrt{15}}=3.61[/tex]

[tex]4 + 2.14 \frac{0.7}{\sqrt{15}}=4.39[/tex]

The 95% confidence interval is given by (3.61;4.39)

Step-by-step explanation:

Notation and definitions

n=15 represent the sample size

[tex]\bar X=4[/tex] represent the sample mean  

[tex]s=0.7[/tex] represent the sample standard deviation

m represent the margin of error

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".  

The margin of error is the range of values below and above the sample statistic in a confidence interval.  

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".  

Calculate the critical value tc

In order to find the critical value is important to mention that we don't know about the population standard deviation, so on this case we need to use the t distribution. Since our interval is at 95% of confidence, our significance level would be given by [tex]\alpha=1-0.95=0.05[/tex] and [tex]\alpha/2 =0.025[/tex]. The degrees of freedom are given by:  

[tex]df=n-1=15-1=14[/tex]  

We can find the critical values in excel using the following formulas:  

"=T.INV(0.025,14)" for [tex]t_{\alpha/2}=-2.14[/tex]  

"=T.INV(1-0.025,14)" for [tex]t_{1-\alpha/2}=2.14[/tex]  

The critical value [tex]tc=\pm 2.14[/tex]

Calculate the margin of error (m)

The margin of error for the sample mean is given by this formula:

[tex]m=t_c \frac{s}{\sqrt{n}}[/tex]

[tex]m=2.14 \frac{0.7}{\sqrt{15}}=0.387[/tex]

Calculate the confidence interval  

The interval for the mean is given by this formula:

[tex]\bar X \pm t_{c} \frac{s}{\sqrt{n}}[/tex]

And calculating the limits we got:

[tex]4 - 2.14 \frac{0.7}{\sqrt{15}}=3.61[/tex]

[tex]4 + 2.14 \frac{0.7}{\sqrt{15}}=4.39[/tex]

The 95% confidence interval is given by (3.61;4.39)

The vector represented by the directed line segment with initial point A(1, −4, 1) and terminal point B(−2, 5, 4) is (-3, 9, 3).

To find the vector represented by the directed line segment with initial point A(1, −4, 1) and terminal point B(−2, 5, 4), we subtract the coordinates of A from the coordinates of B. Subtraction of vectors is equivalent to adding a negative vector, so we have:

AB = B - A = (-2 - 1, 5 - (-4), 4 - 1) = (-3, 9, 3)

The vector AB is represented as (-3, 9, 3).

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a) The values of a, b and c are [tex]\frac{173}{4}, 41[/tex] and [tex]1547[/tex] respectively.

b) The number of craft beer breweries in 2016 will be 4643.

The quadratic equation holds an important significance in mathematics and is used in many situations, like calculating area or finding profit. When two linear expressions get multiplied, the resultant expression is a quadratic expression.

The number of craft beer breweries is modeled by a quadratic equation [tex]f(t)=at^2+bt+c[/tex].

In 2008, t=0.

a) Here, it is given that [tex]f(0)=1547[/tex], [tex]f(2)=1802[/tex] and [tex]f(4)=2403[/tex].

Now, use these values to find a, b and c as follows:

[tex]f(0)=a(0)^2+b(0)+c[/tex]

[tex]1547=c[/tex]

[tex]f(2)=a(2)^2+2b+c[/tex]

[tex]1802=4a+2b+1547[/tex]

[tex]255=4a+2b[/tex]

[tex]f(4)=a(4)^2+b(4)+c[/tex]

[tex]2403=16a+4b+1547[/tex]

[tex]856=16a+4b[/tex]

[tex]214=4a+b[/tex]

Now, setting the equations [tex]4a+2b=255[/tex] and [tex]4a+b=214[/tex] equal to each other:

[tex]4a=255-2b[/tex]

[tex]4a=214-b[/tex]

[tex]255-2b=214-b[/tex]

[tex]b=255-214[/tex]

[tex]b=41[/tex]

Now plugging the value of b into the equation [tex]4a+b=214[/tex], we get

[tex]4a+b=214[/tex]

[tex]4a=214-b[/tex]

[tex]a=\frac{214-b}{4}[/tex]

[tex]a=\frac{214-41}{4}[/tex]

[tex]a=\frac{173}{4}[/tex]

So, we have [tex]a=\frac{173}{4}[/tex], [tex]b=41[/tex] and [tex]c=1547[/tex]

b) Using the values calculated in part (a), the quadratic equation becomes

[tex]f(t)=\frac{173}{4}t^2+41t+1547[/tex]

Now, in 2016, the value of t=8

So, the number of craft beer breweries in 2016 will be calculated by [tex]f(8)[/tex]:

[tex]f(8)=\frac{173}{4}(8)^2+41(8)+1547[/tex]

[tex]= 2768+328+1547[/tex]

[tex]= 4643[/tex]

Therefore, the number of craft beer breweries in 2016 will be 4643.

Learn more about the quadratic function here:

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We first find the constants by substituting in the provided points into the quadratic equation to create a series of equations. Solving them gives us a = 61.5, b = 47, and c = 1547. To predict the number of breweries in 2016, we substitute t = 8 into the function to get approximately 3455 breweries.

To find the constants a, b, and c, we will substitute the given points (0, 1547), (2, 1802), and (4, 2403) into the equation f(t) = at² + bt + c. This will give us three equations:

Solving these gives us a = 61.5, b = 47, and c = 1547. Therefore the quadratic function is: f(t) = 61.5t² + 47t + 1547.

For (b), we want to find the number of breweries in 2016, which is 8 years from 2008. Substituting t = 8 into our quadratic function gives us f(8) = 61.5(8²) + 47(8) + 1547 which is approximately 3455. So, the model estimates there will be around 3455 craft-beer breweries in 2016.

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