Suppose that diameters of a new species of apple have a bell-shaped distribution with a mean of 7.25 cm and a standard deviation of 0.42 cm. Using the empirical rule, what percentage of the apples have diameters that are between 6.41cm and 8.09 cm?

Answers

Answer 1

Answer:

95%

Step-by-step explanation:

Upper limit = 8.09 cm

Lower limit = 6.41 cm

Distribution mean = 7.25 cm

Standard deviation = 0.42 cm

The number of standard deviations from the mean of the upper and lower limits are, respectively:

[tex]N_U=\frac{U-M}{SD} =\frac{8.09-7.25}{0.42}=2 \\N_L=\frac{M-L}{SD} =\frac{7.25-6.41}{0.42}=2[/tex]

Both limits are two standard deviations away from the mean.

According to the empirical rule, in normal distributions, 95% of the data falls within two standard deviations of the mean. Therefore, 95% of the apples have diameters that are between 6.41cm and 8.09 cm.


Related Questions

in a random sample of 72 adults in santa clarita, CA each person was asked if they support the death penalty. 31 adults in the sample said they dp support the death penalty. What was the sample proportion of adults in Santa CLarita that support the death penalty?Now calculate a 95% confience interval population estimate of people in Santa Clarita that support the death penalty.

Answers

Answer:

a) [tex] \hat p = \frac{X}{n}= \frac{31}{72}= 0.431[/tex]

b) [tex]0.431 - 1.96 \sqrt{\frac{0.431(1-0.431)}{72}}=0.317[/tex]

[tex]0.431 + 1.96 \sqrt{\frac{0.431(1-0.431)}{72}}=0.545[/tex]

And the 95% confidence interval would be given (0.317;0.545).

Step-by-step explanation:

Part a

The best estimator for the population proportion is the sample proportion given by:

[tex] \hat p = \frac{X}{n}= \frac{31}{72}= 0.431[/tex]

Where X represent the adults in the sample that support the death penalty and n the sample size selected

Part b

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]0.431 - 1.96 \sqrt{\frac{0.431(1-0.431)}{72}}=0.317[/tex]

[tex]0.431 + 1.96 \sqrt{\frac{0.431(1-0.431)}{72}}=0.545[/tex]

And the 95% confidence interval would be given (0.317;0.545).

The sample proportion is approximately 0.431, and the 95% confidence interval for the population proportion is (0.317, 0.545), providing a range for the likely proportion of adults in Santa Clarita who support the death penalty based on the sample data.

In a random sample of 72 adults in Santa Clarita, California, the sample proportion ([tex]\hat{p}[/tex]) of adults who support the death penalty is calculated using the formula [tex]\hat{p}[/tex] = X/n, where X is the number of adults in the sample supporting the death penalty (31), and n is the sample size (72).

In this case, [tex]\hat{p}[/tex] = 31/72 ≈ 0.431, representing the estimated proportion of adults in Santa Clarita supporting the death penalty.

To construct a 95% confidence interval for the population proportion, the formula for the confidence interval is employed:

Confidence Interval = [tex]\left( \hat{p} - Z \sqrt{\frac{\hat{p}(1-\hat{p})}{n}}, \hat{p} + Z \sqrt{\frac{\hat{p}(1-\hat{p})}{n}} \right)[/tex]

Here, Z is the z-score associated with a 95% confidence interval, which is approximately 1.96. Substituting the given values into the formula, the confidence interval is calculated as (0.317, 0.545), indicating that we can be 95% confident that the true proportion of adults in Santa Clarita supporting the death penalty lies within this range.

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Compact and oversized tires are produced on two different machines. The table shows the number of each type of tire produced, y, depending on the number of hours, x, the machines work.

Answers

Answer:

OPTION B: 57x - 3

Step-by-step explanation:

Total tires produced is the sum of number of over-sized tires and the number of compact tires.

So, we have when x = 1, tires, y = 23 + 31 = 54

When x = 2, total tires y = 48 + 63  = 111

When x = 3, total tires y = 73 + 95  = 168

When x = 4, total tires y = 98 + 127 = 225

We can substitute the options to check which one will be the correct representation.

Option A: 55x - 1

When x = 1, y = 55(1) - 1    = 54

When x = 2, y = 55(2) - 1  = 109    [tex]$ \ne $[/tex]    111

So, this option is eliminated.

Option B: 57x - 1

When x = 1, y = 57(1) - 3    =   54

When x = 2, y = 57(2) - 3  =   111

When x = 3, y = 57(3) - 3  =   168

When x = 4, y = 57(4) - 3  =   225

These values exactly match with the values from the table. So, Option B is the right answer.

Option C: 110x - 2

When x = 1, y = 110(1) - 2 = 108  [tex]$ \ne $[/tex]  54

Hence, this option is incorrect.

Option D: 114x - 6

When x = 1, y = 114(1) - 6 [tex]$ \ne $[/tex]  54

Hence, this option is also eliminated.

Option B is the required answer.

Researchers studied 208 infants whose brains were temporarily deprived of oxygen due to complications at birth. When researchers detected oxygen deprivation, they randomly assigned babies to either usual care or to a whole-body cooling group. The goal was to see whether reducing body temperature for three days after birth increased the rate of survival without brain damage.
Which of the following is used in the design of this experiment? Check all that apply.

a. Random assignment
b. No answer text provided
c. Double blinding
d. Control group

Answers

Answer:

Correct option: c. Double blind.

Step-by-step explanation:

A double blind experiment is an experiment where the participants are divided into two groups: one is the experimental group and the other is a control group. The participants in the experimental group are provided with a treatment and those in the control group are not provided with the treatment but are given a placebo.

In this experiment neither the researcher nor the participants know to which group a participant is placed.

After the experiment the results for the two groups are compared and the conclusion is hence drawn.

Here the researcher randomly assigned babies to either usual care or to a whole-body cooling group. The experimental group is the cooling group and the control group is the group provided with usual treatment.

Thus, the researchers are conducting a double blind experiment to determine whether reducing body temperature for three days after birth increased the rate of survival without brain damage or not.

Thus, the correct option is (c).

If you use a 95% confidence level in a two-tail hypothesis test, what will you decide about your Null Hypothesis if the computed value of the test statistic is Z = 2.57? Why?

Answers

Answer:

z_{calc}=2.57[/tex]

Since is a two-sided test the p value would be:  

[tex]p_v =2*P(z>2.57)=0.0101[/tex]  

If we compare the p value and the significance level given [tex]\alpha=0.05[/tex] we see that [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is different from [tex]\mu_o[/tex] at 5% of signficance.  

Step-by-step explanation:

Data given and notation  

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

[tex]\sigma[/tex] represent the population standard deviation

[tex]n[/tex] sample size  

[tex]\mu_o [/tex] represent the value that we want to test  

Confidence = 95% or 0.95

[tex]\alpha=1-0.95=0.05[/tex] represent the significance level for the hypothesis test.  

z would represent the statistic (variable of interest)  

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

State the null and alternative hypotheses.  

We need to conduct a hypothesis in order to check if the mean is equal to an specified value [tex]\mu_o [/tex], the system of hypothesis would be:  

Null hypothesis:[tex]\mu =\mu_o[/tex]  

Alternative hypothesis:[tex]\mu \neq \mu_o[/tex]  

Since we know the population deviation, is better apply a z test to compare the actual mean to the reference value, and the statistic is given by:  

[tex]z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}}[/tex] (1)  

z-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Calculate the statistic  

We can replace in formula (1) and we got a value calculated let's say [tex] z_{calc}=2.57[/tex]

P-value  

Since is a two-sided test the p value would be:  

[tex]p_v =2*P(z>2.57)=0.0101[/tex]  

Conclusion  

If we compare the p value and the significance level given [tex]\alpha=0.05[/tex] we see that [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the true mean is different from [tex]\mu_o[/tex] at 5% of signficance.  

For a 95% confidence level in a two-tail hypothesis test, if the computed Z-value is 2.57, you would reject the null hypothesis, as the value lies outside the critical z-scores of ±1.96, indicating statistical significance.

If you use a 95% confidence level in a two-tail hypothesis test, the critical z-scores are ±1.96.

This means that if the computed test statistic falls beyond these values (either less than -1.96 or greater than +1.96), we reject the null hypothesis.

In the scenario where the computed value of the test statistic is Z = 2.57, it is greater than +1.96. Therefore, under these conditions, you will reject the null hypothesis.

The reason for this decision stems from the test statistic lying outside the range of values considered to be consistent with the null hypothesis at the 95% confidence level.

The absolute value of 2.57 is greater than 1.96, indicating that the observed effect is statistically significant, and the likelihood of observing such a result if the null hypothesis were true is less than 5% (which is the alpha level of 0.05 associated with a 95% confidence level).

This indicates that there is sufficient evidence to support the alternative hypothesis over the null hypothesis in a two-tailed test.

List the Octal and Hexadecimal numbers from 16 to 32. Using A and B as the last two digits (A representing a value of 10 and B representing a value of 11), list the numbers from 8 to 28 in base 12.

Answers

Answer:

  see attached

Step-by-step explanation:

The attached list shows base-10 numbers in the left column, followed by their equivalents in base 8, base 16, and base 12.

Counting is done in the usual way: when you come to the last digit of the particular base, you increment the next digit to the left, and start over.

Final answer:

The Octal numbers from 16 to 32 and the Hexadecimal numbers from 16 to 32 are listed. Additionally, numbers from 8 to 28 are provided in base 12 system, where A and B are two last digits representing 10 and 11 respectively.

Explanation:

The Octal numbers from 16 to 32 are as follows: 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 33, 34, 35, 36, 37, 40.

The Hexadecimal numbers from 16 to 32 are: 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1A, 1B, 1C, 1D, 1E, 1F, 20.

For base 12 numbers from 8 to 28, where A stands for 10 and B for 11, they are: 8, 9, A, B, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1A, 1B, 20, 21, 22, 23.

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Use the null hypothesis H0 : μ = 98.6, alternative hypothesis Ha: μ < 98.6, and level of significance α = 0.05. 98 99.6 97.8 97.6 98.7 98.4 98.9 97.1 99.2 97.4 99.1 96.9 98.8 99.9 96.8 97 98.7 97.6 98.7 98.2 whats the t-score?

Answers

Answer:

The t-score is -1.8432    

Step-by-step explanation:

We are given the following in the question:  

98, 99.6, 97.8, 97.6, 98.7, 98.4, 98.9, 97.1, 99.2, 97.4, 99.1, 96.9, 98.8, 99.9, 96.8, 97, 98.7, 97.6, 98.7, 98.2

Formula:

[tex]\text{Standard Deviation} = \sqrt{\displaystyle\frac{\sum (x_i -\bar{x})^2}{n-1}}[/tex]  

where [tex]x_i[/tex] are data points, [tex]\bar{x}[/tex] is the mean and n is the number of observations.  

[tex]Mean = \displaystyle\frac{\text{Sum of all observations}}{\text{Total number of observation}}[/tex]

[tex]Mean =\displaystyle\frac{1964.4}{20} = 98.22[/tex]

Sum of squares of differences = 16.152

[tex]s = \sqrt{\dfrac{16.152}{49}} = 0.922[/tex]

Population mean, μ = 98.6

Sample mean, [tex]\bar{x}[/tex] = 98.22

Sample size, n = 20

Sample standard deviation, s = 0.922

First, we design the null and the alternate hypothesis

[tex]H_{0}: \mu = 98.6\\H_A: \mu < 98.6[/tex]

Formula:

[tex]t_{stat} = \displaystyle\frac{\bar{x} - \mu}{\frac{s}{\sqrt{n}} }[/tex]

Putting all the values, we have

[tex]t_{stat} = \displaystyle\frac{98.22 - 98.6}{\frac{0.922}{\sqrt{20}} } = -1.8432[/tex]

The t-score is -1.8432    

Final answer:

The t-score is calculated using the sample mean, the population mean under the null hypothesis, the sample's standard deviation, and the sample size. For the provided data, these values lead to a computed t-score of approximately -0.4594.

Explanation:

To calculate the t-score for a set of data when testing a hypothesis, you can use the following formula:

t = (X - \/u0) / (s/√n)

Where X is the sample mean, \/u0 is the population mean according to the null hypothesis, s is the sample standard deviation, and n is the sample size. To find the t-score, you need to know the sample mean (X), the standard deviation (s), and the sample size (n), all of which are usually provided in the problem or can be calculated from the data. In this case:

X (sample mean) = 98.59µ0 (population mean under H0) = 98.6s (standard deviation) = 0.0973n (sample size) = 20 (number of data points provided)

Plugging these values into the t-score formula gives us:

t = (98.59 - 98.6) / (0.0973/√20)

Perform the calculations:

t = -0.01 / (0.0973/4.4721)

t = -0.01 / 0.02176

t ≈ -0.4594

Thus, the calculated t-score is approximately -0.4594.

Use scalar projection to show that the distance from a point P1(x1,y1) to the line ax+by+c=0 is |ax1+by1+c|/underroot(a^2 +b^2)

Use this formula to find the distance from the point (-2,3) to the line 3x-4y+5=0

Answers

Answer:

d = 13 / 5 units          

Step-by-step explanation:

Given:

- Point P = (-2 , 3 )

- line : 3x - 4y + 5 = 0

Find:

- Use projection to show the given formula

- use the formula to find the distance from given point and line.

Solution:

- Let line L be defined as:

                                     a*x + b*y + c = 0

- Choose A as fixed point on the line L whose coordinates are ( m , k ).

- Now the coordinates of any point (x , y ) can be given by the line L:

                                    a*( x - m ) + b*( y - k ) + c = 0

- We did that by subtracting the coordinates (x,y) from (m,k).

- The above line can represented by dot product of constants (a , b ) to vector coordinates between points (x,y) to (m,k):

                                   ( a , b ) . ( x - m , y - k) = 0

- For above expression to be true i.e the dot product of two vectors is only zero when the vectors are orthogonal. So vector (a , b ) is always perpendicular to every vector in direction of line L

- The vector:

                                         v =  ( x - m , y - k)

- It may represent the line connecting the points (x_1 , y_1) and (m, k).

Then the distance d from the point P_1: (x_1, y_1) to the line L is given by the magnitude of the scalar projection of v onto a, because the latter is the length of the side of a right  triangle with two of the vertices being P_1 and

( m , k), and the other vertex lying on L So:

                                      d = | component v along x |

                                      d =  | v . ( a , b ) | / | (a , b ) |

                                      d = | (x_1 - m , y_1 - k ) . ( a , b)| / sqrt(a^2 + b^2)

                                      d = | ax_1 + by_1 - (a*m + b*k) | / sqrt(a^2 + b^2)

Where point A (m,k) lies on line hence;

                                      a*m + b*k + c = 0

                                      c = - (a*m + b*k)

Hence,

                                      d = | ax_1 + by_1 + c | / sqrt(a^2 + b^2)

- Given point P (-2,3) and line L : 3x - 4y + 5 = 0

where,

                                    (x_1 , y_1) = (-2 , 3 )

                                     (a , b) = ( 3 , -4 )

                                            c = 5

-Evaluate:

                                    d = | 3*(-2) + -4*3 + 5 | / sqrt(3^2 + 4^2)

                                    d = | - 13 | / 5

                                    d = 13 / 5 units                                    

                               

The distance from the point (-2,3) to the line [tex]\(3x - 4y + 5 = 0\)[/tex] is [tex]\(\frac{|3(-2) - 4(3) + 5|}{\sqrt{3^2 + (-4)^2}}\)[/tex].

To find the distance from a point [tex]\(P_1(x_1, y_1)\)[/tex] to a line [tex]\(ax + by + c = 0\)[/tex], one can use the formula derived from scalar projection:

[tex]\[ \text{Distance} = \frac{|ax_1 + by_1 + c|}{\sqrt{a^2 + b^2}} \][/tex]

Here, [tex]\(a\)[/tex], [tex]\(b\)[/tex], and [tex]\(c\)[/tex] are the coefficients of the line, and [tex]\(x_1\)[/tex] and [tex]\(y_1\)[/tex] are the coordinates of the point. The numerator represents the absolute value of the expression [tex]\(ax_1 + by_1 + c\)[/tex], which is the scalar projection of the vector from the origin to the point onto the normal vector of the line. The denominator is the magnitude of the normal vector of the line.

Given the point [tex]\(P_1(-2, 3)\)[/tex] and the line [tex]\(3x - 4y + 5 = 0\)[/tex], we substitute [tex]\(x_1 = -2\)[/tex] and [tex]\(y_1 = 3\)[/tex] into the formula:

[tex]\[ \text{Distance} = \frac{|3(-2) - 4(3) + 5|}{\sqrt{3^2 + (-4)^2}} \][/tex]

Now, we calculate the numerator:

[tex]\[ 3(-2) - 4(3) + 5 = -6 - 12 + 5 = -13 + 5 = -8 \][/tex]

The absolute value of [tex]\(-8\)[/tex] is [tex]\(8\)[/tex], so the numerator becomes [tex]\(8\)[/tex].

Next, we calculate the denominator, which is the magnitude of the normal vector of the line:

[tex]\[ \sqrt{3^2 + (-4)^2} = \sqrt{9 + 16} = \sqrt{25} = 5 \][/tex]

Finally, we divide the absolute value we found in the numerator by the denominator to get the distance:

[tex]\[ \text{Distance} = \frac{8}{5} \][/tex]

Therefore, the distance from the point (-2,3) to the line [tex]\(3x - 4y + 5 = 0\)[/tex] is [tex]\(\frac{8}{5}\)[/tex].

Calculate the data value that corresponds to each of the following z-scores.

a. Final exam scores: Allison’s z-score = 2.30, μ = 74, σ = 7.
b. Weekly grocery bill: James’ z-score = –1.45, μ = $53, σ = $12.
c. Daily video game play time: Eric’s z-score = –0.79, μ = 4.00 hours, σ = 1.15 hours.

Answers

Answer:

a) 90.1

b) $35.6

c) 3.0915 hours

Step-by-step explanation:

The z-score measures how many standard deviations 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 and [tex]\sigma[/tex] is the standard deviaition.

In all three cases, we have to find X

a. Final exam scores: Allison’s z-score = 2.30, μ = 74, σ = 7.

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

[tex]2.30 = \frac{X - 74}{7}[/tex]

[tex]X - 74 = 7*2.3[/tex]

[tex]X = 90.1[/tex]

b. Weekly grocery bill: James’ z-score = –1.45, μ = $53, σ = $12.

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

[tex]-1.45 = \frac{X - 53}{12}[/tex]

[tex]X - 53 = -1.45*12[/tex]

[tex]X = 35.6[/tex]

Mean and standard deviation in dollars, so the answer also in dollars.

c. Daily video game play time: Eric’s z-score = –0.79, μ = 4.00 hours, σ = 1.15 hours.

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

[tex]-0.79 = \frac{X - 4}{1.15}[/tex]

[tex]X - 4 = -0.79*1.15[/tex]

[tex]X = 3.0915[/tex]

Mean and standard deviation in hours, answer in hours.

Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data is plotted with temperature, in degrees Fahrenheit (degree), on the horizontal axis and the number of ice bags sold on the vertical axis. One of the plotted points on the graph is (82.67). The least squares regression line for this data is y =-192.20 + 3.13x. Determine the predicted number of bags of ice sold, y, when the temperature is 82 degree F. Round the predicted value to the nearest whole number. y = ice bags Compute the residual at this temperature. Round the value to the nearest whole number. residual = ice bags

Answers

Answer:

64bags of ice were sold when the temperature is 82 degree F

Step-by-step explanation:

From the equation ; Y =-192.20 + 3.13x

where Y = predicted number of bags of ice sold

x = temperature, in degrees Fahrenheit (degree)

To find Y when x = 82

substitute the value of x in the equation given

= Y = -192.20 + 3.13(82)

Y = 64.46 and approximately, Y = 64

To Compute the residual at this temperature;

residual = 67 - 64.46= 2.53 which is approximately 3

Assume that 200 births are randomly selected and 6 of the births are girls. Use subjective judgment to describe the number of girls as significantly​ high, significantly​ low, or neither significantly low nor significantly high. Choose the correct answer below. A. The number of girls is neither significantly low nor significantly high. B. The number of girls is significantly low. C. The number of girls is significantly high.

Answers

Answer:

B. The number of girls is significantly low.

Step-by-step explanation:

Given that 200 births are randomly selected and 6 of the births are girls.

Normally we expect 50% of births to be boys and 50% girls.  If it is not exactly 50% atleast near to 50% we expect

But here out of 200 births, only 6 births are girls.

This means percentage of girls birth= [tex]\frac{6}{200} =0.03[/tex]=3%

while that of boys is 97%

This is a very unbalanced figure posing danger to the future generations.

B. The number of girls is significantly low.

Final answer:

The number of girls out of 200 randomly selected births is significantly low.

Explanation:

The number of girls out of a randomly selected group of 200 births is 6. To determine if this number is significantly high or low, we can use statistical methods. To do this, we can calculate the expected number of girls using probability. Assuming a 50% probability of having a boy or a girl, the expected number of girls would be 200 * 0.5 = 100. Comparing the observed number of girls (6) to the expected number (100), we can see that the number of girls is significantly low.

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Find a parametrization of the line in which the planes x + y + z = -6 and y + z = -8 intersect.
Find the parametrization of the line. Use a point with z = 0 on the line to determine the parametrization.

Answers

Answer:

L(x,y) = (2,-8,0) + (0,-1,1)*t

Step-by-step explanation:

for the planes

x + y + z = -6  and y + z = -8

the intersection can be found subtracting the equation of the planes

x + y + z - ( y + z ) = -6 - (-8)

x= 2

therefore

x=2

z=z

y= -8 - z

using z as parameter t and the point (2,-8,0) as reference point , then

x= 2

y= -8 - t

z= 0 + t

another way of writing it is

L(x,y) = (2,-8,0) + (0,-1,1)*t

Final answer:

The parametrization of the line where the planes x + y + z = -6 and y + z = -8 intersect is found by solving the equations together and using a point with z = 0. This leads to parametric equations x(t) = 2, y(t) = -8 - t, and z(t) = t.

Explanation:

To find a parametrization of the line in which the planes x + y + z = -6 and y + z = -8 intersect, we first solve these two equations together to find the relationship between x, y, and z. Since both equations involve y and z, we can set them equal to isolate x.

1. Subtract the second equation from the first to isolate x: x = 2.

2. Using the second equation y + z = -8, we express y in terms of z: y = -8 - z.

Now, to use a point with z = 0 to determine the parametrization, we plug z = 0 into our equations. This gives us x = 2 and y = -8 for the point (2, -8, 0).

With z as our parameter t, the parametrization of the line can be given as x = 2, y = -8 - t, and z = t. Therefore, the parametric equations describing the intersection line are x(t) = 2, y(t) = -8 - t, and z(t) = t.

Suppose two dice, one orange and one blue, are rolled. Define the following events: A: The product of the two numbers that show is 12 B: The number on the orange die is strictly larger than the number on the blue die. C: The sum of the numbers is divisible by four. D: The number on the orange die is either 1 or 3

Answers

Answer:

A = {2,6; 6,2; 3,4; 4,3}

B = {6,5; 6,4; 6,3; 6,2; 6,1; 5,4; 5,3; 5,2; 5,1; 4,3; 4,2; 4,1; 3,2; 3,1; 2,1}

C = {1,3; 3,1; 2,2; 3,5; 5,3; 4,4; 6,6}

D = {1,1; 1,2; 1,3; 1,4; 1,5; 1,6; 3,1; 3,2; 3,3; 3,4; 3,5; 3,6}

Step-by-step explanation:

Let the pair (O,B) be the number rolled on the orange and blue dice respectively.

For event A:  The product of the two numbers that show is 12, the sample space is:

A = {2,6; 6,2; 3,4; 4,3}

For event B: The number on the orange die is strictly larger than the number on the blue die, the sample space is:

B = {6,5; 6,4; 6,3; 6,2; 6,1; 5,4; 5,3; 5,2; 5,1; 4,3; 4,2; 4,1; 3,2; 3,1; 2,1}

For event C: The sum of the numbers is divisible by four, the sum must be 4, 8 or 12 and the sample space is:

C = {1,3; 3,1; 2,2; 3,5; 5,3; 4,4; 6,6}

For event D: The number on the orange die is either 1 or 3, the sample space is:

D = {1,1; 1,2; 1,3; 1,4; 1,5; 1,6; 3,1; 3,2; 3,3; 3,4; 3,5; 3,6}

Find the proportion of observations (±0.0001) from a standard Normal distribution that falls in each of the following regions. In each case, sketch a standard Normal curve and shade the area representing the region.
(a) z gif.latex?%5Cleqslant ?2.34:
(b) z gif.latex?%5Cgeqslant ?2.34:
(c) z > 1.74:
(d) ?2.34 < z < 1.74:

Answers

Answer:

a) We can use the following excel code to find it:"=NORM.DIST(-2.34,0,1,TRUE)"

[tex] P(Z \leq -2.34)=0.0096[/tex]

b) [tex] P(Z \geq -2.34)= 1-P(X \leq -2.34)= 1-0.0096=0.9904[/tex]

c) We can use the following excel code: "=1-NORM.DIST(1.74,0,1,TRUE)"

[tex] P(Z > 1.74)= 1-P(X \leq 1.74)=0.0409[/tex]

d) We can use the following excel code: "=NORM.DIST(1.74,0,1,TRUE)-NORM.DIST(-2.34,0,1,TRUE)"

[tex] P(-2.34<Z < 1.74)= P(Z<1.74)-P(Z<-2.34)=0.959-0.0096=0.949[/tex]

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".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Part a

We want to find this probability:

[tex] P(Z \leq -2.34)[/tex]

And we can use the following excel code to find it:"=NORM.DIST(-2.34,0,1,TRUE)"

[tex] P(Z \leq -2.34)=0.0096[/tex]

Part b

We want to find this probability:

[tex] P(Z \geq -2.34)[/tex]

And for this case we can use the complement rule:

[tex] P(Z \geq -2.34)= 1-P(X \leq -2.34)[/tex]

And using the result from part a we got:

[tex] P(Z \geq -2.34)= 1-P(X \leq -2.34)= 1-0.0096=0.9904[/tex]

Part c

We want to find this probability:

[tex] P(Z > 1.74)[/tex]

And for this case we can use the complement rule:

[tex] P(Z > 1.74)= 1-P(X \leq 1.74)[/tex]

And we can use the following excel code: "=1-NORM.DIST(1.74,0,1,TRUE)"

[tex] P(Z > 1.74)= 1-P(X \leq 1.74)=0.0409[/tex]

Part d

We want to find this probability:

[tex] P(-2.34<Z <1.74)[/tex]

And for this case we can find this probability with this difference:

[tex] P(-2.34<Z < 1.74)= P(Z<1.74)-P(Z<-2.34)[/tex]

And we can use the following excel code: "=NORM.DIST(1.74,0,1,TRUE)-NORM.DIST(-2.34,0,1,TRUE)"

[tex] P(-2.34<Z < 1.74)= P(Z<1.74)-P(Z<-2.34)=0.959-0.0096=0.949[/tex]

Final answer:

The given z-scores correspond to various portions of a standard Normal distribution. Using a standard Normal distribution table, the proportions for the respective regions are derived as: z <= -2.34 is approximately 0.0094, z >= -2.34 is approximately 0.9906, z > 1.74 is approximately 0.0409, -2.34 < z < 1.74 is approximately 0.9497.

Explanation:

To answer your question, let's use the standard Normal distribution table which provides the proportion of observations less or equal to a particular z-score (for the values of z <= 0 and z >= 0).

For z <= -2.34: The proportion is simply the value associated with -2.34 in the standard Normal distribution table, which is approximately 0.0094.For z >= -2.34: This is equivalent to 1 minus the proportion of z <= -2.34, so it will be 1 - 0.0094 = 0.9906.For z > 1.74: Using similar approach, we get 1 minus the value associated with 1.74, which will be approximately 1 - 0.9591 = 0.0409.For -2.34 < z < 1.74: Here, we need to subtract the value of z <= -2.34 from the value of z <= 1.74. So, the proportion is 0.9591 - 0.0094 = 0.9497.

Please remember that these proportions represent the areas under the curve (or the total probability) that the z-score will fall within the outlined regions.

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Consider purchasing a system of audio components consisting of a receiver, a pair of speakers, and a CD player. Let A1 be the event that the receiver functions properly throughout the warranty period. Let A2 be the event that the speakers function properly throughout the warranty period. Let A3 be the event that the CD player functions properly throughout the warranty period. Suppose that these events are (mutually) independent with P(A1) = 0.91, P(A2) = 0.85, and P(A3) = 0.77.(a) What is the probability that at least one component needs service during the warranty period?(b) What is the probability that exactly one of the components needs service during the warranty period?

Answers

Answer:

(a) Probability that at least one component needs service during the warranty period = 0.4044.

(b) Probability that exactly one of the components needs service during the warranty period = 0.3419.

Step-by-step explanation:

Given A1 be the event that the receiver functions properly throughout the warranty period.

A2  be the event that the speakers function properly throughout the warranty period.

A3 be the event that the CD player functions properly throughout the warranty period.

Also P(A1) = 0.91, P(A2) = 0.85, and P(A3) = 0.77.

Now P(A1)' means that the receiver need service during the warranty period which is 1 - P(A1) = 1 - 0.91 = 0.09.

Similarly,P(A2)' =1 - P(A2) =1 - 0.85 =0.15  and  P(A3)' =1 - P(A3)=1 - 0.77 = 0.23

Note: The ' sign on the P(A1) represent compliment of A1 or not A1.

(a) The probability that at least one component needs service during the warranty period = 1 - none of the component needs service during the warranty period

And none of the component needs service during the warranty period means that all the three components functions properly during the warranty period .

So, Probability that at least one component needs service during the warranty period = 1 - P(A1) x P(A2) x P(A3) = 1 - (0.91 x 0.85 x 0.77) = 0.4044.

(b) Now to find the Probability that exactly one of the components needs service during the warranty period, there would be three cases for this:

Receiver needs service and other two does not need during the warranty period.Speaker needs service and other two does not need during the warranty period.CD player needs service and other two does not need during the warranty period.

And we have to add these three cases to calculate above probability.

Probability that exactly one of the components needs service during the warranty period = P(A1)' x P(A2) x P(A3) + P(A1) x P(A2)' x P(A3) + P(A1) x  P(A2) x P(A3)'

                         = 0.09 x 0.85 x 0.77 + 0.91 x 0.15 x 0.77 + 0.91 x 0.85 x 0.23

                         = 0.3419.

Answer:

(a) P (At least one component needs service) = 0.404

(b) P (Either component A₁ or A₂ or A₃) = 0.997

Step-by-step explanation:

Given:

[tex]A_{1}=[/tex] Event that the receiver functions properly throughout the warranty period.

[tex]A_{2}=[/tex] Event that the speakers function properly throughout the warranty period.

[tex]A_{3}=[/tex] Event that the CD player functions properly throughout the warranty period.

[tex]P(A_{1})=0.91,\ P(A_{2})=0.85\ and\ P(A_{3})=0.77[/tex]

(a)

Compute the probability that at least one component needs service during the warranty period:

P (At least one component needs service) = 1 - P (None of the one component needs service)

= 1 - {P ([tex]A_{1}[/tex]) × P ([tex]A_{2}[/tex]) × P ([tex]A_{3}[/tex])}

[tex]=1 - (0.91\times0.85\times0.77)\\=1-0.595595\\=0.404405\\\approx0.404[/tex]

Thus, the probability that at least one component needs service during the warranty period is 0.404.

(b)

Compute the probability that exactly one of the components needs service during the warranty period, i.e. P (Either A₁ or A₂ or A₃):

[tex]P(A_{1}\cup A_{2}\cup A_{3})=P(A_{1})+P(A_{2})+P(A_{3})-P(A_{1}\cap A_{2})-P(A_{2}\cap A_{3})-P(A_{3}\cap A_{1})+P(A_{1}\cap A_{2}\cap A_{3})\\=P(A_{1})+P(A_{2})+P(A_{3})-[P(A_{1})\tmes P(A_{2})]-[P(A_{2})\tmes P(A_{3})]-[P(A_{3})\tmes P(A_{1})] +[P(A_{1})\tmes P(A_{2})\times P(A_{3})]\\=0.91+0.85+0.77-(0.91\times0.85)-(0.85\times0.77)-(0.77\times0.91)+(0.91\times0.85\times0.77)\\=0.996895\\\approx0.997[/tex]

Thus, the probability that exactly one of the components needs service during the warranty period is 0.997

In a standard Normal​ distribution, if the area to the left of a​ z-score is about 0.3500​, what is the approximate​ z-score? Draw a sketch of the Normal​ curve, showing the area and​ z-score.

Answers

Answer:

z-score=0.385

(See attached picture)

Step-by-step explanation:

The procedure to find the z-score will depend on the resources we have available. I have a table with the area between the mean and the value we wish to normalize, so the very first thing we need to do is precisely find this area we need to analyze.

Everything to the left of thte mean will represent 50% of the data, so we start by subtracting:

50%-35%=15%

so we need to look in the table for the value 0.15.

In my table I can see that for an area of 0.15, the z-score will be between 0.38 (z-score of 0.1480) and 0.39 (z-score of 0.1517).

By doing some interpolation, you can determine a more accurate value of the z-score to be 0.385.

Final answer:

The z-score corresponding to an area of 0.3500 in a standard normal distribution is approximately -0.39. This z-value indicates that the data point is 0.39 standard deviations below the mean.

Explanation:

In a standard Normal distribution, the z-score is equivalent to the number of standard deviations a given data point is from the mean. If you know the area to the left of the z-score (which in this case is 0.3500), you can use a z-score table (also known as a standard normal table) to find the corresponding z-score.

Normally, the z-score table gives the area to the left of the score. However, in this case, the value (0.3500) does not appear in the body of the z-score table because it corresponds to a negative z-score (since 0.3500 < 0.5). Thus, we will first find the equivalent positive area (1- 0.3500 = 0.6500) and look up that value in the z-score table. The value 0.6500 corresponds approximately to a z-score of 0.39. Since our original question gives an area less than 0.5 (indicating a z-score below the mean) the z-score is -0.39.

Please note that for illustrating the Normal curve, any standard statistics textbook or online resource will have a diagram illustrating the curve, with a vertical line indicating the z-score (in this case -0.39) and shading demonstrating the area to the left of the z-score. These images typically aren't included in text-based tutoring platforms.

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Find a system of two equations in two variables, x1 and x2, that has the solution set given by the parametric representation x1 = t and x2 = 5t − 6, where t is any real number. (Enter your answer as a comma-separated list of equations.)

Answers

Answer:

The required system of equations to the given parametric equations are:

5x1 - x2 = 6

x1 + x2 = -6

Step-by-step explanation:

Given the parametric equations:

x1 = t

x2 = -6 + 5t

Eliminating the parameter t, we obtain one of the equations of a system in two variables, x1 and x2 that has the solution set given by the parametric equations.

Doing that, we have:

5x1 - x2 = 6

Again a second equation can be a linear combination of x1 and x2

x1 + x2 = -6 + 6t

x1 + x2 = -6 (putting t=0)

And they are the required equations.

Under what conditions might it make better sense to use a linear function rather than a quadratic or cubic function that fits a few data points more​ closely?

Answers

Answer:

Step-by-step explanation:

When data points are plotted between two variables, seeing the scatter plot we can form idea about the curve which is close to all points.

In other words, using least squares method, the curve of best fit would be the curve which has squares of deviations form the observed points a minimum

Thus conditions are

i) The scatter plot suggests a linear relationship

ii) Pearson correlation coefficient has value near to 1 or -1 suggesting linearlity

iii) There seems to be constant increase of y for unit increase in x

Under the above linear line fits

In all the other cases, quadratic or cubic function fits well.

5. Two vertices of a triangle lie at (4, 0) and (8, 0). The perimeter of the triangle is 12 units. What are all the possible locations of the third vertex? How do you know you have found them all? Can you determine which of these vertices will produce a triangle with the largest area?

Answers

Final answer:

The possible locations of the third vertex of the triangle with a perimeter of 12 units, given two vertices at (4, 0) and (8, 0), are (12, 0) and (0, 0). The vertex at (0, 0) will produce a triangle with the largest area equals to 8 square units.

Explanation:

Possible Locations of Third Vertex:

To find the possible locations of the third vertex of the triangle, we need to consider the perimeter of the triangle. Given that the perimeter is 12 units and two vertices are located at (4, 0) and (8, 0), we can deduce that the third vertex must lie on the line segment between these two points.

Calculating the Third Vertex:

Since the distance between the two given vertices is 8 - 4 = 4 units, the remaining distance to achieve a perimeter of 12 units would be 12 - 4 = 8 units.

Therefore, the possible locations of the third vertex are (4 + 8, 0) = (12, 0) or (8 - 8, 0) = (0, 0).

Determining the Largest Area:

To determine which vertex would produce a triangle with the largest area, we need to consider the base and the height of the triangle. Since both the possible vertices lie on the x-axis, the base would be the same for both triangles, which is 4 units.

The height of the triangle can be determined by finding the distance between the base and the y-coordinate of the third vertex. If the third vertex is (12, 0), the height would be 0 units. If the third vertex is (0, 0), the height would be 4 units.

Therefore, the triangle with the third vertex at (0, 0) would produce the largest area, which is equal to 1/2 * base * height = 1/2 * 4 * 4 = 8 square units.

The possible locations of the third vertex of the triangle form a line segment parallel to the x-axis and symmetric about the y-axis, extending from (4, 3) to (8, -3) or from (4, -3) to (8, 3). The triangle with the largest area will be the one where the third vertex is directly above or below the midpoint of the line segment joining the first two vertices, at either (6, 3) or (6, -3).

Given two vertices of a triangle at (4, 0) and (8, 0), the distance between them is the length of the line segment joining them, which is 8 - 4 = 4 units. Since the perimeter of the triangle is 12 units, the sum of the lengths of the other two sides must be 12 - 4 = 8 units.

Let's denote the third vertex as (x, y). The distance from (4, 0) to (x, y) is one side of the triangle, and the distance from (8, 0) to (x, y) is the other side. Using the distance formula, we have:

[tex]\[ \sqrt{(x - 4)^2 + y^2} + \sqrt{(x - 8)^2 + y^2} = 8 \][/tex]

To simplify the problem, we can look for points where the sum of the distances to the two fixed points is 8 units. Since the two given vertices are on the x-axis, the third vertex must be such that its x-coordinate is between 4 and 8 (inclusive) to form a triangle.

For the y-coordinate, we know that the sum of the distances from the third vertex to the two fixed points is 8 units. If we consider the case where y = 0, the third vertex would be on the x-axis, which would not form a triangle. Therefore, y must be non-zero.

Let's consider the two sides of the triangle formed by the third vertex and the two fixed points. The lengths of these sides can be thought of as the radii of two circles, one centered at (4, 0) and the other at (8, 0), both with a radius of 4 units (since each circle's radius is half the sum of the lengths of the two sides not on the x-axis).

The third vertex must lie on the intersection of these two circles. Since the circles are of equal radius and their centers are 4 units apart, they will intersect in two points, which will be equidistant from the line segment joining the first two vertices.

To find these points, we can set up the following system of equations based on the distance formula:

[tex]\[ (x - 4)^2 + y^2 = 16 \][/tex]

[tex]\[ (x - 8)^2 + y^2 = 16 \][/tex]

The line segment joining these two points, (6, 3) and (6, -3), represents all possible locations of the third vertex. This line segment is parallel to the x-axis and symmetric about the y-axis, and it extends from (4, 3) to (8, -3) or from (4, -3) to (8, 3), depending on which side of the x-axis the third vertex is located.

To find the vertex that produces the largest area, we note that for a given base length (which is fixed at 4 units in this case), the area of a triangle is maximized when the height is maximized. The height is maximized when the third vertex is directly above or below the midpoint of the base, which is at (6, 0). Therefore, the third vertex should be at either (6, 3) or (6, -3) to produce the triangle with the largest area. The area of this triangle is 1/2 * base * height = 1/2 * 4 * 3 = 6 square units.

We have found all possible locations of the third vertex because any point outside the line segment joining (6, 3) and (6, -3) would result in a perimeter greater than 12 units, and any point inside would result in a perimeter less than 12 units. Thus, the line segment from (4, 3) to (8, -3) or from (4, -3) to (8, 3) represents the complete set of solutions for the third vertex that satisfy the given perimeter constraint.

An apartment has two fire alarms. In the event of a fire, the probability that alarm A will fail is 0.004, and the probability that alarm B will fail is 0.01. Assume the two failures are independent, what is the probability that at least one alarm fails in the event of a fire

Answers

Answer: 0.0136

Step-by-step explanation:

Let events are:

A = alarm A will fail

B=  alarm B will fail

We have given ,

P(A) =  0.004  ,   P(B)=0.01

Since both events are independent , so

P(A and B) = P(A) x P(B)

= 0.04 x 0.01 =0.0004

i.e. P(A and B) =0.0004

Now , P(A or B) = P(A)+P(B)-P(A and B)

= 0.004+ 0.01-0.0004=0.0136

Hence, the probability that at least one alarm fails in the event of a fire is 0.0136 .

The probability that at least one alarm fails in the event of a fire is approximately 0.014 or 1.4%.

The probability that at least one alarm fails in the event of a fire is given by:

[tex]\[ P(\text{at least one fails}) = 1 - P(\text{both work}) \][/tex]

Since the failures are independent, the probability that both alarms work is the product of their individual probabilities of working:

[tex]\[ P(\text{both work}) = P(\text{A works}) \times P(\text{B works}) \][/tex]

The probability that alarm A works is the complement of the probability that it fails, which is [tex]\( 1 - 0.004 \)[/tex]. Similarly, the probability that alarm B works is  1 - 0.01 .

Thus, we have:

[tex]\[ P(\text{A works}) = 1 - 0.004 = 0.996 \] \[ P(\text{B works}) = 1 - 0.01 = 0.99 \][/tex]

Now we can calculate [tex]\( P(\text{both work}) \)[/tex]:

[tex]\[ P(\text{both work}) = 0.996 \times 0.99 \] \[ P(\text{both work}) = 0.98604 \][/tex]

Finally, we find the probability that at least one alarm fails:

[tex]\[ P(\text{at least one fails}) = 1 - 0.98604 \] \[ P(\text{at least one fails}) = 0.01396 \][/tex]

what is the difference between a composite number and a prime number?​

Answers

Answer:

Step-by-step explanation:

Prime numbers are numbers that are divisible by itself and '1'. This means prime numbers are numbers with just two factors while composite numbers are numbers that are divisible by more than two numbers, that is they have more than 2 factors.

Example of prime numbers are 5,7,11 etc. We see that these numbers are only divisible by themselves and by '1' while examples of composite numbers are 10, 15, 20, etc. We clearly see that these numbers have more than 2factors.

Prime numbers are divisible by only 2 numbers: 1 and themselves.

Composite numbers have 3 or more factors.

Hope this helps!

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Time value of money calculations can be solved using a mathematical equation, a financial calculator, or a spreadsheet. Which of the following equations can be used to solve for the present value of a perpetuity? PMT x {1 – [1 / (1+r)n1+rn ]} PV x (1+r)n1+rn FV / (1+r)n1+rn PMTr

Answers

The formula for the present value (PV) of a perpetuity is \[PV = \frac{FV}{(1 + r)^n}\]. Here option C is correct.

The formula for calculating the present value (PV) of a perpetuity is given by:

\[PV = \frac{FV}{(1 + r)^n}\]

Where:

PV (Present Value) is what we want to find.

FV (Future Value) is the fixed payment that will continue indefinitely.

r (Discount Rate) represents the interest rate or required rate of return.

n represents the number of time periods (infinite in the case of a perpetuity).

This formula takes into account the infinite nature of the perpetuity and discounts future cash flows to their equivalent value in today's dollars, considering the time value of money. The discount factor \(\frac{1}{(1 + r)^n}\) ensures that the cash flows in the future are worth less in present terms. Therefore, option C is correct.

Complete question:

Which of the following equations can be used to solve for the present value (PV) of a perpetuity?

A) \(PV = PMT \cdot \left(1 - \frac{1}{{(1 + r)^{n(1+r)}}}\right)\)

B) \(PV = PV_0 \cdot (1 + r)^n\)

C) \(PV = \frac{FV}{{(1 + r)^n}}\)

D) \(PV = PMT \cdot \frac{1 - \left(\frac{1}{{(1 + r)^{n(1+r)}}}\right)}{r}\)

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Express the confidence interval 0.333less thanpless than0.555 in the form ModifyingAbove p with caret plus or minus Upper E. ModifyingAbove p with caret plus or minus Upper Eequals nothingplus or minus nothing

Answers

Answer:

The confidence interval is (0.444 ± 0.111).

Step-by-step explanation:

The general form of a confidence interval for single proportion is: [tex](\hat p- E<p<p\hat + E)=\hat p \pm E[/tex]

The interval provided is: (0.333 < p < 0.555)

Then

[tex]\hat p-E=0.333...(i)\\\hat p + E = 0.555...(ii)[/tex]

Solving the two equation simultaneously:

Add (i) and (ii),

[tex]2\hat p=0.888\\\hat p=\frac{0.888}{2}\\ =0.444[/tex]

Substitute the value of [tex]\hat p[/tex] in (i) to compute the value of E:

[tex]\hat p-E=0.333\\0.444-E=0.333\\E=0.444-0.333\\=0.111[/tex]

Thus, the confidence interval is,

[tex](0.444-0.111<p<0.444+0.111)=0.444 \pm 0.111[/tex]

Whats an explicit rule for this? 1, -4, -9, -14, etc. Write an explicit formula for the nth term an.

Answers

Answer:

-5n + 6

Step-by-step explanation:

It goes up in the - 5 times tables and you have to add 6 to get the real answer.

Find the difference between numbers to find the n. (-5n bit)

A machine set to fill soup cans with a mean of 20 ounces and a standard deviation of 0.11 ounces. A random sample of 15 cans has a mean of 20.04 ounces. Should the machine be reset?

A. Yes, the probability of this outcome at 0.080, would be considered unusual, so the machine should be reset
B. No the probability of this outcome at 0.358 would be considered usual, so there is no problem
C. No, the probability of this outcome at 0.080, would be considered usual, so there is no problem
D. Yes, the probability of this outcome at 0.920 would be considered unusual, so the machine should be reset

Answers

Answer:

C. No, the probability of this outcome at 0.080, would be considered usual, so there is no problem

Step-by-step explanation:

To solve this problem, it is important to know the Central Limit Theorem and the Normal probability distribution.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], a large sample size can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]\frac{\sigma}{\sqrt{n}}[/tex]

Normal Probability Distribution

Problems of normally distributed samples can be 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.

When a probability is unusual?

A probability is said to be unusual if it is higher than 0.95 or lower than 0.05.

In this problem, we have that:

[tex]\mu = 20, \sigma = 0.11, n = 40, s = \frac{0.11}{\sqrt{15}} = 0.0284[/tex]

Should the machine be reset?

What is the probability of a mean of 20.04 or higher?

This is 1 subtracted by the pvalue of Z when X = 20.04. So

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

[tex]Z = \frac{20.04 - 20}{0.0284}[/tex]

[tex]Z = 1.41[/tex]

[tex]Z = 1.41[/tex] has a pvalue of 0.92.

So the probability of this outcome is 1-0.92 = 0.08 = 8%.

8% is still an usual probability.

So the correct answer is:

C. No, the probability of this outcome at 0.080, would be considered usual, so there is no problem

Final answer:

The sample mean of 20.04 ounces can be calculated using the z-score formula to determine if the machine should be reset. The probability of obtaining this sample mean is extremely close to 1, indicating it is likely to occur by random chance. Therefore, the machine does not need to be reset.

Explanation:

To determine if the machine should be reset, we can calculate the probability of obtaining a sample mean of 20.04 ounces or higher, assuming the machine is still set to the mean of 20 ounces. We can use the z-score formula to standardize the sample mean. The formula is z = (x - μ) / (σ / sqrt(n)), where x is the sample mean, μ is the population mean, σ is the standard deviation, and n is the sample size. Plugging in the values, we have z = (20.04 - 20) / (0.11 / sqrt(15)) = 5.45.

Next, we can find the probability associated with this z-score using a z-table or a calculator. From the z-table, we find that the probability is approximately 0.99999999.

Since the probability is extremely close to 1, which means it is very likely to occur by random chance, we can conclude that the sample mean of 20.04 ounces is not significantly different from the mean of 20 ounces. Therefore, there is no need to reset the machine.

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Historically, the proportion of people who trade in their old car to a car dealer when purchasing a new car is 48%. Over the previous 6 months, in a sample of 115 new-car buyers, 46 have traded in their old car. To determine (at the 10% level of significance) whether the proportion of new-car buyers that trade in their old car has statistically significantly decreased, what can you conclude concerning the null hypothesis?

Answers

Answer:

[tex]z=\frac{0.4 -0.48}{\sqrt{\frac{0.48(1-0.48)}{115}}}=-1.717[/tex]  

[tex]p_v =P(z<-1.717)=0.0429[/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 reject the null hypothesis, and we can said that at 5% of significance the proportion of people that have traded in their old car is lower than 0.48 or 48%.  

Step-by-step explanation:

Data given and notation

n=115 represent the random sample taken

X=46 represent the number of people that have traded in their old car.

[tex]\hat p=\frac{46}{115}=0.4[/tex] estimated proportion of people that have traded in their old car

[tex]p_o=0.48[/tex] is the value that we want to test

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

Confidence=90% or 0.9

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 less than 0.48.:  

Null hypothesis:[tex]p\geq 0.48[/tex]  

Alternative hypothesis:[tex]p < 0.48[/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{0.4 -0.48}{\sqrt{\frac{0.48(1-0.48)}{115}}}=-1.717[/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<-1.717)=0.0429[/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 reject the null hypothesis, and we can said that at 5% of significance the proportion of people that have traded in their old car is lower than 0.48 or 48%.  

A missile protection system consists of n radar sets operating independently, each with a probability of .9 of detecting a missile entering a zone that is covered by all of the units.
a If n = 5 and a missile enters the zone, what is the probability that exactly four sets detect the missile? At least one set?
b How large must n be if we require that the probability of detecting a missile that enters the zone be .999?

Answers

Answer:

a. probability that exactly four sets detect the missile is 0.06561

probability that at least 1 set detect the missile is 0.99999

b. n = 3

Step-by-step explanation:

a. The probability that exactly 4 sets with probability of detection being 0.9 and 1 set fail with probability of 1 - 0.9 = 0.1 is

0.9*0.9*0.9*0.9*0.1 = 0.06561

The probability of having at least 1 set detect the missile is the inverse of the probability of having none of the set detecting the missile, which means all of the set fail to detect the missile, which is

0.1*0.1*0.1*0.1*0.1 = 0.00001

So the probability that at least 1 set detect the missile is

1 - 0.00001 = 0.99999

b. For the system to have a success rate of 0.999, this means at least 1 radar could detect the missile with probability of 0.999, which means all of them can fail with probability of 0.001. For this to happen:

[tex]0.1^n = 0.001[/tex]

[tex](10^{-1})^n = 10^{-3}[/tex]

[tex]10^{-1n} = 10^{-3}[/tex]

[tex]-n = -3[/tex]

[tex]n = 3[/tex]

You need 3 radars

Final answer:

The probability that exactly four out of five radar sets detect a missile is about 0.33, while the probability that at least one set detects it is almost 1 (0.99999). In order to achieve a detection probability of .999 or higher, there should be at least 11 radar sets.

Explanation:

The subject matter of this question is in the realm of probability and statistics, specifically binomial distributions. Probability is the measure of the likelihood that an event will occur in a random experiment.

a) To find the probability that exactly four sets detect the missile, we use the formula for a binomial probability, that is P(X=k) = C(n, k) * (p^k) * ((1-p)^(n-k)), where n is the number of trials, k is the number of successes, p is the probability of success, and C(n, k) is the number of combinations of n items taken k at a time. So, the probability is C(5, 4) * (0.9^4) * ((1-0.9)^(5-4)) = 0.32805. The probability that at least one set detects the missile equals to 1 minus the probability that none of the sets detect the missile, which is 1-(0.1^5) = 0.99999.

b) In order to achieve a probability of at least .999 of detecting a missile, we'd need to solve the inequality 1-(1-p)^n >= .999 for n. This yields n as greater than or equal to log(.001)/log(.1), which rounded up to the nearest whole number is 11.

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The vertices of a triangle are given. Determine whether the triangle is an acute triangle, an obtuse triangle, or a right triangle. (-4, 0, 0), (0, 0, 0), (7, 2, 6)

Answers

Answer:

Obtuse triangle

Step-by-step explanation:

Given are the vertices of a triangle

Let A (-4, 0, 0),B (0, 0, 0),C(7, 2, 6)

Let us find angles between AB, BC and CA

AB = (4, 0,0): BC = (7,2,6) : CA = (11, 2,6)

Cos B = [tex]\frac{AB.BC}{|AB||BC|} \\[/tex]

B = arc cos [tex]\frac{AB.BC}{|AB||BC|} \\[/tex]=137 deg 54 min 7 sec

Similarly

A=29 deg 53 min 53 seconds

C = 12 deg 12 min 3 sec

Obtuse triangle since one angle > 90 degrees

Final answer:

To determine the type of triangle, find the lengths of the sides using the distance formula. Then compare the sum of squares of the two shortest sides with the square of the longest side.

Explanation:

To determine whether a triangle is acute, obtuse, or right, we need to find the lengths of its three sides and then use the Pythagorean theorem. The distance formula can be used to find the lengths of the sides by finding the distances between the given vertices. After finding the lengths, we can compare the sum of the squares of the two shortest sides with the square of the longest side to determine the type of triangle.

Using the distance formula, we find that the lengths of the sides are 4,7, and 9. The shortest side is 4, so we calculate the sum of the squares of 4 and 7, which equals 65. The square of the longest side (9) is 81. Since 65 < 81, the triangle is an acute triangle.

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Let R be the region bounded by the following curves. Find the volume of the solid generated when R is revolved about the​ x-axis. Recall that cosine squared x equals one half (1 plus cosine 2 x ). yequalscosine 21 x​, yequals​0, xequals0 Set up the integral that gives the volume of the solid.

Answers

Answer:

Volume of the solid generated = pi2/84 cubic unit

Step-by-step explanation:

The deatiled step and appropriate integration is donw as shown in the attached file.

Final answer:

To find the volume of the solid when the region bounded by the curves is revolved about the x-axis, use the disk method to integrate the cross-sectional areas of the disks formed. The limits of integration are determined by finding the intersection points of the curves. The formula for the cross-sectional area is A = πr^2, where r is the distance from the x-axis to the function y(x).

Explanation:

To find the volume of the solid when the region bounded by the curves is revolved about the x-axis, we can use the disk method. The disk method involves integrating the cross-sectional area of each disk formed by rotating a thin vertical strip of the region about the x-axis. The formula for the cross-sectional area of a disk is A = πr^2, where r is the distance from the x-axis to the function y(x).

First, we need to determine the limits of integration. The curves y = cos(21x) and y = 0 intersect at x = 0 and x = π/42. So we integrate from x = 0 to x = π/42.

The distance from the x-axis to the function y(x) is y(x) = cos(21x). Therefore, the cross-sectional area of each disk is A(x) = π[cos(21x)]^2. To find the volume, we integrate A(x) from x = 0 to x = π/42:

V = ∫0π/42π[cos(21x)]^2 dx

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Astronomers treat the number of stars in a given volume of space as a Poisson random variable. The density in the Milky Way Galaxy in the vicinity of our solar system is one star per 16 cubic light years.
How many cubic light years of space must be studied so that the probability of one or more stars exceeds 0.94?[Round your answer to the nearest integer.]

Answers

Answer:

t = 45 cubic light years to find a star with this certainty.

Step-by-step explanation:

The Poisson random probability equation is given by:

[tex]P(k events in interval t)=\frac{(\lambda t)^{k}e^{-\lambda t}}{k!}[/tex]

λ is the density (1/16 star/cubic light years)t is the parameter in cubic light years

We can use the next equation to quantify how many cubic light years of space must be studied so that the probability of one or more stars exceeds 0.94.

[tex]P(k\ge 1) \ge 0.94[/tex]

[tex]1-f(0)=1-\frac{(\frac{1}{16}*t)^{0}e^{-\frac{1}{16}*t}}{0!}=1-e^{-\frac{1}{16}*t}} \ge 0.94[/tex]

So, here we just need to solve it for t:

[tex]1-e^{-\frac{1}{16}*t}} \ge 0.94[/tex]

[tex]e^{-\frac{1}{16}*t}} \ge 0.06[/tex]

[tex]ln(e^{-\frac{1}{16}*t}}) \ge ln(0.06)[/tex]

[tex]-\frac{1}{16}*t \ge -2.8[/tex]

[tex]t \ge 44.8[/tex]

Therefore t = 45 cubic light years to find a star with this certainty.

I hope it helps you!

To find the volume of space where the probability of encountering one or more stars exceeds 0.94 in the Milky Way, use the inverse of the cumulative distribution function of the Poisson distribution, with the given star density of one per 16 cubic light years, and solve for the volume V such that the probability of zero stars is below 0.06.

In order to solve the problem of how many cubic light years of space must be studied so that the probability of one or more stars exceeds 0.94, we need to use the properties of the Poisson distribution. The Poisson distribution is often used for modeling the number of events in fixed intervals of time or space under certain conditions. If we let λ denote the average number of stars in a given volume, then for our Milky Way Galaxy in the vicinity of our solar system where the density is one star per 16 cubic light years, λ is 1/16 per cubic light year. The probability of finding no stars in a volume V is given by e^{-λV}. To find when the probability of one or more stars exceeds 0.94, we need to find V such that the probability of finding no stars is less than 0.06 (which is 1 - 0.94).

Let's calculate the volume V:

We first solve the inequality e^{-λV} < 0.06 for V.

Taking the natural logarithm of both sides gives us -λV < ln(0.06).

We then solve for V: V > ln(0.06) / -λ.

Substituting λ (1/16) gives us V > ln(0.06) / -(1/16).

Finally, calculate the numeric value and round to the nearest integer to find the minimum volume V that meets the requirement.

By performing these calculations, you can find how many cubic light years of space must be studied so that the probability of one or more stars exceeds 0.94.

Evaluate cos(sin^-1(3/7)). Please I really confused about how to solve it. ASAP!!!!!!

Answers

Answer:

2√10 / 7

Step-by-step explanation:

to solve cos(sin^-1(3/7))

we break it into simpler terms

sin^-1(3/7) ------ these will be taken as an angle when dealing with cos

sin Ф = opposite / hypothenus = 3/7

Using Pythagoras Theorem

Hypothenus ² = opposite² + adjacent ²

7² = 3² + a²

49 = 9 + a²

a² = 49 - 9 = 40

a = √40 = √2x2x10 = 2√10

cos Ф = adjacent / hypothenus = 2√10 / 7  

cos(sin^-1(3/7)) = 2√10 / 7  

The value of the given expression is 2√10 / 7.

What is trigonometric identity?

Trigonometry is the branch of mathematics that set up a relationship between the sides and angle of the right-angle triangles.

Trigonometric identities are equality conditions in trigonometry that hold for all values of the variables that appear and are defined on both sides of the equivalence. These are identities that, geometrically speaking, involve certain functions of one or more angles.

Solve cos(sin⁻¹(3/7)). Break it into simpler terms sin⁻¹(3/7) these will be taken as an angle when dealing with cos.

sin Ф = opposite / hypothenus = 3/7

Using Pythagoras Theorem

Hypothesis ² = opposite² + adjacent ²

7² = 3² + a²

49 = 9 + a²

a² = 49 - 9 = 40

a = √40 = √2x2x10 = 2√10

cos Ф = adjacent / hypothenus = 2√10 / 7  

cos(sin⁻¹(3/7)) = 2√10 / 7  

Hence, the value of cos(sin⁻¹(3/7)) will be 2√10 / 7.

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