HELPPPP! i will give brainliest Find the measure of the missing angle.

Yes, the normal distribution can be used to approximate the probability of at least 92 people.

To determine if the normal distribution can be used to solve this problem, we need to check if the sample size is sufficiently large and if the sample proportion is not too close to 0 or 1.

The sample size is not given in the problem statement, but we can assume that it is large enough for the normal distribution to be a reasonable approximation. A general rule of thumb is that the normal distribution can be used if the sample size is at least 30.

The problem states that the probability of a random person recognizing the McDonald's brand name is 0.95. We can interpret this as the sample proportion (p-hat) being equal to 0.95. The normal distribution can be used to approximate the probability of at least 92 people recognizing the brand name if the following conditions are met:

Since we can assume that the sample size is large enough, and both np >= 10 and n(1-p) >= 10, we can use the normal distribution to approximate the probability of at least 92 people recognizing the McDonald's brand name.

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Answer:

c

Step-by-step explanation:

because 8 is equal to 8. 0 and 1 are less than 8.

Answer: 1/50

Step-by-step explanation:

0.020 = 20/1000 = 1/50

Answer:

35%

Step-by-step explanation:

The number of yellow is 35% of the total items.

Answer:

Therefore, the cost of 2 1/2 metres of cloth at 47 5/4 rupee per metre is 955/8 rupee.

Step-by-step explanation:

We can solve this problem using multiplication and addition as follows:

The cost of 1 metre of cloth is 47 5/4 rupee.

So, the cost of 2 1/2 metres of cloth is:

2 1/2 * 47 5/4

To multiply mixed numbers, we first convert them to improper fractions.

2 1/2 = 5/2

47 5/4 = 191/4

So, 2 1/2 * 47 5/4 = 5/2 * 191/4

To multiply fractions, we multiply the numerators together and the denominators together.

5/2 * 191/4 = (5 * 191)/(2 * 4) = 955/8

Therefore, the cost of 2 1/2 metres of cloth at 47 5/4 rupee per metre is 955/8 rupee.

Answer:

Growth

Step-by-step explanation:

You can simply look at this and say that this is growth because the number in the parenthesis is greater than 1.00.

It would only be decay if the parenthesis^2 resulted in a number less than 1

Yes, if a figure can be rotated 360° to be mapped onto itself, it is considered to have rotational symmetry.

This is because a 360° rotation means that the figure will return to its original position, making it symmetrical. Rotational symmetry is a type of symmetry where a figure can be rotated about a central point and still look the same. The degree of rotational symmetry depends on the number of times a figure can be rotated to match its original appearance. Therefore, if a figure can be rotated 360° and maintain its original appearance, it is said to have rotational symmetry of degree 1. This is true regardless of the size, orientation, or position of the figure. Yes, a figure that can be rotated 360° to be mapped onto itself is considered to have rotational symmetry. Rotational symmetry occurs when an object can be rotated around a central point and still appear the same as its original position. In the case of a 360° rotation, the figure returns to its initial configuration, confirming its rotational symmetry.

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(a) The 92nd percentile of the number of calories is 524.3.

(b) The 30th percentile of the number of calories is 466.4.

(c) The third quartile of the number of calories is 502.1.

To find percentiles in a normally distributed population, we use the standard normal distribution and the z-score formula:

z = (x - μ) / σ

where;

To find the 92nd percentile of the number of calories:

We want to find the value x such that 92% of the servings have fewer calories than x.

This means that we need to find the z-score such that the area to the left of z is 0.92.

Using a standard normal distribution table or calculator, we can find that the z-score corresponding to an area of 0.92 is approximately 1.41.

Then, we use the z-score formula to solve for x:

1.41 = (x - 482) / 30

x - 482 = 42.3

x = 524.3

To find the 30th percentile of the number of calories:

We want to find the value x such that 30% of the servings have fewer calories than x.

This means that we need to find the z-score such that the area to the left of z is 0.30.

Using a standard normal distribution table or calculator, we can find that the z-score corresponding to an area of 0.30 is approximately -0.52.

Then, we use the z-score formula to solve for x:

-0.52 = (x - 482) / 30

x - 482 = -15.6

x = 466.4

To find the third quartile of the number of calories:

The third quartile, denoted Q3, is the value such that 75% of the servings have fewer calories than Q3.

This means that we need to find the z-score such that the area to the left of z is 0.75.

Using a standard normal distribution table or calculator, we can find that the z-score corresponding to an area of 0.75 is approximately 0.67.

Then, we use the z-score formula to solve for x:

0.67 = (x - 482) / 30

x - 482 = 20.1

x = 502.1

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The least number of miles she would have to drive per year to make leasing no more expensive than purchasing is 48500 miles.

Given:

She can lease a car for $420 per month (on an annual basis). Under this plan, the cost per mile (gas and oil) is $0.06. If she were to purchase the car, the fixed annual expense would be $4700, and other costs would amount to $0. 08 per mile.

Let x be the least miles.

420 * 12 + 0.06x < > 4700 + 0.08x

multiply by 100 on both sides.

504000+6x < > 470000+8x

97000 < > 2x

48500=x

Therefore the least number of miles she would have to drive per year to make leasing no more expensive than purchasing is 48500 miles.

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Answer:

2f =c

350c + 500f = 4800

Step-by-step explanation:

Twice as many cans of soup as frozen dinners

All food combined contain 4800 (mg of sodium)

2f =c

350c + 500f = 4800

These are the systems of equations.

Answer: Radius=19.2 diameter=38.39

Step-by-step explanation: :DDD

The null hypothesis for the single factor ANOVA states that all means are equally true.

The null hypothesis for a single-factor ANOVA (analysis of variance) states that all means are equal.

The alternative hypothesis, on the other hand, suggests that at least one of the means is different from the others.

The purpose of the ANOVA test is to determine whether there is sufficient evidence to reject the null hypothesis and conclude that there are significant differences between the means. A statistical formula used to compare variances across the means (or average) of different groups.

Hence, the statement is true .

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Answer:0.375

Step-by-step explanation:

3/4=0.75

0.75/2=0.375

(3/4)/2=0.375

Answer:

642000000000000000000000

Step-by-step explanation:

The compound proposition that is true is "p OR q".

To determine which compound proposition is true, we need to analyze the truth values of the individual propositions and apply logical operators to form compound propositions. Let's examine each compound proposition based on the given truth values of p, q, and r: p is true, q is false, and r is true.

1. Proposition 1: (p ∧ q) ∨ r

We have:

p is true (T)

q is false (F)

r is true (T)

Now let's evaluate the compound proposition:

(p ∧ q) ∨ r

Step 1: Evaluate (p ∧ q)

(p ∧ q) is false because q is false. (T ∧ F) is F.

Step 2: Evaluate (p ∧ q) ∨ r

Since (p ∧ q) is false (F) and r is true (T), (p ∧ q) ∨ r is true (T).

Therefore, Proposition 1, (p ∧ q) ∨ r, is true.

2. Proposition 2: ¬p ∧ (q ∨ r)

We have:

p is true (T)

q is false (F)

r is true (T)

Now let's evaluate the compound proposition:

¬p ∧ (q ∨ r)

Step 1: Evaluate ¬p

¬p is false because p is true. ¬T is F.

Step 2: Evaluate (q ∨ r)

(q ∨ r) is true because r is true. F ∨ T is T.

Step 3: Evaluate ¬p ∧ (q ∨ r)

Since ¬p is false (F) and (q ∨ r) is true (T), ¬p ∧ (q ∨ r) is false (F).

Therefore, Proposition 2, ¬p ∧ (q ∨ r), is false.

3. Proposition 3: (p ∨ q) ∧ r

We have:

p is true (T)

q is false (F)

r is true (T)

Now let's evaluate the compound proposition:

(p ∨ q) ∧ r

Step 1: Evaluate (p ∨ q)

(p ∨ q) is true because p is true. T ∨ F is T.

Step 2: Evaluate (p ∨ q) ∧ r

Since (p ∨ q) is true (T) and r is true (T), (p ∨ q) ∧ r is true (T).

Therefore, Proposition 3, (p ∨ q) ∧ r, is true.

Based on the given truth values of p, q, and r, Proposition 1 and Proposition 3 are true, while Proposition 2 is false.

It's important to note that the truth values of the individual propositions and the logical operators used to form the compound propositions determine their overall truth value. In this case, Proposition 1 and Proposition 3 have at least one true component, which makes them true. Proposition 2, on the other hand, has a false component, resulting in a false truth value.

Analyzing the truth values and evaluating compound propositions is a fundamental aspect of propositional logic. It allows us to reason about the relationships between propositions and determine the overall truth or falsity of complex statements based on the truth values of their components.

In this example, by carefully evaluating the truth values of p, q, and r and applying logical operators, we have determined the truth values of the compound propositions. This exercise demonstrates the importance of understanding the principles of propositional logic and how truth values interact when forming compound propositions.

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Find the area of the triangle and multiply by the length of the prism.

Area = 1/2 x 8x3 = 12 square yds.

Volume = 12 x 6 = 72 cubic yards.

Answer:

£28.8 Milllion

Step-by-step explanation:

£30,000,000 × 0.8 = £24,000,000 (Depreciates by 20%)

£24,000,000 × 1.2 = £28,800,000 (Appreciates by 20%)

A matrix consisting entirely of zeros is called a zero matrix, or an all-zero matrix.

It is denoted with the symbol O and can be written in a matrix form, such as O = [0 0 0 0] where the number of columns and rows depends on the size of the matrix. A zero matrix is a matrix which has all its elements equal to zero. It has a number of special properties that make it useful in linear algebra. For instance, the sum of any two zero matrices is a zero matrix, and any scalar multiple of a zero matrix is a zero matrix. Additionally, the product of two zero matrices is a zero matrix, and the product of a zero matrix and an identity matrix is a zero matrix. These properties make it useful in solving systems of linear equations where all the coefficients are zero. Finally, the inverse of a zero matrix does not exist since its determinant is zero.

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"Biocalculus: Calculus, Probability, and Statistics for the Life Sciences" by James Stewart and Troy Day is a comprehensive textbook designed to introduce the concepts of calculus, probability, and statistics within the context of life sciences.

"Biocalculus" is specifically tailored for students pursuing life science disciplines, such as biology, biochemistry, and genetics. The book covers essential mathematical topics including limits, derivatives, integration, and differential equations, emphasizing their relevance to biological phenomena and processes. The authors incorporate numerous examples and exercises that focus on real-world applications in areas such as population dynamics, genetics, epidemiology, and pharmacokinetics.

By integrating calculus with probability and statistics, the book equips students with the necessary tools to analyze and interpret data in the life sciences. It introduces key concepts such as probability distributions, hypothesis testing, regression analysis, and experimental design, highlighting their importance in biological research. The authors take a step-by-step approach, providing clear explanations and detailed calculations, ensuring that students grasp the mathematical concepts and their practical implications.

Overall, "Biocalculus: Calculus, Probability, and Statistics for the Life Sciences" serves as an invaluable resource for life science students, helping them develop a strong mathematical foundation and enabling them to apply quantitative methods effectively in their future research and careers.

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Answer:

1. point p is on the perpendicular bisector of AB¯¯¯¯¯- given

2. AXP≅BXP. definition of bisector

3. ∠PXA and ∠PXB are right angles. definition of perpendicular

4. ∠PXA≅ ∠PXB. All right angles are congruent.

5.PX¯¯¯¯¯≅PX¯¯¯¯¯ ​ Reflexive Property of Congruence

6.AXP≅AXQ. SAS Congruence Postulate

7.AX¯¯¯¯¯≅BX¯¯¯¯¯

8.Point P is equidistant from the endpoints of AB¯¯¯¯¯. Definition of equidistant

Step-by-step explanation:

Answer:

1. Point P is on the perpendicular bisector of AB¯¯¯¯¯. Given

2.   AX¯¯¯¯¯≅BX¯¯¯¯¯¯ . Definition of bisector

3. ∠PXA and ∠PXB are right angles . Definition of Perpendicular

4. ∠PXA and ∠PXB . All right angles are congruent.

5. ​ PX¯¯¯¯¯≅PX¯¯¯¯¯ ​. Reflexive Property of Congruence

6. △AXP≅△BXP . SAS Congruence Postulate

7. PA¯¯¯¯¯≅PB¯¯¯¯¯ . Corresponding parts of congruent triangles are congruent

8. Point P is equidistant from the endpoints of AB¯¯¯¯¯ . Definition of equidistant

Step-by-step explanation:

Answer:

A.

Step-by-step explanation:

The formula for trying to find the area of a circle is Area= r^2

Sooo:

Area=3.14 x 18 x 18

18 x 18 is the first part of the equation

=324

Then:

3.14(pi) x 324 = 1017.36 = 1017 ft2

Yes, it can be concluded at a 0.01 level of significance that there is a linear correlation between the two variables.

The following is a solution to the given question. The weight of a child riding a bike and the rolling distance achieved after going down a hill without pedaling is given by the data. The correlation coefficient between the two variables is to be tested to conclude if there is a linear correlation between the two variables at a 0.01 level of significance.

Linear correlation between the two variables A correlation coefficient, r, is used to determine if two variables have a linear correlation. A value of r=1 indicates a perfect positive correlation, while a value of r=-1 indicates a perfect negative correlation. A value of r=0 indicates no correlation between the two variables.To find the correlation coefficient, we use the following formula:

\($r = \frac{n\sum xy - \sum x\sum y}{\sqrt{(n\sum x^2 - (\sum x)^2)(n\sum y^2 - (\sum y)^2)}}$\)

Where

Weight, \($x$\)  Rolling Distance \($y$59 2683 4397 4956 20103 6587 4488 4891 4252 3963 3371 39100 4989 55103 5399 4274 3375 3089 30102 40103 3399 3386 3785 37\)

We need to find n,

\($\sum x$\) \($\sum y$\) \($\sum x^2$\)\($\sum y^2$\)

\(\sum xy$.n=30$\\ \sum x=2792$$\\ \sum y=1129$$\\ \sum x^2=221506$$\\ \sum y^2=86223$$\\ \sum xy=106883$r = 0.91\)

Correct to two decimal places.

Decision RuleWe have to check if the value of r lies in the critical region for a 0.01 level of significance. The value of r that separates the critical region from the non-critical region is found using the following formula:

\($$r_c = \frac{1}{\sqrt{n-2}}$$\)

Where n is the sample size.

Substituting the values, we get

\($$r_c = \frac{1}{\sqrt{30-2}} = 0.366$$\)

The critical region is when r is greater than 0.366 or less than -0.366.

Conclusion The value of r (0.91) is greater than the critical value (0.366). Hence, we conclude that there is a linear correlation between the two variables at a 0.01 level of significance. Therefore, the answer is: Yes, it can be concluded at a 0.01 level of significance that there is a linear correlation between the two variables.

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Answer:

The answer is Option A

Step-by-step explanation:

Start by dividing 54 by 6 which will give you 9

then divide b² by b^5 which will give you b³ at the denominator

then a^8÷a^-4

using indices...

=a^8-(-4)

=a^12

at the numerator

put everything together and you'll have...

9a^12/b³

A. \( \frac{9 \: {a}^{12} }{ {b}^{3} }\) ✅

\(\large\mathfrak{{\pmb{\underline{\red{Step-by-step\:explanation}}{\orange{:}}}}}\)

\(54 {a}^{8} {b}^{2} \div 6 {a}^{ - 4} {b}^{5} \)

To solve the expression in a simpler way, single out the like terms.

Now, we have

\( \frac{54}{6} . \frac{ {a}^{8} }{ {a}^{ - 4} } . \frac{ {b}^{2} }{ {b}^{5} } \\ \\ = 9 \: {a}^{8 - ( - 4)} {b}^{2 - 5} \\ \\ (∵ \frac{ {a}^{m} }{ {a}^{n} } = {a}^{m - n} ) \\ \\ = 9 \: {a}^{8 + 4} {b}^{ - 3} \\ \\ = 9 \: {a}^{12} {b}^{ - 3} \\ \\ ( \: or \: ) \\ \\ = \frac{9 \: {a}^{12} }{ {b}^{3} } \\ \\ (∵ {a}^{ - m} = \frac{1}{ {a}^{m} } )\)

\(\large\mathfrak{{\pmb{\underline{\orange{Happy\:learning }}{\orange{!}}}}}\)

The complement of set A, denoted by ​ A`, is the collection of all elements that belong to the universal set but are not part of set A. It's not necessary to mention the universe (also known as U) if it's understood which set of elements is being referred to.

The complement of a set A is the collection of all elements that belong to the universal set but not to set A. It is denoted as ​ A` and does not include any elements that are already in set A. The universal set, also known as U, contains all possible elements and is assumed to be known. Therefore, when referring to the complement of a set, it is not necessary to mention the universal set explicitly. The complement of a set is useful in determining the set of elements that are not part of a particular set, and it can be used in various mathematical operations.

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The time at which the ball was in the air for the two cases of being dropped and being caught are respectively; t = 0.05 s and t = 2.77 s

We are given the function to represent the given height as;

h(t)= -16t² + 45t + 3.5

Since the football is caught at a height of 5.5ft on the ball's descent, then;

-16t² + 45t + 3.5 = 5.5

⇒ -16t² + 45t - 2 = 0

From online quadratic equation solver, we have;

t = 0.05 s and t = 2.77 s

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