A regular square pyramid has a height of 6 and a base with sides of length 12. What is the: Lateral area of the pyramid?

Answer:

x = 368     production of country A (millions of (MT)

y = 215      production of country B (millions of (MT)

z =  93       production of country C (millions of (MT)

Step-by-step explanation:

Let call production as follows

Country A   production  x   millions on MT

Country B   production  y   millions on MT

Country C   production  z   millions on MT

Then according to problem statement

x  +  y  +  z   =  676        (1)

x = 60 +  y  + z

y = 122 + z

That system  ( 3 equations and three unknown varables ) could be solved by any of the available procedures.

By subtitution we get

x  =  60 + 122 + z + z     ⇒  x  =  182 + 2*z

And      

182 +  2*z  + 122 + z + z = 676

Solving for z

304  +  4*z  =  676     ⇒   4*z  =  676 - 304   ⇒   4*z  =  372

z  =  372/4       ⇒     z  =  93  millions of  (MT)

And

y  =  122 + z       ⇒  y  =  122 + 93       ⇒  y = 215  millions of (MT)

x  =  182  + 2*z    ⇒  x  =  182  + 2 ( 93)   ⇒ x  =  182 + 186

x = 368  millions of (MT)

We can cheked in equation 1

x = 368

y = 215

z =  93

Give a total of 676 millions of (MT)

Answer:

(a) There are 70 different ways set up 4 computers out of 8.

(b) The probability that exactly three of the selected computers are desktops is 0.305.

(c) The probability that at least three of the selected computers are desktops is 0.401.

Step-by-step explanation:

Of the 9 new computers 4 are laptops and 5 are desktop.

Let X = a laptop is selected and Y = a desktop is selected.

The probability of selecting a laptop is = [tex]P(Laptop) = p_{X} = \frac{4}{9}[/tex]

The probability of selecting a desktop is = [tex]P(Desktop) = p_{Y} = \frac{5}{9}[/tex]

Then both X and Y follows Binomial distribution.

[tex]X\sim Bin(9, \frac{4}{9})\\ Y\sim Bin(9, \frac{5}{9})[/tex]

The probability function of a binomial distribution is:

[tex]P(U=k)={n\choose k}\times(p)^{k}\times (1-p)^{n-k}[/tex]

(a)

Combination is used to determine the number of ways to select k objects from n distinct objects without replacement.

It is denotes as: [tex]{n\choose k}=\frac{n!}{k!(n-k)!}[/tex]

In this case 4 computers are to selected of 8 to be set up. Since there cannot be replacement, i.e. we cannot set up one computer twice or thrice, use combinations to determine the number of ways to set up 4 computers of 8.

The number of ways to set up 4 computers of 8 is:

[tex]{8\choose 4}=\frac{8!}{4!(8-4)!}\\=\frac{8!}{4!\times 4!} \\=70[/tex]

Thus, there are 70 different ways set up 4 computers out of 8.

(b)

It is provided that 4 computers are randomly selected.

Compute the probability that exactly 3 of the 4 computers selected are desktops as follows:

[tex]P(Y=3)={4\choose 3}\times(\frac{5}{9})^{3}\times (1-\frac{5}{9})^{4-3}\\=4\times\frac{125}{729}\times\frac{4}{9}\\ =0.304832\\\approx0.305[/tex]

Thus, the probability that exactly three of the selected computers are desktops is 0.305.

(c)

Compute the probability that of the 4 computers selected at least 3 are desktops as follows:

[tex]P(Y\geq 3)=1-P(Y<3)\\=1-[P(Y=0)+P(Y=1)+P(Y=2)]\\=1-[({4\choose 0}\times(\frac{5}{9} )^{0}\times (1-\frac{5}{9} )^{4-0}+({4\choose 1}\times(\frac{5}{9} )^{1}\times (1-\frac{5}{9} )^{4-1}+({4\choose 2}\times(\frac{5}{9} )^{2}\times (1-\frac{5}{9} )^{4-2}]\\=1-0.59918\\=0.40082\\\approx0.401[/tex]

Thus, the probability that at least three of the selected computers are desktops is 0.401.

To Plotting lines , use the PFloor line tool and click your mouse for the first and second end-points, ensuring that the line intersects both the D1 and S1 lines and has a height greater than 50.

To plot the line described in the question, follow these steps:

Select the line tool on the tool palette labeled PFloor.

Click your mouse for the first end-point on the vertical axis.

Move your mouse to the right and click again for the second end-point.

The new line should intersect both the D1 and S1 lines and have a height greater than 50 on the vertical axis.

Learn more about Plotting lines here:

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Answer:

Kelly will owe $1320.92 to the fabulous fence company.

Step-by-step explanation:

There is a cost related to the number of hours and a cost per feet. So the total cost is:

[tex]T = C_{h} + C_{f}[/tex]

In which [tex]C_{h}[/tex] is the cost related to the number of hours and [tex]C_{f}[/tex] is the cost related to the number of feet.

Cost per hour

Each hour costs $15.57.

They work for 6 hours total. So

[tex]C_{h} = 15.57*6 = 93.42[/tex]

Cost per feet

Each feet costs $3.25.

Kelly needs 350 feet. So

[tex]C_{f} = 350*3.25 = 1137.5[/tex]

The total cost is:

[tex]T = C_{h} + C_{f} = 93.42 + 1137.5 = 1230.92[/tex]

Kelly will owe $1320.92 to the fabulous fence company.

Answer:

a) And if we replace we got: [tex]\bar X= 78[/tex]

[tex] s = 15.391[/tex]

b) [tex]78-3.25\frac{15.391}{\sqrt{10}}=62.182[/tex]    

[tex]78-3.25\frac{15.391}{\sqrt{10}}=93.818[/tex]    

So on this case the 99% confidence interval would be given by (62.182;93.818)    

Step-by-step explanation:

Dataset given: 109 67 58 76 65 80 96 86 71 72

Part a

For this case we can calculate the sample mean with the following formula:

[tex]\bar X = \frac{\sum_{i=1}^n X_i}{n}[/tex]

And if we replace we got: [tex]\bar X= 78[/tex]

And the deviation is given by:

[tex] s =\sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}}[/tex]

And if we replace we got [tex] s = 15.391[/tex]

Part b

The confidence interval for the mean is given by the following formula:

[tex]\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]   (1)

In order to calculate the critical value [tex]t_{\alpha/2}[/tex] we need to find first the degrees of freedom, given by:

[tex]df=n-1=10-1=9[/tex]

Since the Confidence is 0.99 or 99%, the value of [tex]\alpha=0.01[/tex] and [tex]\alpha/2 =0.005[/tex], and we can use excel, a calculator or a table to find the critical value. The excel command would be: "=-T.INV(0.005,9)".And we see that [tex]t_{\alpha/2}=3.25[/tex]

Now we have everything in order to replace into formula (1):

[tex]78-3.25\frac{15.391}{\sqrt{10}}=62.182[/tex]    

[tex]78-3.25\frac{15.391}{\sqrt{10}}=93.818[/tex]    

So on this case the 99% confidence interval would be given by (62.182;93.818)    

Answer:

The variance of given sample is 33.64 square pounds.

Step-by-step explanation:

We are given the following in the question:

Sample size, n = 16

Standard deviation, s = 5.8 pounds

We have to find the variance of the given sample.

Variance is the square of the standard deviation.

[tex]\text{Variance} = (\text{Standard Deviation})^2\\= (5.8\text{ pounds})^2\\=33.64\text{ pound}^2[/tex]

Thus, the variance of given sample is 33.64 square pounds.

Answer:

Null hypothesis:[tex]p=0.114[/tex]  

Alternative hypothesis:[tex]p \neq 0.114[/tex]  

[tex]z=\frac{0.152 -0.114}{\sqrt{\frac{0.114(1-0.114)}{850}}}=3.49[/tex]  

Since is a bilateral test the p value would be:  

[tex]p_v =2*P(z>3.49)=0.00049[/tex]  

So the p value obtained was a very low value and using the significance level given [tex]\alpha=0.05[/tex] we have [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis.

[tex]0.152 - 1.96 \sqrt{\frac{0.152(1-0.152)}{850}}=0.128[/tex]

[tex]0.152 - 1.96 \sqrt{\frac{0.152(1-0.152)}{850}}=0.176[/tex]

And the 95% confidence interval would be given (0.128;0.176).

And support the conclusion obtained on the hypothesis test since the value of 0.114 is not in the confidence interval, so we have enough evidence to reject the null hypothesis.

Step-by-step explanation:

Data given and notation

n=850 represent the random sample taken

X=129 represent the number of housing units that are vacant.

[tex]\hat p=\frac{129}{850}=0.152[/tex] estimated proportion of housing units that are vacant.

[tex]p_o=0.114[/tex] is the value that we want to test

[tex]\alpha=0.05[/tex] represent the significance level

Confidence=95% or 0.95

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 proportion is equal is 0.114 or not:  

Null hypothesis:[tex]p=0.114[/tex]  

Alternative hypothesis:[tex]p \neq 0.114[/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{0.152 -0.114}{\sqrt{\frac{0.114(1-0.114)}{850}}}=3.49[/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 assumed is [tex]\alpha=0.05[/tex]. The next step would be calculate the p value for this test.  

Since is a bilateral test the p value would be:  

[tex]p_v =2*P(z>3.49)=0.00049[/tex]  

So the p value obtained was a very low value and using the significance level given [tex]\alpha=0.05[/tex] we have [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis.

Confidence interval

The confidence interval would be given by this formula

[tex]\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}[/tex]

For the 95% confidence interval the value of [tex]\alpha=1-0.95=0.05[/tex] and [tex]\alpha/2=0.025[/tex], with that value we can find the quantile required for the interval in the normal standard distribution.

[tex]z_{\alpha/2}=1.96[/tex]

And replacing into the confidence interval formula we got:

[tex]0.152 - 1.96 \sqrt{\frac{0.152(1-0.152)}{850}}=0.128[/tex]

[tex]0.152 - 1.96 \sqrt{\frac{0.152(1-0.152)}{850}}=0.176[/tex]

And the 95% confidence interval would be given (0.128;0.176).

And support the conclusion obtained on the hypothesis test since the value of 0.114 is not in the confidence interval, so we have enough evidence to reject the null hypothesis.

We first set the null and alternative hypothesis and then conduct a z-test for proportions to calculate the z-score and subsequently the p-value. We use the p-value to decide whether to reject the null hypothesis. Finally, we construct a 95% confidence interval for the true proportion of vacant houses and check if this supports our test conclusion.

Firstly, define the proportion of vacant housing units in the country as p0 and in the randomly selected county as p. The null hypothesis (H0) states that the county isn't different, so H0: p = p0 = 0.114. The alternative hypothesis (Ha) would be that the county is different, so Ha: p ≠ 0.114.

Let's conduct a Test of Hypothesis using a z-test for proportions. The z-score is calculated as (p - p0) / sqrt((p0 * (1 - p0)) / n), where n represents the sample size. Substituting in your values, the z score will be calculated. This z-score can be used to find the p-value from a standard normal (Z) distribution table.

If the p-value is less than 0.05 (which is α, significance level), we reject the null hypothesis in favor of alternative hypothesis, else we do not reject the null hypothesis. Thus, our conclusion is formulated based on this p-value.

To construct a 95% confidence interval for the true proportion of vacant houses, we use the formula: p ± Z * sqrt((p * (1 - p)) / n). Here, Z will be the Z score corresponding to the desired confidence level, 95% (which is 1.96 for two-tailed test).

If the national proportion (0.114) doesn't lie within this interval, it supports our test conclusion of rejecting the null hypothesis and vice versa.

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Using the Last Diminisher method, in the first round, Anne gets her fair share because no one diminishes. In the second round, Doris is the only one who diminishes, thus gets her fair share. In the third round, despite Cindy and Ellen both diminishing, Ellen gets her fair share because she is later in turn order.

The Last Diminisher method is a fair division protocol used when a divisible good, like a cake in this example, needs to be divided amongst several players. This method removes discrepancies by having each player in turn reduce the piece until they don't want to diminish it further, and then giving that piece to the last to diminish.

In this case, Anne, Betty, Cindy, Doris, and Ellen are dividing the cake and playing in that order. In the first round, no one diminishes, so Anne gets her fair share of the cake. In the second round, Doris is the only one who diminishes, so she gets her fair share at the end of this round. In the third round, the last to diminish are Cindy and Ellen, but since Ellen is later in order, Ellen is the one who gets her fair share at the end of the round.

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Answer:

2√6 ft

Step-by-step explanation:

Tan Ф = opposite/ adjacent

tan 60  = t / 2√2 ft

tan 60 = √3

t = (tan 60 )(2√2 ft)

t = (√3)(2√2 ft)  = 2√6 ft

Answer:

N = 6300 ways

She can choose the materials 6300 ways

Step-by-step explanation:

In this case order of selection is not important, so we use combination.

For solids,

She needs 2 out of 9 available solids = 9C2

For striped prints

She needs 4 out of 7 available = 7C4

For floral prints

She needs 4 out of 5 available = 5C4

The total number of ways she can choose the materials is;

N = 9C2 × 7C4 × 5C4

N = 9/(7!2!) × 7/(4!3!) × 5/(4!1!)

N = 6300 ways

To find the number of different ways Courtney can choose the materials for her quilt, we can use the concept of combinations. The total number of ways she can choose the materials is the product of the number of choices for each type of fabric.

To find the number of different ways Courtney can choose the materials for her quilt, we can use the concept of combinations. The total number of ways she can choose the materials is given by the product of the number of choices for each type of fabric. So, the answer is:

Total number of ways = number of ways to choose solids * number of ways to choose floral prints * number of ways to choose striped fabrics

Given that she needs 2 solids, 4 floral prints, and 4 striped fabrics, we can calculate:

Substituting these values into the formula:

Total number of ways = 36 * 5 * 35 = 6300

So, there are 6300 different ways Courtney can choose the materials for her quilt.

Answer:

ML = {bba, ab, a, bbaabb, ababb, aabb}

Step-by-step explanation:

By application of Union of a set.

M = {bba,ab, a}

L = {Λ,abb}

ML = {bba, ab, a, bbaabb, ababb, aabb}

Answer:

[tex]z=\frac{\bar d -0}{\frac{\sigma_d}{\sqrt{n}}}=\frac{-0.625 -0}{\frac{6.818}{\sqrt{8}}}=-0.259[/tex]

[tex]p_v =2*P(z<-0.259) =0.796[/tex]

So the p value is higher than the significance level given [tex]\alpha=0.01[/tex], then we can conclude that we FAIL to reject the null hypothesis that the difference mean between after and before is equal to 0. So we can conclude that we don't have significant differences between the two populations.

Step-by-step explanation:

Previous concepts  

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".  

Solution to the problem

Let's put some notation :

x=values popoulation 2 , y = values population 1

x: 64 69 83 60 66 84 60 81

y: 58 76 77 70 62 76 67 76

The system of hypothesis for this case are:

Null hypothesis: [tex]\mu_y- \mu_x = 0[/tex]

Alternative hypothesis: [tex]\mu_y -\mu_x \neq 0[/tex]

The first step is calculate the difference [tex]d_i=y_i-x_i[/tex] and we obtain this:

d: -6,7,-6,10,-4,-8, 7, -5

The second step is calculate the mean difference  

[tex]\bar d= \frac{\sum_{i=1}^n d_i}{n}= \frac{-5}{8}=-0.625[/tex]

The third step would be calculate the standard deviation for the differences, and we got:

[tex]\sigma_d =\frac{\sum_{i=1}^n (d_i -\bar d)^2}{n} =6.818[/tex]

The 4 step is calculate the statistic given by :

[tex]z=\frac{\bar d -0}{\frac{\sigma_d}{\sqrt{n}}}=\frac{-0.625 -0}{\frac{6.818}{\sqrt{8}}}=-0.259[/tex]

Now we can calculate the p value, since we have a two tailed test the p value is given by:

[tex]p_v =2*P(z<-0.259) =0.796[/tex]

So the p value is higher than the significance level given [tex]\alpha=0.01[/tex], then we can conclude that we FAIL to reject the null hypothesis that the difference mean between after and before is equal to 0. So we can conclude that we don't have significant differences between the two populations.

Answer:

Correct answer is option C i.e 28 minutes

Step-by-step explanation:

Number of students arriving at adviser's office per hour = x = 28

Number of students get approved = [tex]\frac{1}{2min}[/tex]  = 30/hour

    ∴ y = 30

Number of students on average on waiting =Lq

Lq = [tex]\frac{x^{2} }{y(y-x)}[/tex]

=  [tex]\frac{28^{2} }{30(30-28)}[/tex]

= 13.07

Average time student has to spend in

Waiting = Wq = [tex]\frac{x}{y(y-x)}[/tex]

= [tex]\frac{28}{30(30-28)}[/tex]

= 0.466 hours

= 28 minutes

Answer:

The question is incomplete, below is the complete question,"There are two traffic lights on Darlene's route from home to work. Let E denote the event that Darlene must stop at the first light, and define the event F in a similar manner for the second light. Suppose that P(E) = 0.2, P(F) = 0.3, and P(E ∩ F) = 0.13.

a) What is the probability that the individual needn't stop at either light?

b) What is the probability that the individual must stop at exactly one of the two lights? c) What is the probability that the individual must stop just at the first light?"

Answer:

A. 0.63

B. 0.24

C. 0.07

Step-by-step explanation:

Data given,

P(E) = 0.2, P(F) = 0.3, and P(E ∩ F) = 0.13.

From the question, we can conclude that the event are dependent, hence

a. P(needn't stop at either light) = 1 - P(Need to stop at either light)

P(EUF)' =1-P(EUF)

P(EUF)' =1- (P(E)+P(F) -P(E ∩ F))

P(EUF)' =1-(0.2+0.3-0.13)

P(EUF)' =1-0.37

P(EUF)' =0.63

b. P(must stop at exactly one of the two lights) = P(must stop at either light) - P(must stop at both lights)

P(must stop at exactly one of the two lights)  = P(E u F) - P(En F)

but P(E u F)=0.37,

P(En F)=0.13,

P(must stop at exactly one of the two lights) = 0.37 - 0.13 = 0.24

c. P(must stop at just the first light) = P(must stop at either light) - P(must stop at the second light)

P(must stop at just the first light) = P(E u F)-P(F)

P(must stop at just the first light) = 0.37 - 0.3 = 0.07

The question deals with the topic of Probability in Mathematics. It presents the probabilities of two events, denoted as E and F, which are stopping at the first and second traffic lights, respectively. The question also provides the concurrent occurrence of both events.

The mathematics topic this question deals with is Probability. In the scenario given, E represents the event that Darlene must stop at the first traffic light and F represents the event that she needs to stop at the second traffic light. The probabilities of these events are given as P(E)=0.2 and P(F)=0.3, respectively. Additionally, we're given that the probability of both events happening (denoted P(E ∩ F)) is 0.13.

In order to analyze the situation, we can leverage the rule of joint probability, which states that the probability of two independent events both happening is the product of their individual probabilities. However, in this case the events E and F are not independent (since the probability of the intersection P(E ∩ F) is not equal to the product of probabilities P(E)*P(F)) so we know that the occurrence of E does influence the occurrence of F, and vice versa.

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Answer:

Number of births to women below 22 years of age: 830

% of births occurred to women of age between 34 and 36: 6.35%

Step-by-step explanation:

There are two parts to this question:

To calculate the number of births, we look at the histogram below.

We see that each bar has a number on top, suggesting that particular for the age limit. Number of births to women below age of 22, we start adding all numbers below the mark of 22 on x-axis:

⇒ 39+134+29+363 = 830

To calculate the percentage, we divide the number of births in that particular interval by total number of births and then multiply by 100.

To calculate the total number of births, we add all the numbers on the top of the bars:

⇒ 39+ 134+294+363+391+425+460+474+432+343+250+163+98+49+17+4+1 Total births = 3937

[tex]\frac{250}{3937} \times 100\\ 0.0635 \times 100\\= 6.35 \%[/tex]

To sketch the curve of intersection, we substitute the equation of the parabolic cylinder into the equation of the ellipsoid. We use the discriminant to determine the nature of the curve and find its parametric equations.

To sketch the curve of intersection of the parabolic cylinder and the top half of the ellipsoid, we can substitute the equation of the parabolic cylinder into the equation of the ellipsoid and then solve for the remaining variable. By doing this, we obtain a quadratic equation.

We can then use the discriminant to determine the nature of the solutions, which will help us identify if the curve is a parabola or an ellipse. Based on the discriminant, we can find the parametric equations for the curve and determine its shape.

For example, if the quadratic equation has two distinct real solutions, then the curve is an ellipse, but if it has one repeated real solution, the curve is a parabola.

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Answer:

(44/4)*30 = $330

Step-by-step explanation:

divide by four and multiply by 30

So, the probabilities are: (a) 37/64, (b) 3/64, (c) 27/64, (d) 57/64

In each spin, there are four possible outcomes (nun, gimel, hei, shin), and each outcome is equally likely.

(a) Probability of getting at least one nun:

The probability of getting no nuns in a single spin is 3/4. So, the probability of getting no nuns in three spins is [tex](3/4)^3[/tex]. Therefore, the probability of getting at least one nun is 1 - [tex](3/4)^3[/tex].

Probability of getting at least one nun:

1 - [tex](3/4)^3[/tex] = [tex]1-\frac{27}{64}=\frac{37}{64}[/tex] = 0.58

(b) Probability of getting exactly 2 nuns:

The probability of getting a nun in a single spin is 1/4. So, the probability of getting exactly 1 hei in three spins is [tex]\left(\begin{array}{l}\frac{3}{1} \\\end{array}\right)\left(\frac{1}{4}\right)\left(\frac{3}{4}\right)^2[/tex].

= [tex]3 \times \frac{1}{16} \times \frac{3}{4}=\frac{3}{64}[/tex] = 0.05

(c) Probability of getting exactly 1 hei:

The probability of getting a hei in a single spin is 1/4. So, the probability of getting exactly 1 hei in three spins is [tex]\left(\begin{array}{l}\frac{3}{1} \\\end{array}\right)\left(\frac{1}{4}\right)\left(\frac{3}{4}\right)^2[/tex]

= [tex]3 \times \frac{1}{4} \times \frac{9}{16}=\frac{27}{64}[/tex] = 0.42

(d) Probability of getting at most 2 gimels:

The probability of getting 0 gimels is [tex](3/4)^3[/tex]. The probability of getting 1 gimel is [tex]\left(\begin{array}{l}\frac{3}{1} \\\end{array}\right)\left(\frac{1}{4}\right)\left(\frac{3}{4}\right)^2[/tex]. The probability of getting 2 gimels is [tex]\left(\begin{array}{l}\frac{3}{2} \\\end{array}\right)\left(\frac{1}{4}\right)^2\left(\frac{3}{4}\right)[/tex].

Add these probabilities to get the total probability.

[tex]\left(\frac{3}{4}\right)^3+\left(\begin{array}{l}\frac{3}{1} \\\end{array}\right)\left(\frac{1}{4}\right)\left(\frac{3}{4}\right)^2+\left(\begin{array}{l}\frac{3}{2} \\\end{array}\right)\left(\frac{1}{4}\right)^2\left(\frac{3}{4}\right)[/tex]

[tex]=\frac{27}{64}+\frac{27}{64}+\frac{3}{64}=\frac{57}{64}[/tex] = 0.9

​

Calculating probabilities of specific outcomes when spinning a dreidel multiple times.

Dreidel Probability Calculations:

Approximately 68.26% of the measurements fall between 46 and 74 in this distribution.

To find the proportion of measurements between 46 and 74 in a normal distribution with a mean (μ) of 60 and a standard deviation (σ) of 14, we can use the standard normal distribution (z-score) and the cumulative distribution function (CDF).

First, we need to convert the interval endpoints to z-scores using the formula:

z = (x - μ) / σ

Where x is the value in the interval, μ is the mean, and σ is the standard deviation.

For x = 46:

z₁ = (46 - 60) / 14

z₁ = -1

For x = 74:

z₂ = (74 - 60) / 14

z₂ = 1

Using the Excel functions:

=NORM.S.DIST(-1) and =NORM.S.DIST(1)

The probabilities are 0.1587 and 0.8413 respectively.

Now, we want the proportion of measurements between z₁ and z₂, which is:

Proportion = 0.8413 - 0.1587

                  ≈ 0.6826

To learn more about the z-score;

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Final answer:

Using the Empirical Rule for a normal distribution, approximately 68% of the measurements would fall between 46 and 74, as this range lies within one standard deviation above and below the mean of 60 in a distribution with a standard deviation of 14.

Explanation:

To find the proportion of measurements between 46 and 74 in a distribution with a mean of 60 and a standard deviation of 14, we can use the Empirical Rule, assuming the distribution is normal (bell-shaped). This rule states that approximately 68% of the data lies within one standard deviation of the mean, 95% within two, and more than 99% within three.

In this case, 46 is one standard deviation below the mean (60 - 14), and 74 is one standard deviation above the mean (60 + 14). So, we would expect approximately 68% of the measurements to lie between 46 and 74.

This is because the data is likely to be distributed symmetrically around the mean in a normal distribution, and the range given includes measurements falling within one standard deviation from the mean.

Answer:

Number of student = 25

Step-by-step explanation:

Let x be the number of student and y be the others

A new streaming service charges 5 dollars per month for students, and 10 dollars per month for everyone else

[tex]x+y=55\\y=55-x[/tex]

[tex]5x+10y=425[/tex]

replace y with 55-x

[tex]5x+10y=425\\5x+10(55-x)=425\\5x+550-10x=425\\-5x+550= 425[/tex]

Subtract 550 from both sides

[tex]-5x+550= 425\\-5x= -125\\x=25[/tex]

[tex]y=55-x\\y=55-25\\y=30\\[/tex]

Number of student = 25

Answer: 25 students used the service this month.

Step-by-step explanation:

Let x represent the number of students that used the streaming service this month.

Let y represent the number of people apart from students that used the streaming service this month.

This month, the service had 55 users. It means that

x + y = 55

The new streaming service charges 5 dollars per month for students, and 10 dollars per month for everyone else. They collected a total of 425 dollars. It means that

5x + 10y = 425 - - - - - - -1

Substituting x = 55 - y into equation 1, it becomes

5(55 - y) + 10y = 425

275 - 5y + 10y = 425

- 5y + 10y = 425 - 275

5y = 150

y = 150/5 = 30

x = 55 - y = 55 - 30

x = 25

Answer:

linear: 5s

quadratic: 50s

log-linear: 0.75 s

cubic: 500s

Step-by-step explanation:

Let [tex]t_1,t_2[/tex] be the running time associated with the input of sizes [tex] s_1,s_2[/tex]

If the running time is linear

[tex]t_2 = t_1\frac{s_2}{s_1} = 0.5*\frac{1000}{100} = 0.5*10 = 5s[/tex]

If the running time is quadratic

[tex]t_2 = t_1\left(\frac{s_2}{s_1}\right)^2 = 0.5*\left(\frac{1000}{100}\right)^2 = 0.5*10^2 = 50s[/tex]

If the running time is log-linear

[tex]t_2 = t_1\frac{log(s_2)}{log(s_1)} = 0.5*\frac{log(1000)}{log(100)} = 0.5*1.5 = 0.75s[/tex]

If the running time is cubic:

[tex]t_2 = t_1\left(\frac{s_2}{s_1}\right)^3 = 0.5*\left(\frac{1000}{100}\right)^3 = 0.5*10^3 = 500s[/tex]

Answer:

Option D

75.39

Step-by-step explanation:

When provided with the co-ordinates (x, y) and(a, b) then the distance between them is given by  [tex]\sqrt {(x-a)^{2}+(y-b)^{2}}[/tex]

Since  u = (25, $350) and v = (53, $420) then the Euclidean distance will be

[tex]\sqrt {(53-25)^{2}+(350-420)^{2}}=75.3923073\approx 75.39[/tex]

The dissimilarity between the two observations using Euclidean distance is approximately 75.39(Option d).

To calculate the dissimilarity between two observations using Euclidean distance, we need to find the distance between the corresponding elements in the two observations and then calculate the square root of the sum of their squared differences.

In this case, we have:

u = (25, $350) and v = (53, $420)

The distance between the ages is 53 - 25 = 28.

The distance between the amounts spent is $420 - $350 = $70.

Now we can use the formula for Euclidean distance:

Distance = sqrt((28)^2 + (70)^2) = sqrt(784 + 4900) = sqrt(5684) ≈ 75.39

Therefore, the dissimilarity between the two observations using Euclidean distance is approximately 75.39.

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Answer:

0.2637

Step-by-step explanation:

We see from the question that the 5-card hand contains all 4 suits as shown below;

Number of cards = 52

Number of suits = 4

For the favorable cases therefore, we will choose two cards from the suit in which two cards are drawn. Then we will proceed to choose one card from each of the other suits.

4 suits will divide into 52 cards to give = (52 / 4) = 13 cards

Hence, the required probability;

[tex]= {\frac{4 *13c_2*13c_1*13c_1*13c_1}{52c_5}}\\= {\frac{2197}{8330}}\\= 0.2637[/tex]

Answer:

Step-by-step explanation:

Check attachment for solution

Answer:

a) [tex] \bar X = \frac{2+2+1+3+1+0+4+1}{8}= 1.75[/tex]

b) The margin of error indicates we can be 95%confident that the sample mean falls within 0.89 of the population mean

Step-by-step explanation:

Part a

The best point of estimate for the population mean is the sample mean given by:

[tex] \bar X = \frac{\sum_{i=1}^n X_i}{n}[/tex]

Since is an unbiased estimator [tex] E(\bar X) = \mu[/tex]

Data given: 2 , 2 , 1 , 3 , 1 , 0 , 4 , 1

So for this case the sample mean would be:

[tex] \bar X = \frac{2+2+1+3+1+0+4+1}{8}= 1.75[/tex]

Part b

Previous concepts

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".

[tex]\bar X[/tex] represent the sample mean for the sample  

[tex]\mu[/tex] population mean (variable of interest)

s represent the sample standard deviation

n represent the sample size  

The confidence interval for the mean is given by the following formula:

[tex]\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]   (1)

The margin of error is given by this formula:

[tex] ME=t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex]    (2)

And for this case we know that ME =0.89 with a confidence of 95%

So then the limits for our confidence level are:

[tex] Lower= \bar X -ME= 1.75- 0.89=0.86[/tex]

[tex] Upperr= \bar X +ME= 1.75+0.89=2.64[/tex]

So then the best answer for this case would be:

The margin of error indicates we can be 95%confident that the sample mean falls within 0.89 of the population mean

Answer:

12x + 2

Step-by-step explanation:

Let the number be represented by x.

Then five times the number = 5*x

Seven times the number = 7*x

Sum of 5 times the number minus -2 = [tex]\[5*x - (-2)\][/tex] = [tex]\[5x +2\][/tex]

Adding seven times the number to this expression yields, [tex]\[5x+2+7x\][/tex]

[tex]\[= (5+7)x+2\][/tex]

[tex]\[= 12x+2\][/tex]

So the simplified expression corresponds to 12x + 2.

The answer are (a) 169 (b) 341 (c) 125 (d) 87

A Venn diagram is an illustration that uses circles to show the commonalities and differences between things or groups of things.

Given that, A department store surveyed 428 shoppers, and the following information was obtained: 216 shoppers made a purchase, and 294 were satisfied with the service they received. If 47 of those who made a purchase were not satisfied with the service,

Refer to the Venn diagram attached.

The total number of shoppers surveyed is, N = 428.

Number of shoppers who made a purchase, n (P) = 216

Number of shoppers who were satisfied with the service they received,

n (S) = 294

Number of shoppers who made a purchase but were not satisfied with the service, n(S' ∩ P)  = 47

(a) The number of shoppers who made a purchase and were satisfied with the service = n(S ∩ P)

n(S ∩ P) = n(P)-n(S'∩P)

= 216 - 47 = 169

(b) The numbers of shoppers who made a purchase or were satisfied with the service = n (P ∪ S)

n (P ∪ S) = n(P)+n(S)-n(S∩P)

= 216+294-169

= 341              

(c) The numbers of shoppers who were satisfied with the service but did not make a purchase = n(S∩P')

= n(S)-n(S∩P)

= 241-169

= 125

(d) The number of shoppers who were not satisfied and did not make a purchase  = n(S'∩P')

= N-n (S ∪ P)

= 428-341

= 87

Hence, the answer are (a) 169 (b) 341 (c) 125 (d) 87

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a. 169 shoppers made a purchase and were satisfied with the service.

b. 341 shoppers made a purchase or were satisfied with the service.

c. 125 shoppers were satisfied with the service but did not make a purchase.

d. 381 shoppers were not satisfied and did not make a purchase.

Let's break down the information given:

Total shoppers surveyed = 428

Shoppers who made a purchase = 216

Shoppers satisfied with the service = 294

Shoppers who made a purchase and were not satisfied = 47

We are asked to find:

a. Shoppers who made a purchase and were satisfied with the service.

To find this, we subtract the shoppers who made a purchase and were not satisfied from the total shoppers who made a purchase:

216 − 47 = 169

b. Shoppers who made a purchase or were satisfied with the service.

To find this, we add the shoppers who made a purchase and the shoppers who were satisfied, but we need to be careful not to count the overlap twice (those who made a purchase and were satisfied):

216+294−169=341

c. Shoppers who were satisfied with the service but did not make a purchase.

To find this, we subtract the shoppers who made a purchase and were satisfied from the total shoppers who were satisfied:

294−169=125

d. Shoppers who were not satisfied and did not make a purchase.

To find this, we subtract the shoppers who made a purchase and were not satisfied from the total shoppers surveyed:

428−47=381

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Answer:

The trip consists of two parts. The rowing part is the hypotenuse of right angled triangle

whose sides are the distance from P to the island, which is 5, and the distance between P and

the landing point of the rowboat on the shore, which is x

so this part of trip is sqrt(25+ x^2)

The 2nd part is the walking part, which is (8-x)

Distance = rate times time (D = rt), so to get the time you have t = D/r. We must divide each

of the trip by the appropriate rate to get the time.

a) T(x) = sqrt(25+x^2)/3 + (8-x)/4

To find minimum time required take derivative of the T(x) function and find it's zeros

T'(x) = x/(3(sqrt(25+x^2)) - 1/4 = 0

x/(3(sqrt(25+x^2)) = 1/4

4x = 3sqrt(25+x^2

16x^2 = 9(25+x^2) = 225 + 9x^2

7x^2 = 225

x^2 = 225/7

x = sqrt(225/7) = 5.669467 miles

T(x) = 3.602386382 hours

Step-by-step explanation:

The point where the boat should be landed can be found by expressing

the distance travelled on the boat and walking as a function of time.

The point where the boat should be landed is the point 3.4 miles from the

point P towards the town.

Reasons:

x represent the distance from point P to the boat landing point.

Therefore, distance of rowing the boat = √((12 - x)² + 3²)

The total time, t, is therefore;

[tex]t = \dfrac{12-x}{4} +\dfrac{\sqrt{x^2 + 3^2} }{3}[/tex]

When the time is minimum, we get;

[tex]\dfrac{dt}{dx} = \dfrac{d}{dx} \left( \dfrac{12-x}{4} +\dfrac{\sqrt{x^2 + 3^2} }{3} \right) = \dfrac{12\cdot \left(-3 + 4 \cdot\dfrac{2 \cdot x }{2\cdot \sqrt{x^2 + 9} } \right)}{144}[/tex]

[tex]\dfrac{12\cdot \left(-3 + 4 \cdot\dfrac{2 \cdot x }{2\cdot \sqrt{x^2 + 9} } \right)}{144} = -\dfrac{1}{4} +\dfrac{x }{3 \cdot \sqrt{x^2 +9} }[/tex]

[tex]\dfrac{x }{3 \cdot \sqrt{x^2 +9} } = \dfrac{1}{4}[/tex]

4·x = 3·√(x² + 9)

16·x² = 9·(x² + 9)

7·x² = 81

[tex]x = \dfrac{9 \cdot \sqrt{7} }{7}[/tex]

x ≈ 3.4 miles.

The point where the boat should be landed is the point approximately 3.4

miles from the point P in the direction of the town.

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Answer:

a) 0.501

b) 0.166

c) 0.3

Step-by-step explanation:

We have the following information:

1967 qualified applicants

985 accepted

327 waitlisted

655 turned away for lack of space

a. The relative frequency of accepted qualified students (to three places after the decimal) is:________

This is the number of accepted qualified students divided by the number of qualified students.

So

985/1967 = 0.501

b. The proportion of waitlisted students (to three places after the decimal) is:________

This is the number of waitlisted students divided by the number of qualified students.

So

327/1967 = 0.166

c. The percentage of students turned away from lack of space (to one place after the decimal) is:______

This is the number of students turned away by lack of space divided by the number of qualified students.

So

655/1967 = 0.3

The relative frequency of accepted students is approximately 0.501, the proportion of waitlisted students is 0.166, and the percentage of students turned away for lack of space is roughly 33.3%.

To find the relative frequency, proportion, and percentage from the given data for the school district's magnet schools program, we will use simple mathematical computations. We have a total of 1967 qualified applicants, where 985 were accepted, 327 were waitlisted, and 655 were turned away due to lack of space.