True or false: If we leave off the error term from the population linear model, the left hand side of the equation is now the expected value of Y for a given x value.

The distribution (or scattering) of IQ scores approximates a bell-shaped curve, also called a normal distribution or Gaussian distribution.

Normal distribution, also known as Gaussian distribution, is a type of probability distribution that is commonly used in statistical analysis. It is a continuous probability distribution with a bell-shaped curve that is symmetrical around the mean, or average, of the data.

The shape of the normal distribution curve is determined by two parameters: the mean and the standard deviation. The mean represents the central tendency of the data, while the standard deviation measures the spread of the data around the mean. The standard deviation also determines the width of the curve. In a normal distribution, about 68% of the data falls within one standard deviation of the mean, about 95% falls within two standard deviations of the mean, and about 99.7% falls within three standard deviations of the mean.

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The group size is given as follows:

12 people.

The number of visitors for each day is given as follows:

The group size must be the same for each day, hence it is the greatest common factor of 108 and 156.

The greatest common factor between two amounts is obtained factoring them simultaneously by prime factors, as follows:

108 - 156|2

54 - 78|2

27 - 39|3

9 - 13

There is not any more number by which 9 and 13 are divisible, hence the group size is given as follows:

gcf(9, 13) = 2² x 3 = 12 people.

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There are 275 different desserts at this ice cream shop.

If the ice cream shop made 22 different flavors of ice cream, you would have 22 choices for a single flavor in a cone or a cup. For a sundae, you could choose a combination of two or more flavors. Let's assume you choose two flavors for your sundae.

You would have 22 options for the first flavor and 21 options for the second flavor since you can't repeat the same flavor.

So, the total number of different desserts you could have is:
22 (single flavor in a cone) + 22 (single flavor in a cup) +[tex]22 (\frac{21}{2} )[/tex] (two flavors in a sundae)
= 22 + 22 + 231
= 275

Therefore, you could have 275 different desserts at this ice cream shop.

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The length of the parking lot is 10 kilometers.

To find the length of the parking lot, we can use the formula for the area of a rectangle:

Area = Length x Width

We know that the area of the parking lot is 10 square kilometers and the width is 1 kilometer. Substituting these values into the formula, we get:

10 km² = Length x 1 km

To solve for the length, we can divide both sides of the equation by 1 kilometer:

Length = 10 km² ÷ 1 km

Simplifying the right side of the equation, we get:

Length = 10 km

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The dependent variable in Max's scenario is the cups of coffee sold. This variable is dependent on the temperature, which is the independent variable.

Max believes that the sales of coffee at his coffee shop depend on the temperature. Therefore, he is interested in studying how the temperature affects the number of cups of coffee sold.

In the given sample of 5 days, Max has recorded the number of cups of coffee sold and the corresponding temperature on each of those days. By analyzing this data, Max can determine the relationship between the two variables. He can use statistical tools to find out how much of the variation in the number of cups of coffee sold can be explained by the temperature.

If Max finds a strong positive correlation between the temperature and the number of cups of coffee sold, it would indicate that customers prefer to buy more coffee on hotter days. On the other hand, if there is no significant correlation between the two variables, it would mean that temperature has no effect on coffee sales at Max's coffee shop. This information can help Max make informed decisions about pricing, marketing, and inventory management.

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Since the point of rotation is (3, 2), a sequence of transformations that can be used to carry ABCD onto itself include the following:

A. Reflection across the line x = 3

B. Rotation of 180°.

In Mathematics and Geometry, a transformation can be defined as the movement of a point from its initial position to a new location. This ultimately implies that, when a function or object is transformed, all of its points would also be transformed.

In this scenario, a line of reflection that would map geometric figure ABCD onto itself is an equation of the line that passes through AC.

In this context, we can reasonably infer and logically deduce that a reflection across the line x = 3, a reflection across the line y = 2, and rotation of 180° are sequence of transformations that can only be used to carry or map quadrilateral ABCD onto itself because the point of rotation is (3, 2).

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The specific percentage may vary depending on the study, but it highlights the financial challenges faced by students while pursuing their education.

The National Center for Education Statistics reported that of college students work to pay for tuition and living expenses. Assume that a sample of college students was used in the study, it is important to note that the results of the study may not accurately represent the entire population of college students.

Additionally, it would be important to know the size and characteristics of the sample in order to determine the reliability and validity of the findings. It is also possible that other factors may impact a college student's decision to work, such as financial aid, family support, and personal preferences. Therefore, further research may be necessary to fully understand the relationship between college students and work.

The National Center for Education Statistics (NCES) conducted a study on college students and found that many of them work to pay for tuition and living expenses. This data is usually gathered from a sample of college students to provide an accurate representation of the entire population.

*complete question: The National Center for Education Statistics reported that of college students work to pay for tuition and living expenses. Assume that a sample of college students was used in the report and state what the specific percentage highlights.

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When a previous result is found to be an error and a corrected result is obtained, it is important to appropriately handle and document the old result. Here are some steps to consider:

1. Acknowledge the error: Clearly identify and acknowledge that the previous result was incorrect. It is important to be transparent and honest about the mistake.

2. Retract or correct the old result: Communicate the error and provide the corrected result. This can be done through formal channels, such as retracting a publication or notifying relevant parties about the correction. Make sure the corrected information reaches the appropriate audience.

3. Provide an explanation: Offer an explanation of why the error occurred. Was it a calculation mistake, data entry error, or any other factor that led to the incorrect result? Providing an explanation can help prevent similar errors in the future and maintain trust in the accuracy of your work.

4. Update relevant documentation: Update any reports, documents, or records that include the old result. Ensure that the corrected result is reflected in all relevant materials to avoid confusion and provide accurate information to others who may refer to those documents.

5. Learn from the mistake: Take the opportunity to learn from the error and implement measures to prevent similar mistakes in the future. This may include double-checking calculations, implementing quality control processes, or seeking feedback and review from colleagues.

By acknowledging the error, correcting the result, and taking steps to prevent similar mistakes in the future, you can maintain integrity and trust in your work.

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The value of x -intercepts of the graph of the function are,

⇒ x = 1.75 and x = - 6.75

We have to given that;

Function is,

⇒ f (x) = x² + 5x - 12

Now, We can simplify for x - intercept by substitutive f (x) = 0;

⇒ f (x) = x² + 5x - 12

⇒ 0 = x² + 5x - 12

⇒ x = - 5 ± √(5)² - 4×1×- 12 / 2

⇒ x = - 5 ± √25 + 48 / 2

⇒ x = - 5 ± √73 / 2

⇒ x = - 5 ± 8.5 / 2

⇒ x = (- 5 + 8.5)/2

⇒ x = 3.5 / 2

⇒ x = 1.75

⇒ x = (- 5 - 8.5) / 2

⇒ x = - 13.5 / 2

⇒ x = - 6.75

Thus, The value of x -intercepts of the graph of the function are,

⇒ x = 1.75 and x = - 6.75

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The box plot most resembles the information above is given by the image of Box plot A, option 1.

A box plot or boxplot is a visual representation of the location, dispersion, and skewness groups of quartiles of numerical data. The box-and-whisker plot and box-and-whisker diagram are other names for box plots, which can additionally have lines (referred to as whiskers) extending from the box to indicate variability beyond the top and lower quartiles.

Santa Clara Country,  CA has approximately 27873 Japanese - Americans. Their ages are as follows :

Age Group  Percent of Community

0-17 18.9

18-24 8.0

25-34 22.8

35-44 15.0

45-54 13.1

55-64 11.9

 10.3

Summary of the data is ,

Minimum = 0

Maximum = 100

Q1 = 24

Q2 = 34

Q3 = 53

Inter Quartile Range = IQR

= Q3 - Q1 = 53 - 24 = 29 .

IQR = 29

According to above summery of the data,

The most resembles Boxplot is A.

Hence , Choose  option 1) Boxplot A is the answer.

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Based on the provided information, the box plot that best represents the data is Box plot A, which corresponds to option 1.

The box plot, also known as a box-and-whisker plot, visually displays the distribution of numerical data through quartiles, indicating the location, spread, and skewness of the data. It consists of a box that represents the interquartile range (IQR), with a line inside indicating the median. Whiskers extend from the box to show the range of the data, excluding outliers.

For the given data on the ages of Japanese-Americans in Santa Clara County, CA, the summary reveals the following statistics: the minimum age is 0, the maximum age is 100, and the quartiles are Q1 = 24, Q2 = 34, and Q3 = 53. The interquartile range (IQR) is calculated as Q3 - Q1, resulting in an IQR of 29.

Considering the characteristics of the data summary, the box plot that closely matches this description is Box plot A. Therefore, the correct answer is option 1) Boxplot A.

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True. Statistical process control is commonly used in service industries, including blood testing labs, to monitor and analyze processes and determine normal levels of variation.

These normal levels of variation are often used as the basis for setting specifications and determining if a process is in control or out of control. Therefore, they can be considered the "voice of the specification" in service industries.

True. Statistical process control is used in service industries like a blood testing lab to determine normal levels of variation. Normal levels of variation are considered the voice of the specification. This helps to maintain quality and control the process.

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The hypothesis that is typically used to test the claim is the null hypothesis, which asserts that the average time spent by students studying for a midterm exam is indeed 3 hours. The alternative hypothesis would be that the average time spent is either greater or less than 3 hours.

The null hypothesis is usually denoted as H0 and the alternative hypothesis as Ha. In this case, we can write:

H0: The average time spent by students studying for a midterm exam is 3 hours.

Ha: The average time spent by students studying for a midterm exam is not 3 hours.

To test this hypothesis, a statistical test can be performed, such as a t-test or a z-test, depending on the sample size and the population parameters. The results of the test will determine whether the null hypothesis can be rejected or not. If the null hypothesis is rejected, it means that there is evidence to suggest that the average time spent studying is different from 3 hours. If the null hypothesis is not rejected, it means that there is not enough evidence to suggest that the average time spent studying is different from 3 hours.

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Answer:

7 + x/9 = 3

x/9 = -4, so x = -36

The requried, The range is the best measure of variability, and it equals 45. Option B is correct.

The appropriate measure of variability for the data shown is the range, which is the difference between the largest and smallest values in the dataset. From the stem-and-leaf plot, the smallest value is 20 and the largest value is 65. Therefore, the range is 65 - 20 = 45. Thus, the statement "The range is the best measure of variability, and it equals 45" is correct.

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The store owner should mix 73 ounces of spearmint tea with 28 ounces of peppermint tea to obtain the same revenue as selling them separately.

Let's assume that x ounces of spearmint tea are mixed with (101-x) ounces of peppermint tea to obtain a total of 101 ounces of the mixture.

The total cost of the spearmint tea would be 3.23x dollars and the total cost of the peppermint tea would be 5.25(101-x) dollars.

To obtain a selling price of 3.80 an ounce, the total revenue from selling 101 ounces of the mixture would be 3.80(101) = 383.80 dollars.

Let's assume that the store owner sells the spearmint and peppermint tea separately without mixing them. To obtain the same revenue, the revenue from selling the spearmint tea and the peppermint tea should be equal to 383.80 dollars.

Let's assume that y ounces of spearmint tea are sold at 3.23 an ounce and z ounces of peppermint tea are sold at 5.25 an ounce. The total revenue from selling y ounces of spearmint tea would be 3.23y dollars and the total revenue from selling z ounces of peppermint tea would be 5.25z dollars.

We want to find y and z such that 3.23y + 5.25z = 383.80 and y + z = 101.

We can solve this system of equations to find y and z:

y + z = 101

3.23y + 5.25z = 383.80

Multiplying the first equation by 3.23, we get:

3.23y + 3.23z = 327.23

Subtracting this equation from the second equation, we get:

2.02z = 56.57

z = 28

Substituting z = 28 into the first equation, we get:

y + 28 = 101

y = 73

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The  coordinate of A is (-10, 10).

We have,

Point B has coordinates (2, 1).

x coordinate of A is -10.

and, distance between point A and point B is 15 units.

Using Distance Formula

d= √(-10-2)² + (y - 1)²

15² =  12² + (y-1)²

225 - 144 = (y - 1)²

(y -1)² = 81

y - 1 = 9

y = 9 + 1

y= 10

Thus, the coordinate of A is (-10, 10).

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The equation representing the relation of proportional relationship in the form of y = px is equal to y = 120x.

Values of x and y are ,

x - 3, 5, 8, 9

y - 360, 600, 960, 1080

The equation that represents the proportional relationship,

To determine the constant of proportionality.

By finding the ratio of any two corresponding values of x and y.

Let us choose the first two values to express in the form of y =px we have,

x = 3, y = 360

x = 5, y = 600

The ratio of y to x in both cases is the same

y/x = 360/3

     = 120

y/x = 600/5

     = 120

This implies,

The constant of proportionality is 120.

Now ,write the equation in the form y = px,

where p is the constant of proportionality.

y = 120x

Equation holds for the other values of x and y given in the table we have,

x = 8, y = 960

120x = 120(8)

        = 960

x = 9, y = 1080

120x = 120(9)

       = 1080

Therefore, the equation that represents the proportional relationship is equal to y = 120x.

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To visualize the letter-grade distribution, you can use a plotting library like Matplotlib to create a histogram of the data. The x-axis would represent the letter-grades (e.g., A, B, C, D, F) and the y-axis would represent the number of grades in each category. This histogram can be saved as an image file or displayed on the screen for the teacher to review.

To create this program, you will first need to define the letter-grade boundaries and their corresponding score ranges. For example, an "A" may be between 90-100, a "B" may be between 80-89, and so on. Once these boundaries are set, you can prompt the teacher to input the exam scores for each student in their class and convert those scores to their respective letter-grade using conditional statements.
After all the scores have been converted to letter-grades, you can then calculate how many grades are in each letter-grade category by using a loop to count the number of grades that fall within each score range. This information can be stored in a list or dictionary for later use.
Finally, to visualize the letter-grade distribution, you can use a plotting library like Matplotlib to create a histogram of the data. The x-axis would represent the letter-grades (e.g., A, B, C, D, F) and the y-axis would represent the number of grades in each category. This histogram can be saved as an image file or displayed on the screen for the teacher to review.

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A graph that represent the quadratic equation x² + 8x + 3 is shown in the image attached below.

In Mathematics and Geometry, the graph of a quadratic function would always form a parabolic curve because it is a u-shaped. Based on the given quadratic function, we can logically deduce that the graph would be an upward parabola because the coefficient of x² is positive and the value of "a" is greater than zero (0).

Since the leading coefficient (value of a) in the given quadratic function y = x² + 8x + 3 is positive 1, we can logically deduce that the parabola would open upward and the y-intercept is given by the ordered pair (0, 3).

In conclusion, the turning point is given by the ordered pair (-4, -13).

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The probability of winning free coffee for a year using digits 1-6 with no repeats, create a 4-digit passcode is 1/360.

To calculate the probability of winning the free coffee for a year with a 4-digit passcode using digits 1-6 with no repeats, follow these steps:
1. Determine the total number of possible passcodes: Since there are 6 digits to choose from and no repeats are allowed, there are 6 options for the first digit, 5 options for the second digit, 4 options for the third digit, and 3 options for the fourth digit. So, the total number of passcodes is 6 x 5 x 4 x 3 = 360 passcodes.
2. Since there is only one correct passcode to win the free coffee for a year, the probability of winning is the ratio of the successful outcomes (1) to the total possible outcomes (360).
So, the probability of winning free coffee for a year with your 4-digit passcode using digits 1-6 with no repeats is 1/360.

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You can get 7 orders of fries for $10 and still have some money left over. If the price per order stays constant, this function can be used to determine how many orders of fries can be purchased with any given sum of money.

To write a function that calculates the number of orders of fries that can be bought with a given amount of money, we need to divide the amount by the cost per order of fries. We can express this function in mathematical notation as:

n(x) = floor(x / 1.29)

where n(x) is the number of orders of fries that can be bought with x dollars, and floor(x / 1.29) is the result of dividing x by the cost per order of fries and rounding down to the nearest integer.

To use this function to find the number of orders of fries that can be bought with $10, we simply need to substitute 10 for x in the formula:

n(10) = floor(10 / 1.29) = floor(7.75193798) = 7

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When continuous data points such as age or GPA are divided into groups, they have been reduced to discrete data.

This process of dividing continuous data into discrete categories is called "discretization" or "binning". Discretization can be useful in some cases, such as when we want to simplify data analysis or make data more understandable to non-experts. However, it can also lead to information loss, as we are losing some of the detailed information contained in the original continuous data.

Continuous data is a type of data that can take on any value within a given range. For example, age can be any value between 0 and infinity, and GPA can be any value between 0 and 4.0 (or higher, in some cases). These types of data are typically measured using numerical scales, such as inches, centimeters, or percentages.

However, when we divide continuous data points into groups, we are creating categories that can only take on certain values. For example, if we divide ages into groups of 10 years (e.g., 0-9, 10-19, 20-29, etc.), we are reducing the continuous data to a set of discrete categories. Similarly, if we divide GPAs into categories (e.g., 0-1.0, 1.1-2.0, 2.1-3.0, etc.), we are also reducing the continuous data to a set of discrete categories.

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Here is the completed frequency tree:

    120

    / \

   B   G

        /   \

    70      50

      |         / \

     52     18 32

               |      |

             26  28

B represents the number of boys, which is 120 - 70 = 50. G represents the number of girls, which is 70. Of the girls, 52 completed the homework, so 70 - 52 = 18 did not complete the homework.

Of the boys, 26 completed the homework, so 50 - 26 = 24 did not complete the homework. The total number of students who did not complete the homework is 18 + 28 + 24 = 70, which is the same as the total number of girls.

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Buss and Plomin's model of temperament proposes that there are three general temperaments: emotionality, activity, and sociability.

These temperaments are believed to be genetically based and to influence an individual's personality traits and behaviors throughout their life. Emotionality refers to an individual's tendency to experience strong emotional reactions, while activity refers to an individual's level of energy and impulsiveness.

Emotionality refers to an individual's tendency to experience and express emotions, such as fear, anger, and sadness.

Activity refers to an individual's level of physical and mental energy, and their tendency to seek out stimulation and engage in activities.

Sociability refers to an individual's preference for social interaction, including their level of interest in and enjoyment of socializing with others.

According to Buss and Plomin's model, these three temperaments are considered to be broad, genetically influenced traits that are present in varying degrees in every individual, and which can have a significant impact on a person's personality and behavior throughout their life.

Sociability, on the other hand, refers to an individual's degree of interest in social interaction and the degree to which they seek out social stimulation.

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The expected number of times that they will end up flipping the coin [tex]\boxed{N}$.[/tex]

Let P be the probability that Alpha goes bankrupt before either player reaches 2N dollars. We can calculate this probability using a recursive approach. Let p_i be the probability that Alpha goes bankrupt given that Alpha has i dollars and Beta has 2N-i dollars. Then we have:

[tex]$p_i = \frac{1}{2}p_{i-1} + \frac{1}{2}p_{i+1}$[/tex]

The first term represents the probability that Alpha loses the next flip and ends up with i-1 dollars, while the second term represents the probability that Alpha wins the next flip and ends up with i+1 dollars. The boundary conditions are[tex]p_0 = 1[/tex] (Alpha is already bankrupt) and [tex]$p_{2N} = 0$[/tex] (Alpha has reached 2N dollars). We can solve this system of equations to find:

[tex]$p_i = \frac{i}{2N}$[/tex]

This result can be verified by induction.

Now, let[tex]$E_i$[/tex]be the expected number of flips required to reach the endpoint of the game (either bankruptcy or 2N dollars) starting from the state where Alpha has i dollars and Beta has [tex]$2N-i$[/tex]dollars. Then we have:

[tex]$E_i = 1 + \frac{1}{2}E_{i-1} + \frac{1}{2}E_{i+1}$[/tex]

The first term represents the flip that is about to be made, while the second and third terms represent the expected number of flips required to reach the endpoint starting from the new state after the next flip. The boundary conditions are [tex]$E_0 = E_{2N} = 0$[/tex](we have already reached an endpoint). We can solve this system of equations to find:

[tex]$E_i = 2N\left(1 - \frac{i}{2N}\right)^2$[/tex]

Therefore, the expected number of flips required to reach the endpoint of the game starting from the initial state where both players have N dollars is:

[tex]$E = E_N = 2N\left(1 - \frac{1}{2}\right)^2 = \boxed{N}$[/tex]

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The height of the cell tower is 324 feet.

Let h be the height of the cell tower in feet. From the given information, we can set up the following two proportions:

[tex]\frac {72}h= \frac {length of tower shadow} {height of tower}[/tex]

[tex]\frac {6}{27}= \frac{length of tree shadow}{height of tree}[/tex]

We can simplify the second proportion:

[tex]\frac{6}{27}= \frac2{9}= \frac{length of tree shadow}{height of tree}[/tex]

Now we can use the first proportion to solve for the height of the tower:

[tex]\frac{h}{72}= \frac9{2}[/tex]

Cross-multiplying, we get:

[tex]2h=72\times9=6482[/tex]

Dividing both sides by 2, we get:[tex]h=6482=324[/tex]

Therefore, the height of the cell tower is 324 feet.

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Thus, the probability of a randomly chosen worker being a college graduate and married is 0.22, or 22%.

To determine the probability of a randomly chosen worker being married and a college graduate, we need to use conditional probability.

Let's start by finding the probability of a worker being a college graduate and married.

According to the data, 44% of the workers are college graduates and 72% are married. We don't know the overlap between these two groups yet, so let's use a formula for conditional probability:

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

In this case, let A be the event of being married, and B be the event of being a college graduate. So,

P(married and college graduate) = P(married|college graduate) x P(college graduate)

We know that half of the college graduates are married, so P(married|college graduate) = 0.5. We also know that P(college graduate) = 0.44. So,

P(married and college graduate) = 0.5 x 0.44 = 0.22

Therefore, the probability of a randomly chosen worker being a college graduate and married is 0.22, or 22%.

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The distance frοm the starting point to the end of driving will be equal to 19.9 miles.

The shortest path an οbject can take to get from one place to another is referred tο as "displacement". Tο put it simply, it is regarded to be the mοdification of the object's locatiοn. It is a vector quantity because of its magnitude and direction.

As per the given informatiοn in the question,

Start driving north fοr 6 miles then turn right and ride for 19 miles.

So the displacement frοm the starting point by Pythagoras' theorem will be:

h² = 6² + 19²

h = √36 + 361

h = 19.9 miles.

Therefοre, the distance from the starting point will be 19.9 miles.

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Complete Question

You start driving nοrth for 6 miles, turn right, and drive east for another 19 miles. At the end οf driving, what is your straight line distance from your starting point? Round to the nearest tenth of a mile.​

The probability that a randomly selected cookie is not safe for Sean to eat is 0.60.

To find the probability that a cookie contains chocolate or nuts, we need to add the probability of the cookie containing chocolate to the probability of the cookie containing nuts, and then subtract the probability of the cookie containing both chocolate and nuts. This is because if a cookie contains both chocolate and nuts, it is counted twice when we add the probability of chocolate and the probability of nuts.

Let's call the event of a cookie containing chocolate "C", the event of a cookie containing nuts "N", and the event of a cookie containing both "C∩N". Then, we can use the formula:

P(C ∪ N) = P(C) + P(N) - P(C ∩ N)

We are given that P(C) = 0.36, P(N) = 0.12, and P(C∩N) = 0.08. Substituting these values into the formula, we get:

P(C ∪ N) = 0.36 + 0.12 - 0.08 = 0.40

Therefore, the probability that a cookie contains chocolate or nuts (but not both) is 0.40.

However, Sean is allergic to both chocolate and nuts, so he cannot eat any cookies that contain either chocolate or nuts. To find the probability that a randomly selected cookie is not safe for Sean to eat, we can subtract the probability of a cookie containing neither chocolate nor nuts from 1:

P(not safe for Sean) = 1 - P(neither C nor N)

To find P(neither C nor N), we can use the complement rule:

P(neither C nor N) = 1 - P(C ∪ N)

Substituting the value we calculated earlier for P(C ∪ N), we get:

P(neither C nor N) = 1 - 0.40 = 0.60

for such more question on probability

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