You've decided you want a plant for your room. At the gardening store, there are
4
44 different kinds of plants (tulip, fern, cactus, and ficus) and
4
44 different kinds of pots to hold the plants (clay pot, plastic pot, metal pot, and wood pot).
If you randomly pick the plant and the pot, what is the probability that you won't get a clay pot or a cactus?

Answer:

80%

Step-by-step explanation:

We Know

There are 260 students at the rally.

208 students are wearing purple.

What percent are wearing purple?

We Take

208 divided by 260, time 100 = 80%

So, 80% students wearing purple.

Answer:

3/7

Step-by-step explanation:

The total is 7 blocks. There are three stars. Probability is PART/WHOLE.

3/7

The solution to the system of equations is x = 6, y = 22.

What is solution?

We can start by setting the two expressions for y equal to each other:

x² - 3x + 16 = 9x - 20

Next, we can rearrange the equation into standard quadratic form:

x² - 12x + 36 = 0

Now we can factor the quadratic:

(x - 6)² = 0

This equation has only one solution, x = 6. To find the corresponding value of y, we can substitute x = 6 into either of the original equations:

y = 6² - 3(6) + 16 = 22

Therefore, the solution to the system of equations is x = 6, y = 22.

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The probability of the spinner landing on keychain is 1/4 or 0.25, which means that for every 4 spins, the spinner is expected to land on keychain once on average.

The measure of the likelihood that an event will occur is known to be Probability.

This is a number between 0 and 1, where 0 represents an impossible event (has no chance of occurring) and 1 represents a definite event (100% chance of occurring).

An event with a probability of 0.5 is equally likely to occur and not to occur. 

To find the probability of the spinner landing on keychain, we need to first determine the total number of spins and the number of times the spinner landed on keychain.

From the given data, we can see that the spinner was spun 8 times, and it landed on keychain twice. Therefore, the probability of the spinner landing on keychain is:

Probability of keychain = Number of times the spinner landed on keychain / Total number of spins

Probability of keychain = 2/8 = 1/4

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We can estimate the expected number of clutch plates with

wear of more than 203 mm as:

[tex]0.7 \times \text{total number of clutch plates}[/tex]

To estimate the average wear and variance, we first calculate the sample

mean and sample variance:

Sample mean:

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

[tex]x_i = \frac{204.5 + 231.1 + 157.5 + 190.5 + 261.6 + 127.0 + 216.6 + 172.7 + 243.8 + 291.0}{10} = 213.3[/tex]

Sample variance:

[tex]s^2 = \frac{1}{n-1}\sum_{i=1}^{n}[/tex]

[tex](x_i - \bar{x})^2 = \frac{(204.5 - 213.3)^2 + (231.1 - 213.3)^2 + ... + (291.0 - 213.3)^2}{9} = 3415.5[/tex]

To estimate the proportion of clutch plates with wear of more than 203

mm, we first need to calculate the sample proportion:

[tex]{number of linings with wear more than 203 mm}{\text{total number of linings}} = \frac{7}{10} = 0.7[/tex]

To estimate the proportion for a large set of clutch plates, we assume

that the sample proportion is equal to the population proportion.

Therefore, we can estimate the expected number of clutch plates with

wear of more than 203 mm as:

[tex]0.7 \times \text{total number of clutch plates}[/tex]

However, we don't know the total number of clutch plates in the

population, so we cannot provide a specific estimate.

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A triangle has two angles that are 73° and 24° in size. The third angle is 83 degrees in length.

The sum of all the angles in a triangle is always 180 degrees. So, we can utilize this fact to get the third angle's measurement:

Let's call the third angle "x". Then we have:

73° + 24° + x = 180°

Simplifying this equation, we get:

97° + x = 180°

Subtracting 97 degrees from both sides, we get:

x = 83°

Therefore, the measure of the third angle is 83 degrees.

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The correct order of the set of numbers from least to greatest is 2 3 over 4, 2.71 repeating 71, 5 over 2, square root 5, the correct option is D..

To order the given set of numbers from least to greatest, we need to compare their values. We start by noticing that 2 and 3 over 4 are equivalent to 2.75. Next, we compare the values of the remaining numbers. Since the square root of 5 is approximately 2.236 and 5 over 2 is equivalent to 2.5, we have:

2 3 over 4 < 2.71 repeating 71 < 2.5 < square root 5

Therefore, the set of numbers in order from least to greatest is 2, 3 over 4, 2.71 repeating 71, 5 over 2, square root 5.

Ordering the set of numbers from least to greatest, we get:

2 3 over 4, 2.71 repeating 71, square root 5, 5 over 2.

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a) The predicted GPA for a student with Verbal SAT score of 500 is 2.9805.

b) The residual for this student is -0.2805.

To calculate the predicted GPA for a student with Verbal SAT score of 500, we need to plug in the value of 500 into the regression equation:

GPA = 2.0336 + 0.0018929 × VerbalSAT

Thus, the predicted GPA for a student with Verbal SAT score of 500 is

GPA = 2.0336 + 0.0018929 × 500 = 2.9805

To calculate the residual for this student, we subtract the predicted GPA from the actual GPA

Residual = Actual GPA - Predicted GPA

Residual = 2.7 - 2.9805 = -0.2805

Therefore, the residual for this student is -0.2805.

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I have solved the question in general, as the given question is incomplete.

The complete question is:

A straight line linear regression analysis was carried out, using Verbal SAT score, VerbalSAT (values can range from 0 to 800), to predict grade point average in college, GPA, for first-year BU students (GPA values can range from 0 to 4). The sample size is 345 first-year BU students. The following are the least squares estimates of the coefficients of the linear regression model and the estimates of their standard error: Variable DF Parameter Standard Estimate Error 1 2.0336 0.1621 Intercept VerbalSAT (Slope) 1 0.0018929 0.0002709 . . Calculate the predicted GPA and the residual for a student with Verbal SAT score of 500. GPA was 2.7 for this student.

Answer:

[tex]\frac{1}{8}[/tex]

Step-by-step explanation:

Since there are four answer choices for question one, the chance of picking the correct answer is [tex]\frac{1}{4}[/tex]. However, there is also another question. That question is a true-or-false question, meaning that there is only two options. Therefore, the probability of picking the correct answer is [tex]\frac{1}{2}[/tex]. To find the probability of picking both correctly, you multiply the two together. [tex]\frac{1}{4} * \frac{1}{2} = \frac{1}{8}[/tex], so the answer is [tex]\frac{1}{8}[/tex].

Step-by-step explanation:

10^2   +    10^6    +   10^1    =    10 ^(2+6+1)  = 10 ^9

1. It is not unusual for Joe to roll a four twice in six attempts because a die has 6 sides, so the probability of rolling a four is 1/6 (one in six).

2. If Joe rolled a four three times in six attempts, it would still not be considered unusual because when the probability of rolling a four three times is slightly lower than rolling it twice, it is still not considered a very low probability or unusual occurrence.

It is not unusual for Joe to roll a four twice in six attempts. Here's why:
1. A die has 6 sides, so the probability of rolling a four is 1/6 (one in six).
2. When rolling the die six times, the probability of rolling a four twice can be calculated using the binomial probability

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

where n is the number of trials,

k is the number of successful outcomes,

p is the probability of success, and q is the probability of failure (1-p).
3. In this case, n=6, k=2, p=1/6, and q=5/6.

So, [tex]P(X=2) = (6C2) * (1/6)^2 * (5/6)^4[/tex] ≈ 0.2009 or 20.09%.
4. Since 20.09% is not a low probability, it is not unusual for Joe to roll a four twice in six attempts.
If Joe rolled a four three times in six attempts, it would still not be considered unusual. Here's why:
1. Using the same binomial probability formula as before, we now have k=3.
2. [tex]P(X=3) = (6C3) * (1/6)^3 * (5/6)^3[/tex] ≈ 0.1550 or 15.50%.
3. While the probability of rolling a four three times is slightly lower than rolling it twice, it is still not considered a very low probability or unusual occurrence.

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Answer:

Using the inscribed angle theorem, we know that the measure of an inscribed angle is equal to half the measure of the central angle that intercepts the same arc. So, we need to find the central angle measure for each of the inscribed angles.

For angle a, the central angle measure is 80°, so the measure of angle a is (1/2)*80° = 40°.

For angle b, the central angle measure is 120°, so the measure of angle b is (1/2)*120° = 60°.

For angle c, the central angle measure is 40°, so the measure of angle c is (1/2)*40° = 20°.

For angle d, the central angle measure is 140°, so the measure of angle d is (1/2)*140° = 70°.

For angle e, the central angle measure is 80°, so the measure of angle e is (1/2)*80° = 40°.

For angle f, the central angle measure is 60°, so the measure of angle f is (1/2)*60° = 30°.

Therefore, the degree measures of the angles are:

a = 40°

b = 60°

c = 20°

d = 70°

e = 40°

f = 30°

Step-by-step explanation: Did try my best

There are 848 different combinations of games that you can attend if you want to go to at least 4 games out of the 10 scheduled games.

If you want to attend at least 4 games out of the 10 scheduled games, there are several different combinations that you can attend.

To calculate the total number of combinations, we can use the combination formula

nCr = n! / r! × (n-r)!

where n is the total number of games (10), and r is the number of games you want to attend (4).

First, let's calculate the number of combinations of attending exactly 4 games

10C4 = 10! / 4! × (10-4)! = 210

This means that there are 210 different combinations of attending exactly 4 games out of the 10 scheduled games.

Next, let's calculate the number of combinations of attending 5, 6, 7, 8, 9, or all 10 games

10C5 = 10! / 5! × (10-5)! = 252

10C6 = 10! / 6! × (10-6)! = 210

10C7 = 10! / 7! × (10-7)! = 120

10C8 = 10! / 8! × (10-8)! = 45

10C9 = 10! / 9! × (10-9)! = 10

10C10 = 10! / 10! × (10-10)! = 1

So the total number of different combinations of attending at least 4 games is

210 + 252 + 210 + 120 + 45 + 10 + 1 = 848

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Answer:Tan 5pi/2 can also be expressed using the equivalent of the given angle (5pi/2) in degrees (450°).

Step-by-step explanation:

5π/2 radians is equivalent to 450 degrees.

We have,

To convert radians to degrees, we can multiply the value in radians by the conversion factor of 180 degrees/π radians.

To convert 5π/2 radians into degrees, we can use the conversion factor that states 180 degrees is equal to π radians.

Let's set up the conversion:

(5π/2 radians) × (180 degrees/π radians)

Here, the π radians in the numerator and denominator cancel out, leaving us with:

(5/2) × 180 degrees

Simplifying further, we have:

(5/2) × 180 = 900/2 = 450 degrees

Therefore,

5π/2 radians is equivalent to 450 degrees.

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By answering the presented question, we may conclude that Because the likelihood of a student possessing a smartphone is the same for each participant, the trials are similar.

A variable is something that may be changed in the context of a mathematical problem or experiment. A variable is often indicated by a single letter. Variables are commonly represented by the letters x, y, and z. A variable is a property that can be measured and has a large range of values. A few examples of criteria are size, age, affluence, location of birth, academic status, and kind of dwelling. Variables may be classified into two basic groups using both category and numerical methods.

X is a random variable that represents the amount of times a given number is rolled in 20 rolls of a 20-sided dice. This circumstance does not fit the binomial distribution model because the following four conditions are not met:

The trials are not independent since the outcome of each dice roll influences the odds of the succeeding rolls.

The success probability is not set since it is determined by the number chosen to count as a success.

Because the possibilities of each event are not equal, the trials are not similar.

The number of trials is predetermined.

X is a random variable that represents the number of successful free throws out of 100. Because the four prerequisites are satisfied, this scenario follows a binomial distribution model:

Because the outcome of one free throw does not impact the outcome of another, the trials are independent.

The success probability is set at 0.6.

Because the probability of making a free throw is the same for each shot, the trials are similar.

The trial count is set at 100.

X is a random variable that represents the number of cards drawn before receiving two spades in a row. This circumstance does not fit the binomial distribution model because the following four conditions are not met:

The trials are not independent since the outcome of each draw influences the likelihood of subsequent pulls.

The likelihood of success is not fixed because it is determined by the outcome of the prior pull (s).

Because the possibilities of each event are not equal, the trials are not similar.

The number of trials is not predetermined.

X is a random variable that represents the number of students out of 200 who own smartphones. Because the four prerequisites are satisfied, this scenario follows a binomial distribution model:

The trials are independent since one student's possession of a smartphone has no bearing on the outcome of another student.

The success probability is set at 0.85.

Because the likelihood of a student possessing a smartphone is the same for each participant, the trials are similar.

The trial count is set at 200.

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If a $1 million grant is to be divided among four charities, J, K, L, and M.  M will be awarded $200,000 of the grant.

Let the amount awarded to K be x. Then the amounts awarded to L and M will be x + 125,000 and y - 325,000, respectively.

Since the total grant is $1 million, we have:

x + (x + 125,000) + (y - 325,000) + y = 1,000,000

Simplifying this equation, we get:

2x + 2y - 200,000 = 1,000,000

2x + 2y = 1,200,000

x + y = 600,000

We also know that:

y - 125,000 = x + 325,000

y = x + 450,000

Substituting this into the equation x + y = 600,000, we get:

x + (x + 450,000) = 600,000

2x + 450,000 = 600,000

2x = 150,000

x = 75,000

Therefore, the amount awarded to M is:

y - 325,000 = x + 450,000 - 325,000 = $200,000

So, M will be awarded $200,000 of the grant.

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The triangle  DAE and FCE is congruent by the vertical angle theorem property.

What is congruency ?

Congruence of triangles is a term used in geometry to describe the relationship between two triangles that have exactly the same size and shape. In other words, if two triangles are congruent, all of their corresponding sides and angles are equal. When two triangles are congruent, they can be superimposed on each other, and all parts of one triangle will coincide with the corresponding parts of the other triangle.

The concept of congruence is essential in geometry, as it allows us to prove various theorems and make deductions about the properties of triangles. Two triangles can be shown to be congruent if any of the following conditions are met:

Side-Side-Side (SSS) Congruence: If the three sides of one triangle are equal to the three sides of another triangle, then the triangles are congruent.

Side-Angle-Side (SAS) Congruence: If two sides and the included angle of one triangle are equal to two sides and the included angle of another triangle, then the triangles are congruent.

Angle-Side-Angle (ASA) Congruence: If two angles and the included side of one triangle are equal to two angles and the included side of another triangle, then the triangles are congruent.

Angle-Angle-Side (AAS) Congruence: If two angles and a non-included side of one triangle are equal to two angles and the corresponding non-included side of another triangle, then the triangles are congruent.

Knowing these congruence criteria, we can use them to prove theorems and solve problems in geometry involving triangles.

The reflexive property is a fundamental concept in mathematics, and it applies to many different areas of study, including geometry. In the context of geometry, the reflexive property is related to congruence of triangles.

The reflexive property of congruence states that any geometric figure is congruent to itself. In the case of triangles, this means that any triangle is congruent to itself. In other words, every triangle is identical to itself, and all of its corresponding sides and angles are equal.

The reflexive property of triangles is used frequently in proofs and demonstrations in geometry. For example, if we want to show that a given triangle is congruent to another triangle, we can use the reflexive property to show that the two triangles are congruent to themselves. Then, we can use other methods, such as the SSS or SAS criteria, to show that the two triangles are congruent to each other.

Overall, the reflexive property is a key concept in geometry that allows us to reason about congruence and to prove various theorems and results related to triangles and other geometric figures.

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Answer:

The triangles are not similar because

12/24 is not equal to 3/5.

"Neither" is the correct answer.

The answer of the given question based on the theoretically optimal solution is ,False.

A model refers to a simplified representation of a real-world system or phenomenon that is used to gain insights, make predictions, or solve problems. Models in math can take many forms, including mathematical equations, geometric shapes, graphs, or diagrams.

Mathematical models are often used in various fields like physics, engineering, economics, and biology to represent and analyze complex phenomena. These models are constructed using mathematical principles and are based on assumptions and simplifications of the real-world system they represent.

False.

In project 8, the out-of-sample results are expected to provide an estimate of how well the model is expected to perform on new, unseen data. The out-of-sample results are not necessarily expected to the track closely with or exceed  results of theoretically optimal solution (TOS), as TOS is based on training data and may not generalize well to new data. The goal is to find a model that performs well on both the training data and new, unseen data, so the out-of-sample results are used to evaluate the generalization performance of the model.

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Answer:

Prompt 1:

Individuals: If someone with lots of side income loses their main job, they will likely have a financial cushion to fall back on. This can help them weather the storm until they find a new job. On the other hand, if someone without a lot of side income loses their main job, they may be more financially vulnerable and may struggle to make ends meet. They may have to dip into their savings or take on debt to cover their expenses until they find a new source of income.

Population: If everyone built side income, it could have a significant impact on the economy. More people would have additional income streams, which could lead to increased consumer spending and investment. This could, in turn, drive economic growth and create more jobs. However, there could also be downsides to this. If everyone were to focus on building side income, it could lead to a shortage of labor in traditional full-time jobs. This could make it difficult for some businesses to find qualified employees, which could slow down economic growth.

Prompt 2:

Individuals: Building side income can be challenging for people who are already working multiple part-time jobs or who have physical or other challenges. They may not have the time or energy to invest in building a side business or pursuing other opportunities. On the other hand, people with a high salary but who work long hours may have less time to dedicate to side income pursuits, even if they have the financial resources to do so. There may be other situations that make it easier or harder to build side income, such as access to capital, knowledge and skills, and support networks.

Population: While side income can help individuals increase their income, it may not be a viable solution to poverty on a large scale. Some people may not have the resources, knowledge, or opportunities to build side income streams, especially if they are already working long hours or struggling with physical or other challenges. To address poverty, it may be necessary to focus on creating more full-time jobs that provide livable wages and benefits. However, side income can still be a valuable supplement to a regular income, especially for those who have the time and resources to invest in building additional income streams.

Step-by-step explanation:

In addition, it's important to note that side income alone may not be enough to lift people out of poverty. In many cases, people living in poverty face systemic barriers such as lack of access to education, healthcare, and affordable housing. Addressing these issues requires more comprehensive solutions that go beyond income supplementation.

Furthermore, it's worth considering the impact of side income on income inequality. While side income can help some individuals increase their income, it may not be a viable solution for everyone. The ability to generate side income may be influenced by factors such as access to education, social networks, and financial resources. Therefore, promoting side income as a solution to poverty without addressing these underlying issues could potentially widen the gap between the rich and the poor.

In conclusion, while side income can provide financial benefits for individuals and potentially stimulate economic growth on a larger scale, it's important to consider the nuances and limitations of this income source. As with any economic issue, there are no easy solutions, and it's necessary to take a comprehensive and nuanced approach to address poverty and promote economic prosperity.

Diversifying income streams can give individuals financial stability and the economy can potentially benefit from increased consumer spending. However, building side income may not be feasible for everyone and while it could be part of poverty alleviation, it can't be the sole solution.

In the domain of microeconomics, individuals with significant side income may have financial security even if they lose their main job. This is because their side income can serve as a bridge, mitigating the possible financial strain of job loss. In contrast, those without much side income may face financial hardships if they lose their main job. It is therefore important for individuals to diversify income sources when possible.

From a macroeconomics perspective, if everyone developed side income, it could stimulate economic activity as income levels increase. Increased disposable income could lead to higher consumer spending, igniting broader economic stimulation. However, it might also lead to intensification of work, reducing leisure time and possibly impacting worker mental health and productivity.

Those who work multiple part-time jobs or have sizeable primary-job commitments might find it difficult to secure time for side-income-generating activities. On the other hand, individuals with higher salaries and flexible work schedules might have both the funding and time to establish and nurture a robust side income.

Side income could be a viable solution to poverty if it was accessible to everyone. This would require educational and entrepreneurial initiatives to equip individuals with the skills and opportunities necessary to generate extra income. However, side income alone is not a magic bullet and should be part of a suite of strategies to eradicate poverty.

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In the given information, we can see that the populace of the United States has expanded consistently over time, with a few variances.

 Here is a chronological chart of the US population data:

Year   Population (millions)

1790  3.9

1800  5.3

1810   7.2

1820   9.6

1830   12.9

1840   17.1

1850   23.2

1860   31.4

1870   38.6

1880   50.2

1890   63.0

1900   76.2

1910   92.2

1920   106.0

1930   123.2

1940   132.2

1950   151.3

1960   179.3

1970   203.3

1980   226.5

1990   248.7

2000  281.4

2010  308.7

From the time chart, we can see that the populace of the United States has expanded consistently over time, with a few variances.

The slant is up, with the populace developing quicker in later a long time.

The time chart moreover permits us to see the rate of populace development over time. We can see that the population has expanded from less than 4 million in 1790 to more than 300 million in 2010.

We are able moreover to see the rate of populace development over diverse periods, such as fast populace development. within the middle of the twentieth century.

In general, the time chart of US populace information gives a visual representation of statistic patterns over time and permits us to effortlessly distinguish designs and changes within the populace.

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Answer:

I can’t see it

Step-by-step explanation:

Answer: 8

Step-by-step explanation: 5x8=40

By answering the presented question, we may conclude that So, the equation of the line that passes through the point ([tex]12,19[/tex]) with slope [tex]-2/3[/tex] is: [tex]y = (-2/3)x + 27[/tex]

what is slope?

In mathematics, slope is the steepness of a line or curve. It is a measure of how much a function's y-value fluctuates when the x-value changes. A line's slope is commonly symbolised by the letter m and may be computed as follows: [tex]m = (y2 - y1) / (x2 - x1) (x1, y1)[/tex] and [tex](x2, y2)[/tex] are any two points on the line. The slope of a line might be positive, negative, zero, or unknown. A positive slope means the line ascends from left to right, whereas a negative slope means the line drops from left to right.

The point-slope form

[tex]y-y1=m(x-x1)[/tex]

[tex]y-19=(-2/3)(x-12)[/tex]

[tex]y-19=(-2/3)x+8\\y=(-2/3)x+27[/tex]

So, the equation of the line that passes through the point [tex](12,19)[/tex]  with slope [tex]-2/3[/tex] is:

[tex]y = (-2/3)x + 27[/tex]

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The coefficient of determination is not the square root of the correlation coefficient.

The coefficient of determination refers to the proportion of the variance in the dependent variable that is accounted for by the independent variable.

It is the square of the correlation coefficient and ranges between 0 and 1, with 0 indicating no correlation, while 1

indicates a perfect correlation.

The coefficient of determination is a measure of how much variation exists between two variables, with a higher value

indicating a stronger relationship between the two variables.

Additionally, the group of answer choices can indicate whether the correlation coefficient is significant, and the

coefficient of determination is not the square root of the correlation coefficient.

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It will take Mindy 1 week tο save $150.

The slοpe οf a line is the measure οf its steepness, defined as the ratiο οf the vertical change (rise) οver the hοrizοntal change (run) between any twο pοints οn the line.

Part A:

Tο create a graph that can be used tο mοdel the number οf dοllars Mindy saves in x weeks, we can use a linear equatiοn in slοpe-intercept fοrm:

y = mx + b

where y is the tοtal amοunt saved after x weeks, m is the slοpe (the cοnstant rate at which Mindy saves mοney), and b is the initial amοunt saved (which is 0 in this case).

Using the infοrmatiοn given, we can find the slοpe οf the line as fοllοws:

m = (change in y) / (change in x)

m = ($900 - $0) / (6 weeks - 0 weeks)

m = $150 per week

Sο the equatiοn fοr the line is:

y = $150x

We can graph this line by plοtting the pοints (0,0) and (6, $900), and then drawing a straight line cοnnecting them.

Part B:

The slοpe οf the line represents the cοnstant rate at which Mindy saves mοney each week. In this case, the slοpe is $150 per week, which means that Mindy is saving $150 every week.

Part C:

Tο use the line tο predict the number οf weeks it will take Mindy tο save $150, we can plug in the value fοr y (which is $150) intο the equatiοn and sοlve fοr x:

$150 = $150x

x = 1

Sο it will take Mindy 1 week tο save $150.

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Since 3 has the highest frequency, the mode is 3.Now, the curve is positively skewed if mean is bigger than mean.

Total number is a term used to refer to the sum of two or more individual elements. It is commonly used in the context of mathematics and can refer to the result of addition, subtraction, multiplication, or division. For example, the total number of apples in a basket could be five, the total number of days in a week could be seven, and the total number of people in a family could be four. In any case, the total number is the sum of all the individual elements that are being considered.

Presented to us is a distribution:

{4.5, 3, 1, 2, 4, 3, 6, 4.5, 4, 5, 2, 1, 3, 4, 3, 2}

We must determine the mean.

Mean is equal to the sum of all observations divided by the total number of observations.

Mean = 52/16

Mean = 3.25

We now determine the mode, which is the observation with the highest frequency, or how frequently it has occurred.

observations per unit of time

4.5 2

3 4

1 2

2 3

4 3

6 1

5 1

Since 3 has the highest frequency, the mode is 3.
Now, the curve is positively skewed if mean is bigger than mean.

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Complete questions as follows-
What is the mean of the given distribution, and which type of skew does it exhibit?
{4.5, 3, 1, 2, 4, 3, 6, 4.5, 4, 5, 2, 1, 3, 4, 3, 2}

WHAT IS THE MEAN? and WHAT TYPE OF SKEW EXHIBITS? negative, positive, symmetric, zero etc..