The length of a Texas Pee Wee football field is 218 feet greater than its width. The area of the field is 20,160 square feet
Please show work !!

Answer:

Part 1) [tex]AC=40\ units[/tex]

Part 2) [tex]DC=29\ units[/tex]

Part 3) [tex]m\angle ABE=39^o[/tex]

Part 4) [tex]m\angle BCE=51^o[/tex]

Step-by-step explanation:

we know that

A kite has two pairs of consecutive, congruent sides the diagonals are perpendicular and the non-vertex angles are congruent

Part 1) Find AC

we know that

BD is the axis of symmetry, bisects the diagonal AC

so

[tex]AE=EC[/tex]

we have

[tex]EC=20\ units[/tex]

[tex]AC=AE+EC[/tex] ----> by segment addition postulate

therefore

[tex]AC=20+20=40\ units[/tex]

Part 2) Find CD

we know that

CDE is a right triangle (the diagonals are perpendicular)

so

Applying Pythagorean Theorem

[tex]DC^2=EC^2+ED^2[/tex]

substitute the values

[tex]DC^2=20^2+21^2[/tex]

[tex]DC^2=841\\DC=29\ units[/tex]

Part 3) Find m∠ABE

we know that

In the right triangle ABE

[tex]51^o+m\angle ABE=90^o[/tex] ----> by complementary angles

[tex]m\angle ABE=90^o-51^o=39^o[/tex]

Part 4) Find m∠BCE

we know that

[tex]m\angle BCE=m\angle BAE[/tex] ----> diagonal BD is the axis of symmetry

we have

[tex]m\angle BAE=51^o[/tex]

therefore

[tex]m\angle BCE=51^o[/tex]

The measure of AC is 40 units.

The measure of the length DC is 29 units.

The measure of the angle ABE is 39 degrees.

The measure of the angle BCE is 51 degrees.

The missing lengths and angle measures in kite ABCD.

According to the question

The rhombus is a four-sided quadrilateral with all its four sides equal in length.

Rhombus is a kite with all its four sides congruent.

A kite is a special quadrilateral with two pairs of equal adjacent sides.

1. The measure of the length of AC is;

In the figure, BD is the axis of symmetry, bisects the diagonal AC.

Then,

[tex]\rm AE = EC[/tex]

And the measure of AC is,

[tex]\rm AC = AE+EC \\ \\ AC = 20+20 \\ \\ AC = 40 \ units[/tex]

The measure of AC is 40 units.

2. In the figure, CDE is a right triangle (the diagonals are perpendicular)

Then,

By applying the Pythagoras Theorem

[tex]\rm DC^2=EC^2+ED^2\\ \\ DC^2=20^2+21^2\\\\ DC^2 = 400+441 \\ \\ DC^2 = 841\\ \\ DC = 29 \ \rm units[/tex]

The measure of the length DC is 29 units.

3. In the right triangle ABE by the complementary angles;

[tex]\rm 51+ \angle ABE = 90\\ \\ \angle ABE=90-51\\ \\ \angle ABE=39 \ degrees[/tex]

The measure of the angle ABE is 39 degrees.

4. By the axis of symmetry the diagonal BD is;

[tex]\rm m \angle BCE = m \angle BAE\\\\ m \angle BCE = m \angle BAE = 51 \ degrees[/tex]

The measure of the angle BCE is 51 degrees.

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The answer & explanation for this question is given in the attachment below.

The number of aces in the first game and the number of spades in the 5th game follow a Hypergeometric Distribution while the number of games receiving at least one ace can be modeled by a Binomial distribution. The event of all cards being from the same suit can be thought of as a Uniform distribution.

a) The number of aces you get in the first game follows a Hypergeometric Distribution. In such a distribution, you are drawing cards without replacement. The parameters are N=52 (the population size), K=4 (the number of success states in the population i.e., the number of aces in a deck), and n=13 (the number of draws).

b) The number of games in which you receive at least one ace can be modeled by a Binomial distribution. Each game you play (out of 50) is a single trial, with the probability of success (getting at least one ace) being the same for every trial. The parameters are n=50 (the number of trials/games) and p (the probability of getting at least one ace).

c) The likelihood of all your cards being from the same suit in a game is heavily reliant on chance, can be modeled as a Uniform distribution given its rare occurrence. Essentially, the parameters would be minimum = 0 and maximum = 1. However, determining the parameters would require calculation of the specific probabilities, which is complex due to the nature of the game.

d) The number of spades you receive in the 5th game also follows a Hypergeometric distribution, similar to the situation in the first game. The parameters in this case are N=52, K=13 (number of spades in a deck), and n=13 (the number of drawn cards).

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The resulting probability is approximately 100%.

To find the probability that the plywood is less than 24mm thick, we need to calculate the z-score for 24mm using the given mean and standard deviation. The z-score formula is:

z = (x - mean) / standard deviation

Substituting the values, we get:

z = (24 - 5) / 0.2 = 95

We can then look up the z-score in a standard normal distribution table to find the corresponding probability.

In this case, the probability is practically 1 (or 100%) since 24mm is significantly greater than the mean.

Therefore, the probability that the plywood is less than 24mm thick is approximately 100%.

Answer:

Option A The linear model on tar content accounts for​ 92.4% of the variability in nicotine content.

Step-by-step explanation:

R-square also known as coefficient of determination measures the variability in dependent variable explained by the linear relationship with independent variable.

The given scenario demonstrates that nicotine content is a dependent variable while tar content is an independent variable. So, the given R-square value 92.4% describes that 92.4% of variability in nicotine content is explained by the linear relationship with tar content. We can also write this as "The linear model on tar content accounts for​ 92.4% of the variability in nicotine content".

The Upper R squared or the coefficient of determination here represents the percentage of the variability in the nicotine content that can be explained by the tar content in the regression model, which in this case is 92.4%.

In this context, the meaning of Upper R squared is represented by option A. The linear model on tar content accounts for 92.4% of the variability in nicotine content. This indicates that 92.4% of the change in nicotine content can be explained by the amount of tar content based on the linear regression model used. This measure is also known as the coefficient of determination. Meanwhile, options B, C, and D are not correct interpretations of the R squared in this context. Both B and D wrongly relate the percentage to the predictability of the data points and option C incorrectly associates this percentage with the residual magnitude.

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Answer:

a) 1.4% of the samples break during shipment

b) the probability is 4/7 ( 57.14%)

Step-by-step explanation:

a) defining the event B= the sample of laboratory glass breaks , then the probability is:

P(B)= probability that sample is shipped in small packaging * probability that the sample breaks given that was shipped in small packaging +  probability that sample is shipped in large packaging * probability that the sample breaks given that was shipped in large packaging = 0.40* 0.02 + 0.60*0.01 = 0.014

b) we can use the theorem of Bayes for conditional probability. Then defining the event S= the sample is shipped in small packaging . Thus we have

P(S/B)= P(S∩B)/P(B) = 0.40* 0.02 / 0.014= 4/7 ( 57.14%)

where

P(S∩B)= probability that sample is shipped in small packaging and it breaks

P(S/B)= probability that sample was shipped in small packaging given that is broken

By definition, the half life is a quantity is the time it takes to lose half of that quantity.

So, if the half life is 60 days, it means that after 60 days you have lost half the initial amount, i.e. you're left with 100 grams.

After another 60 days, you've lost, again, half of that amount, so you're left with 50 grams.

In other words, every time a half life period passes, you're left with half the quantity you had at the beginning of that period.

So, after two half-life periods (i.e. 120 days), you'll have half of the half of the initial quantity, i.e. one quarter.

Answer = 321.7

Explanation:

radius = y

height = [tex]4y^{2} - y^{3}[/tex]

area of cylinder = 2π*r*h

Integrate the area to calculate the volume:

[tex]= \int\limits^0_4 {2\pi(4y^{3} -y^{4}) } \, dy[/tex]

[tex]= 2\pi (\int\limits^0_4 {4y^{3}dy -\int\limits^0_4 y^{4} dy )} \,[/tex]

[tex]= 2\pi (256-\frac{1024}{5} )[/tex]

[tex]=\frac{512\pi }{5}[/tex]

[tex]= 321.7[/tex]

Final answer:

To compute the volume of the solid formed by rotating the region bounded by the curves x = 4y² − y³ and x = 0 around the x-axis, utilize the cylindrical shells method with the relevant volume formula for cylindrical shells and integrate over the intersecting interval of y-values.

Explanation:

Finding the Volume of a Solid of Revolution

To find the volume of the solid obtained by rotating the region bounded by the curves x = 4y2 − y3 and x = 0 about the x-axis using the method of cylindrical shells, we follow these steps:

The relevant formulas for the volume and surface area of a sphere are (4/3)πr3 and 4πr2, respectively. It's important to note that the volume depends on the cube of the radius R3, while the surface area is a function of the square of the radius R2.

Answer:

v_s,1 > v_s,2 > v_s,3

Step-by-step explanation:

Given:

- Material 1:

         modulus of elasticity = E_1

         density of material = p_1

- Material 2:

         modulus of elasticity = E_2

         density of material = p_2

- Material 3:

         modulus of elasticity = E_3

         density of material = p_3

- E_1 > E_2 > E_3

- p_1 < p_2 < p_3

Find:

- Which material has highest speed of sound from highest to lowest:

Solution:

- The relationship between velocity of sound in a material with its elastic modulus and density is:

                               v_s = sqrt ( E / p )

- Since , v_s is proportional to E^0.5 and inversely proportional to p^0.5, then we have:

                                E_1 > E_2 > E_3

                                E_1^0.5 > E_2^0.5 > E_3^0.5

and                         p_1 < p_2 < p_3

                                p_1^0.5 < p_2^0.5 < p_3^0.5

Divide the two:      (E_1 / p_1)^0.5 > (E_1 / p_1)^0.5 > (E_1 / p_1)^0.5      

Hence,                    v_s,1 > v_s,2 > v_s,3

Final answer:

To calculate the probability of the first failure of an electronic device occurring after 9 months and before 12 months, we use the exponential distribution formula. For part a, we raise the probability that one device surpasses 9 months to the power of five. For part b, we use the complementary probability that at least one device fails before 12 months.

Explanation:

The time-to-failure of an electronic device which follows an exponential distribution can be used to calculate probabilities for different time intervals. With a mean of 15 months, the rate [tex](\lambda\))[/tex] is the reciprocal of the mean, thus [tex]\(\lambda = 1/15\)[/tex]. Here's how we can calculate the requested probabilities:

For a sample of five such devices, assuming independence, we require all five devices to surpass 9 months for the first failure to occur after that time, thus we raise the probability found in part a to the power of five. Similarly, for the first failure to occur before 12 months, at least one device must fail before that time, so we use the complementary probability of all devices lasting longer than 12 months.

Let's calculate these probabilities using the exponential distribution formula.

Answer:A) A

B) B

C) A

Step-by-step explanation:Experimental unit is a unit of statistical analysis.

It is also a member in a set entities.

b) Treatment is a combination of factor levels. It is an independent variable and can be manipulated by the one doing the experiment.

c) Response variables is an independent variable in which changes can be made to effect a change in the result.

Factor is a circumstance that engenders to a result.

e) Placebo is an inert substance or treatment which delivers a therapeutic value.

The experimental terms are defined as follows:

(a) The definition of an Experimental Unit is A. A​ person, object, or some other​ well-defined item upon which a treatment is applied.

(b) The definition of treatment is C. Any combination of the values of the factors​ (explanatory variables).

(c) The definition of a response variable is A. The quantitative or qualitative variable for which the experimenter wishes to determine how its value is affected by the explanatory variable.

(d) The definition of a factor is A. A variable whose effect on the response variable is to be assessed by the experimenter.

(e) The definition of a Placebo is C. An innocuous​ medication, such as a sugar​ tablet, that​ looks, tastes, and smells like the experimental medication.

(f) The definition of Confounding is when A. The effect of two factors​ (explanatory variables on the response​ variable) cannot be distinguished.

A confounding factor affects the dependent and independent variables with spurious effects.

Thus, the terms have been correctly defined with the right options.

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The probability that exactly three out of six individuals have group A blood, with a 40 percent chance for each individual, is found using the binomial probability formula. The calculation yields approximately 27.648% as the probability for exactly three individuals having group A blood.

The question asks for the probability that exactly three out of six individuals have group A blood, given that 40 percent of all individuals have group A blood. This is a binomial probability problem because there are two outcomes (having group A blood or not) and a fixed number of trials (six individuals).

Let's denote X as the random variable representing the number of individuals with group A blood. The probability of success on any given trial is p = 0.40 (having group A blood). The probability of failure is q = 1 - p = 0.60 (not having group A blood).

The binomial probability formula is:

[tex]P(X = k) = C(n, k) * p^k * q^(n-k)[/tex]

where:

For our problem:

Plugging these values into the binomial formula gives:

First, calculate the combination:

C(6, 3) = 6! / (3! * (6-3)!) = 20

Then, calculate the probability:

[tex]P(X = 3) = 20 * (0.40)^3 * (0.60)^3 = 20 * 0.064 * 0.216 = 0.27648[/tex]

Hence, the probability that exactly three of the individuals have group A blood is approximately 0.27648 or 27.648%.

Answer: False

Step-by-step explanation:

To know if the circle passes through the given point, we simply insert the coordinates of the given point (5,6) into the general equation Of the Circle. If left hand side of the equation balances with the right hand side, then the circle passed through the point.

The equation of the circle is (x-2)² + (y-6)² = 4

By inserting the given coordinates (5,6) we have.

(5-2)² + (6-6)² = 3² =9

Since the answer gotten is not 4, then the circle does not pass through the point (5,6)

Answer:

There is an 88% probability that a course has a final exam or a research paper.

Step-by-step explanation:

We solve this problem building the Venn's diagram of these probabilities.

I am going to say that:

E is the probability that a course has final exam.

P is the probability that a course requires research paper.

We have that:

[tex]E = e + (E \cap P)[/tex]

In which e is the probability that a course has final exam but does not require research paper and [tex]E \cap P[/tex] is the probability that a course has both of these things.

By the same logic, we have that:

[tex]P = p + (E \cap P)[/tex]

(a) Find the probability that a course has a final exam or a research paper.

This is

[tex]Pr = e + p + (E \cap P)[/tex]

Suppose that 26% of courses have a research paper and a final exam.

This means that

[tex]E \cap P = 0.26[/tex]

43% of courses require research papers.

So [tex]P = 0.43[/tex]

[tex]P = p + (E \cap P)[/tex]

[tex]0.43 = p + 0.26[/tex]

[tex]p = 0.17[/tex]

71% of courses have final exams

So [tex]E = 0.71[/tex]

[tex]E = e + (E \cap P)[/tex]

[tex]0.71 = e + 0.26[/tex]

[tex]e = 0.45[/tex]

The probability is

[tex]Pr = e + p + (E \cap P) = 0.45 + 0.17 + 0.26 = 0.88[/tex]

There is an 88% probability that a course has a final exam or a research paper.

The probability that each of the balls will be of the same color can be calculated using combinations, while the probability that each of the balls will be of all different colors can be calculated using permutations. When sampling with replacement, the probabilities of selecting each color remain the same in each selection.

(a) Probability that each of the balls will be of the same color:

This can be calculated using the concept of combinations. There are a total of 19 balls in the urn. Let's calculate the number of ways to choose all 3 balls of the same color:

Summing up the number of ways for each color, we get the total number of ways to pick 3 balls of the same color. The probability will be this number divided by the total number of ways to pick any 3 balls from the urn, which is C(19, 3).

(b) Probability that each of the balls will be of all different colors:

This can be calculated using the concept of permutations. There are a total of 19 balls in the urn. Let's calculate the number of ways to choose 1 ball of each color:

Since these events are independent, we multiply the number of ways for each color. The probability will be this number divided by the total number of ways to pick any 3 balls from the urn, which is C(19, 3).

(c) Probability that each of the balls will be of the same color (sampling with replacement):

When sampling with replacement, each ball has the same probability of being chosen in each selection. So the probability of selecting 1 red ball, 1 blue ball, and 1 green ball is the product of the probabilities of selecting each color. The probability for each color is the number of balls of that color divided by the total number of balls in the urn. Therefore, the probability will be (5/19) * (6/19) * (8/19).

(d) Probability that each of the balls will be of all different colors (sampling with replacement):

When sampling with replacement, the probability of each color being chosen in each selection remains the same. Therefore, the probability of selecting 1 red ball, 1 blue ball, and 1 green ball is the product of the probabilities of selecting each color. The probability for each color is the number of balls of that color divided by the total number of balls in the urn. Therefore, the probability will be (5/19) * (6/19) * (8/19).

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Answer:

[tex] 8.637 \leq \sigma^2 \leq 28.93[/tex]

[tex] 2.939 \leq \sigma \leq 5.379[/tex]

Step-by-step explanation:

Data given and notation

s represent the sample standard deviation

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

n=23 the sample size

Confidence=95% or 0.95

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 mean or variance 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.

The Chi Square distribution is the distribution of the sum of squared standard normal deviates .

Calculating the confidence interval

The confidence interval for the population variance is given by the following formula:

[tex]\frac{(n-1)s^2}{\chi^2_{\alpha/2}} \leq \sigma \leq \frac{(n-1)s^2}{\chi^2_{1-\alpha/2}}[/tex]

The sample standard deviation for this case was s = 3.8

The next step would be calculate the critical values. First we need to calculate the degrees of freedom given by:

[tex]df=n-1=23-1 =22[/tex]

Since the Confidence is 0.95 or 95%, the value of [tex]\alpha=0.05[/tex] and [tex]\alpha/2 =0.025[/tex], and we can use excel, a calculator or a tabele to find the critical values.  

The excel commands would be: "=CHISQ.INV(0.025,22)" "=CHISQ.INV(0.975,22)". so for this case the critical values are:

[tex]\chi^2_{\alpha/2}=36.78[/tex]

[tex]\chi^2_{1- \alpha/2}=10.98[/tex]

And replacing into the formula for the interval we got:

[tex]\frac{(22)(3.8)^2}{36.78} \leq \sigma^2 \leq \frac{(22)(3.8)^2}{10.98}[/tex]

[tex] 8.637 \leq \sigma^2 \leq 28.93[/tex]

Now we just take square root on both sides of the interval and we got:

[tex] 2.939 \leq \sigma \leq 5.379[/tex]

To find the probability of selling more than 4 properties in one week, use the binomial probability formula for each number of sales above 4 and sum them, or subtract the sum of probabilities of 4 or fewer sales from 1.

To compute the probability of selling more than 4 properties in one week, given that the chance of selling any one property is 50% and is independent of selling another property, we can use the binomial probability formula. In our scenario, we have a total of 14 properties, and the random variable X represents the number of properties sold in a week.

The binomial probability formula is:

P(X = k) = (n choose k) * p^k * (1-p)^(n-k)

Where:

However, instead of calculating the probability of selling exactly k properties, we are interested in selling more than 4 properties. This means we need to calculate the probabilities for selling 5, 6, ..., up to 14 properties and sum them up. Alternately, we can calculate 1 minus the probability of selling 4 or fewer properties to save time, since the probabilities must sum to 1.

Answer:

The answer to your question is below

Step-by-step explanation:

In Mayan notation there are only 3 symbols

   dot   .    means one

   line   ---   means five

  snail          means zero

And the are three levels,     the lower means     x 1

                                              the first means       x 20

                                              the second means  x 400

                                              the higher means    x 8000

Then, 135 is lower than 400, so we must start in the first level and need to divide 135 by 20.                         6

                                        20    135

                                                   15

Finally place 6 in the fist level and 15 in the lower lever, like this

And 120 + 15 = 135.          

Final answer:

To convert 135 to Mayan notation, one must work with a base-20 system. In this system, 135 is broken down to (6 x 20) + 15, which is written in Mayan as a bar and three dots on top, and below that, six dots.

Explanation:

The Maya used a vigesimal (base-20) numeral system for their calculations, which is different from our familiar base-10 system. To convert the number 135 to Mayan notation, you need to express it in base-20.

135 in base-20 is calculated as:

In Mayan notation, numbers are written vertically with the largest value at the top, so 135 would be represented with a bar and three dots on top (for 15), and under that, six dots (for 6).

The answer is a) [tex]X=X_1 +X_2 +X_3+..X_n[/tex]  b) The expression  is

[tex]E[X] = \dfrac{1}{n+m} +\dfrac{1}{n+m-1} +....+ \dfrac{1}{m+1}[/tex].

Given:

An urn contains n+m balls of which n is red and m is black

a)

Expressing X in terms of the defined random variables:

Let be the indicator random variable for the event that red ball i is taken before any black ball is chosen. It takes the value 1 if this event occurs and 0 otherwise.

Now, the value of X is the number of red balls removed before the first black ball is chosen. This can be expressed as the sum of the individual indicator random variables for each red ball:

[tex]X=X_1 +X_2 +X_3+..X_n[/tex]

b)

Find E[X] (expected value of X):

The expected value of a sum of random variables is the sum of the expected values of those random variables. To find E[X],

Find the expected value of each indicator random variable and then sum them up.

Therefore, the expected value   [tex]X_i[/tex] is:

[tex]E[X_i] = 1. \dfrac{1}{n+m-i+1} + 0\cdot \dfrac{m}{n+m-i+1}[/tex]

[tex]= \dfrac{1}{n+m-i+1}[/tex]

Now, to find  E[X], we sum up the expected values of the indicator random variables for all red balls:

[tex]E[X] = E[X_1]+E[X_2]+E[X_3]+.....+E[X_n][/tex]

Substitute the values of [tex]E[X_i][/tex] into the sum and simplify:

[tex]E[X] = \dfrac{1}{n+m} +\dfrac{1}{n+m-1} +....+ \dfrac{1}{m+1}[/tex]

a) [tex]X=X_1 +X_2 +X_3+..X_n[/tex]  b) [tex]E[X] = \dfrac{1}{n+m} +\dfrac{1}{n+m-1} +....+ \dfrac{1}{m+1}[/tex]

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X can be expressed as X = R_1 + 2R_2 + 3R_3 + ... + nR_n. To find E[X], use the linearity of expectation and the probabilities of R_i.

To determine E[X], we need to express X in terms of the random variables and then find the expected value. Let R_i denote the event that red ball i is taken before any black ball is chosen. The expression for X is:

To find the expected value, we use the linearity of expectation. Since the probabilities for each R_i are the same, we have:

Now, we need to determine the probabilities of R_i. Since the balls are drawn without replacement, the probability that red ball i is drawn before any black ball is chosen is:

Substituting this probability into the expression for E[X], we get:

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Answer:

$568.148

Step-by-step explanation:

We will relate the loan (X) with their nominal annual rate converted semiannually:

Jennifer's loan, [tex]X = 800(1+{\frac{j}{2}})^{-10*2}[/tex]

Brian's loan, [tex]X = 1,120(1+{\frac{2j}{2}})^{-10*2}[/tex]

Since Brain and Jennifer took the same amount loan, the two equations of semi annual rates can be combined thus:

[tex]X = 800(1+{\frac{j}{2}})^{-20}} = 1,120(1+{\frac{2j}{2}})^{-20}\\= {\frac{800}{1,120}}(1+{\frac{j}{2}})=(1+{\frac{2j}{2}})[/tex]

For simplicity, we will use "Y" to represent 0.714  (i.e:  [tex]{\frac{800}{1,120}} = 0.714[/tex] )

Therefore, continuing with the equation above:

[tex]Y + {\frac{Yj}{2}}=1+j\\2Y+Yj=2+2j\\2Y+Yj-2j=2\\Yj-2j=2-2Y\\j(Y-2)=2-2Y\\j={\frac{2-2Y}{Y-2}}[/tex]

substituting the real value of Y (0.714) into the equation, we have:

[tex]j = {\frac{2-(2*0.714)}{0.714-2}}\\={\frac{2-1.428}{-1.286}}\\={\frac{0.572}{-1.286}}\\ =-0.445[/tex]

Solving for the value of X using j, we have:

[tex]X(1+{\frac{j}{2}})=800\\X=568.148[/tex]

This is a mathematical problem about compound interest and loan repayment. It creates two equations based on the given scenario. These equations can be solved to find the initial loan amount X.

This question pertains to the concepts of compound interest and loan repayment in mathematics. Given the terms, we can use the formula for the future value of a loan: FV = P(1 + r/n) ^(nt). Here, FV is the future value of the loan, P is the principal loan amount, r is the annual interest rate, n is the number of times that interest is compounded per time t, and t is the time the money is invested for.

According to the problem, the nominal semi-annual rate charged to Jennifer is exactly half of the rate charged to Brian. Hence, if we denote the rate for Brian as 2r, the rate for Jennifer would be r. We know Jennifer's payment is 800 and Brian's is 1,120; these are the future values of their respective loans.

So, we get two equations from this problem:

1. X(1 + r/2)^(2*10) = 800

2. X(1 + 2r/2)^(2*10) = 1,120

You can solve these equations to find the value of X, which represents the amount they borrowed initially.

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Answer:

[tex]P(k) = \frac{(n C k) [(N-n) C (m-k)]}{(NCm)}[/tex]

Step-by-step explanation:

Step 1: Number of possible combination of selecting ‘m’ deer in second sample

Total number of deer are N and therefore the combinations can be calculated as (N С m).  

Step 2: Number of possible combination of marked deer ‘k’ in second sample

Total number of marked deer in total population is ‘n’. Therefore, the possible number of selecting marked deer is (n C k).

Step 3: Number of possible combination unmarked deer in second sample

Since we have already calculated the total combinations of selecting marked deer in the second sample. Hence, we have to calculate the total unmarked deer in total population which is N-n and number of unmarked deer in the second sample which is m-k.

Therefore, total possible combination of unmarked deer in second sample is [(N-n) C (m-k)].

Step 4: Probability of selecting unmarked deer in the second sample is

Let the probability of selecting unmarked deer in the second sample be P(k)

Therefore,

                                 [tex]P(k) = \frac{(n C k) [(N-n) C (m-k)]}{(NCm)}[/tex]

Answer:

a) y = 7.74*x + 7.5

b)  y = 1.148*x + 6.036

Step-by-step explanation:

Given:

                                  f(x) = 6 - 10*x^2

                                  g(x) = 8 - (x-2)^2

Find:

(a) The line simultaneously tangent to both graphs having the LARGEST slope has equation

(b) The other line simultaneously tangent to both graphs has equation,

Solution:

- Find the derivatives of the two functions given:

                                f'(x) = -20*x

                                g'(x) = -2*(x-2)

- Since, the derivative of both function depends on the x coordinate. We will choose a point x_o which is common for both the functions f(x) and g(x). Point: ( x_o , g(x_o)) Hence,

                                g'(x_o) = -2*(x_o -2)

- Now compute the gradient of a line tangent to both graphs at point (x_o , g(x_o) ) on g(x) graph and point ( x , f(x) ) on function f(x):

                                m = (g(x_o) - f(x)) / (x_o - x)

                                m = (8 - (x_o-2)^2 - 6 + 10*x^2) / (x_o - x)

                                m = (8 - (x_o^2 - 4*x_o + 4) - 6 + 10*x^2)/(x_o - x)

                                m = ( 8 - x_o^2 + 4*x_o -4 -6 +10*x^2) /(x_o - x)

                                m = ( -2 - x_o^2 + 4*x_o + 10*x^2) /(x_o - x)

- Now the gradient of the line computed from a point on each graph m must be equal to the derivatives computed earlier for each function:

                                m = f'(x) = g'(x_o)

- We will develop the first expression:

                                m = f'(x)

                                ( -2 - x_o^2 + 4*x_o + 10*x^2) /(x_o - x) = -20*x

Eq 1.                          (-2 - x_o^2 + 4*x_o + 10*x^2) = -20*x*x_o + 20*x^2

And,

                              m = g'(x_o)

                              ( -2 - x_o^2 + 4*x_o + 10*x^2) /(x_o - x) = -20*x

                              -2 - x_o^2 + 4*x_o + 10*x^2 = -2(x_o - 2)(x_o - x)

Eq 2                       -2 - x_o^2 + 4*x_o+ 10*x^2 = -2(x_o^2 - x_o*(x + 2) + 2*x)

- Now subtract the two equations (Eq 1 - Eq 2):

                              -20*x*x_o + 20*x^2 + 2*x_o^2 - 2*x_o*(x + 2) + 4*x = 0

                              -22*x*x_o + 20*x^2 + 2*x_o^2 - 4*x_o + 4*x = 0

- Form factors:       20*x^2 - 20*x*x_o - 2*x*x_o + 2*x_o^2 - 4*x_o + 4*x = 0

                              20*x*(x - x_o) - 2*x_o*(x - x_o) + 4*(x - x_o) = 0

                               (x - x_o)(20*x - 2*x_o + 4) = 0  

                               x = x_o   ,     x_o = 10x + 2    

- For x_o = 10x + 2  ,

                               (g(10*x + 2) - f(x))/(10*x + 2 - x) = -20*x

                                (8 - 100*x^2 - 6 + 10*x^2)/(9*x + 2) = -20*x

                                (-90*x^2 + 2) = -180*x^2 - 40*x

                                90*x^2 + 40*x + 2 = 0  

- Solve the quadratic equation above:

                                 x = -0.0574, -0.387      

- Largest slope is at x = -0.387 where equation of line is:

                                  y - 4.502 = -20*(-0.387)*(x + 0.387)

                                  y = 7.74*x + 7.5          

- Other tangent line:

                                  y - 5.97 = 1.148*(x + 0.0574)

                                  y = 1.148*x + 6.036

Check the picture below.

as we can see, the triangular prism is really just 3 rectangles and 2 triangles stacked up to each other at the edges, so if we simply get the area of each of those five figures and sum them up, that's the surface area of the triangular prism.

[tex]\bf \stackrel{\textit{three rectangles' area}}{(17\cdot 11)+(16\cdot 11)+(17\cdot 11)}~~+~~\stackrel{\textit{two triangles' area}}{\cfrac{1}{2}(16)(15) + \cfrac{1}{2}(16)(15)} \\\\\\ 187+176+187+120+120\implies 790[/tex]

Answer:

Step-by-step explanation:

Given that in a high school graduating class of 202 students, 95 are on the honor roll. Of these, 71 are going on to college, and of the other 107 students, 53 are going on to college.

Total students = 202

Honor roll = 95

College going out of honor = 71

Non college going out of honor = 24

Not in honor roll = 107

Not going to college from not in honour = 53

The probabilities that the person chosen is

(a) going to college,  = [tex]\frac{71+53}{202} \\=0.614[/tex]

(b) not going to college, =[tex]\frac{202-124}{202} \\=0.485[/tex]

(c) on the honor roll, but not going to college

=[tex]\frac{24}{202} \\=0.119[/tex]

Final answer:

The probabilities for a student selected at random from the class are: going to college, not going to college, and being on the honor roll but not going to college, calculated based on provided numbers for a graduating class of 202 students.

Explanation:

To solve this problem, we first need to understand the given information about the high school graduating class consisting of 202 students, with 95 on the honor roll and 107 not on the honor roll. Out of those on the honor roll, 71 are going to college, and of those not on the honor roll, 53 are going to college. Let's calculate the probabilities for each scenario.

Probability of Going to College

Total students going to college = Students on the honor roll going to college + Students not on the honor roll going to college = 71 + 53 = 124

Probability = (Total students going to college) / (Total students) = 124 / 202

Probability of Not Going to College

Total students not going to college = Total students - Total students going to college = 202 - 124 = 78

Probability = 78 / 202

Probability of Being on the Honor Roll but Not Going to College

Total students on the honor roll but not going to college = Total students on the honor roll - Students on the honor roll going to college = 95 - 71 = 24

Probability = 24 / 202

Answer:

the probability to be accepted is 0.302 (30.2%) (many will be rejected)

Step-by-step explanation:

assuming that the rate of 4% applies to the 60 tablets then since each tablet behaves independently, the random variable X= number of tablets with defects out of 60 tablets has a binomial distribution , where:

p(X)=n!/((n-x)!*x!)*p^x*(1-p)^(n-x)

where

n= total number of tablets tested = 60

x = number of defective tablets

p= probability to be defective = 0.04

then in order to be accepted x≤0 , then the probability that the batch is accepted Pa is

Pa=P(x≤1) = P(0) + P(1) = (1-p)^n + n*p*(1-p)^(n-1)

replacing values

Pa= (1-p)^n + n*p*(1-p)^(n-1) =  0.96^60 + 60*0.04*0.96^59 = 0.302 (30.2%)

then the probability to be accepted is  0.302 (30.2%) (many will be rejected)

Answer:

2683

Step-by-step explanation:

Using the linear regression equation that predict the relationship between the weight of the luggage and the total number of passenger y = 103 + 30x, we can plug in the number of passenger x = 86 to predict the weight of the luggage on a flight:

y = 103 + 30*86 =  2683

Answer:

Step-by-step explanation:

Fractions are used in telling time.

Fractions are used to determine discounts when there is sales going on.

Fraction is used to represent part of whole .

Fractions are used in baking to tell how much of an ingredient to use.

Answer:

b)continous

Step-by-step explanation:

A continuous data is a finite number within a chosen range example temperature range.

Answer:

The information above is just a part of a long question.The main question is  found in the attached as well as the answer following a step by step methodical approach.

Step-by-step explanation:

Take a good at the full question before venturing into the statements prepared so as to have a thorough understanding of the requirements and how the answers provided have touched upon the requirements.

Answer:

0.10865 killograms

Step-by-step explanation:

calculating the liquid mass of ammonia removed through the bottom value from a rigid tank at constant temperature.

Given:

temperature: [tex]T=70 F[/tex]

quality : 50% = 0.5

initial mass: [tex]m1= 4.5 lbm[/tex]

to find the removed liquid mass first we have to find total volume from which we can find remaining mass. as the tang is rigid the temperature and volume remains constant.

by taking the difference of mass we can determine the mass of liquid removed.

 we have two phases at temperature [tex]T= 70 F[/tex] with specific volume for liquid  [tex]vf=0.02631 ft^3/lbm[/tex]  and specific volume for vapor is  [tex]vg=2.3098 ft^3/lbm[/tex] .

The Volume in the initial state is given by, (Using definition of specific volume)

                                          [tex]V= m1v1[/tex]

 using [tex]v1=x(vf+vg)[/tex]

                                    [tex]V= m1x(vf+vg)[/tex]

substituting [tex]m1= 4.5 lbm\\[/tex] , [tex]vf= 0.02631 ft^3/lbm[/tex] , [tex]vg=2.3098 ft^3/lbm[/tex]

we get

        [tex]V= (4.5 lbm)(0.5)(0.02631 ft^3/lbm +2.3098 ft^3/lbm)[/tex]  

finally          [tex]V=5.2625 ft^3[/tex]  

we know the formula to find liquid mass is

[tex]mass =density *volume[/tex]

density of ammonia is  [tex]0.73 kg/m^3[/tex]

inserting the values into the formula we get the value for liquid mass removed through the valve.

[tex]m = (0.73 kg/m^3)*(5.25625 ft^3)[/tex]

the final answer is

                           [tex]m= 0.10865 kg[/tex]

Answer: a) Food and performance b) Randomized Experiment c) Yes d) Age, type of food

Step-by-step explanation:

a) The explanatory variable in this case is the food and sleep hours given to the groups and the response variable is the performance or the reaction time.

b) It is a randomized experiment as the people are given food and water and is under the influence of the study head.

c) From the detailed summary given, we can conclude that eating late worsens the effects of alcep depreviation as the group A was not given food and performed better than the group B who which had access to food and water.

d.Confounding variables are the age 21-50, the gender of people who took part in study and the type of food. Because changing these will result in different results.

The study examines the effects of eating late at night on sleep-deprived individuals' reaction time and attention lapses. It was a randomized experiment that concluded that eating late at night worsens these effects. Confounding variables may exist.

a. The explanatory variable in this study is the access to food and drink at night, and the response variables are the participants' reaction time and attention lapses.

b. This is a randomized experiment because the participants were randomly assigned to either group A (water only) or group B (unlimited access to food and drink).

c. Based on the results of the study, we can conclude that eating late at night worsens some of the typical effects of sleep deprivation, specifically reaction time and attention lapses.

d. There are likely to be confounding variables in this study, such as individual differences in metabolism or other lifestyle factors that could impact the participants' performance.