Indicate whether the statement is likely to be a hypothesis. 1) Data on the daily sitting times and weights for 1000 people is obtained to determine if the following statement is true: The more a person sits, the more weight a person gains. O Hypothesis O Not a hypothesis 2) Data on the daily sitting times and weights for 1000 people indicates that the mean sitting time is 5 hours a day. O Hypothesis O Not a hypothesis 3) Data on the daily sitting times and weights of 1000 people is obtained and labeled according to the person's gender. The mean sitting times of men and women are calculated separately to determine if the following statement is true: Men sit longer than women each day. O Hypothesis O Not a hypothesis 4) People should stand more to gain health benefits. O Hypothesis O Not a hypothesis

(a) To find the probability density function (pdf) of Z = X + Y, we can use the convolution formula:

fZ(z) = ∫_{-∞}^{∞} fX(x) fY(z - x) dx

Since X and Y are both uniformly distributed on (0,1), we have:

fX(x) = fY(y) = 1, for 0 < x,y < 1

Substituting these expressions, we get:

fZ(z) = ∫_{0}^{1} 1 * 1 dz - ∫_{0}^{z} 1 * 1 dx = z, for 0 < z < 1

fZ(z) = 0, for z ≤ 0 or z ≥ 1

Therefore, the pdf of Z is:

fZ(z) = {

z, 0 < z < 1,

0, otherwise.

}

(b) To find the moment generating function (MGF) of Z, we can use the definition:

M_Z(t) = E[e^{tZ}] = ∫_{-∞}^{∞} e^{tz} fZ(z) dz

Using the pdf of Z, we get:

M_Z(t) = ∫_{0}^{1} e^{tz} z dz = [(ze^{tz})/(t^2)]|_{0}^{1} = (e^t - 1)/t^2, for t ≠ 0

M_Z(t) = 1, for t = 0

Therefore, the MGF of Z is:

M_Z(t) = {

(e^t - 1)/t^2, t ≠ 0,

1, t = 0.

}

Note that the MGF is defined only for values of t for which the integral converges.

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I'll show you how to do the first one so that you can do the rest yourself

Answer:

7, 10, 13, 19, 24

Step-by-step explanation:

First, re-write the numbers in numerical order;

7  8  10  10  13  16  19  23  24

(If there's a double number, add it twice)

Then, find the following values easily

The Minimum is the lowest value, 7

The Median is the middle value, 13

The Maximum is the highest value, 24

Here's where it gets tricky...You split the first half (7-13) and the second half (13-24). You then find the median of both halves to find Q1 and Q3

Simply follow those steps to find the other solutions

The answer resulted in x = 5 after the operation as the picture suggests, hope this helps

a) The slope of the graph from ( 0 , 1 ) and ( 2 , 4 ) = 3/2

b) The slope of the graph from ( -2 , 1/4 ) and ( -1 , 1/2 ) = 1/4

c) No , the slope is not a constant

d) No , the graph is not linear

Given data ,

Let the exponential equation be represented as A

Now , the slope of the graph from ( 0 , 1 ) and ( 2 , 4 ) is given by

m = ( y₂ - y₁ ) / ( x₂ - x₁ )

m = ( 4 - 1 ) / ( 2 - 0 )

m = 3/2

And , slope of the graph from ( -2 , 1/4 ) and ( -1 , 1/2 ) is given by

m = ( 1/2 - 1/4 ) / ( -1 - ( -2 ) )

m = ( 1/4 )

And , the slopes are not same for the line , so it is not constant and line is not a linear equation

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Answer:

150

Step-by-step explanation:

First, we can simplify 5³:

5³ = 5 × 5 × 5 = 125

Then, we can simplify 4²:

4² = 4 × 4 = 16

Next, we can simplify √81:

√81 = √(9 × 9) = 9

Finally, we can add these simplified values:

5³ + 4² + √81

= 125 + 16 + 9

= 150

_____

Note:

An exponent shows how many times its base (the big number next to it) should be multiplied by itself.

A square root gives the number that is multiplied by itself to get the number under the root sign.

Answer: 0

Step-by-step explanation:

8-8=0

This formula gives us the value that corresponds to the specified confidence level.

To find the critical z value that corresponds to a confidence level of 94%, we need to use a standard normal distribution table or calculator.

Using a table, we can find that the critical z value for a 94% confidence level is approximately 1.88. This means that 94% of the area under the standard normal curve falls within 1.88 standard deviations of the mean.

To find the value that corresponds to this critical z value, we need to know the mean and standard deviation of the population we are interested in. If we don't have this information, we can use a sample mean and standard deviation to estimate them.

Once we have the mean and standard deviation, we can use the formula:

value = mean + (z * standard deviation)

where z is the critical z value we found earlier.

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Answer:

-2/3

Step-by-step explanation:

3x -2y = 14

-2y = -3x + 14

y = 3/2x - 7

m = 3/2

The equation of a perpendicular line to y = 3/2x − 7 must have a slope that is the negative reciprocal of the original slope.

m perpendicular = - [tex]\frac{1}{\frac{2}{3} }[/tex]

So, the answer is m perpendicular = -2/3

The probability that the student chosen will walk to school is 0.5156. 

Out of the 64 understudies (students) overviewed, let x be the number of understudies overviewed in Year 9.

At that point, we know that x = 1.3*20 = 26.

Out of the 20 understudies (students) studied in Year 7, 75% strolled to school, so 15 understudies in Year 7 strolled to school.

In Year 9, 8 more understudies strolled to a school than did not walk. Let w be the number of understudies in Year 9 who strolled to school.

At that point, the number of understudies in Year 9 who did not walk to school is x - w. So we have:

w + (x - w) = 26 (since x is the entire number of understudies overviewed in Year 9)

w - (x - w) = 8 (since 8 more understudies strolled to a school than did not walk)

Understanding this framework of conditions, we get w = 17 and x - w = 9

Out of the remaining understudies studied, which are in Year 11, we know that more strolled to a school than in Year 9.

In this manner, the likelihood that an understudy chosen at irregular strolls to school is:

P(walk to school) = (15 + 17 + x/4)/64

where x/4 is the number of understudies overviewed in Year 11 who strolled to school. We do not know the esteem of x/4, but we do know that it is more prominent than 9, since more understudies strolled to school in Year 11 than in Year 9.

In this manner, ready to say that:

P(walk to school) > (15 + 17 + 9)/64 = 0.5156

So the likelihood that a student chooses irregular walks to school is more noteworthy than 0.5156. 

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Two points that lie on the line are (5, 8) and (16, 10).

The slope that best presents the number of questions completed is 2/11.

In Mathematics and Geometry, the slope of any straight line can be determined by using this mathematical equation;

Rate of change (slope) = (Change in y-axis, Δy)/(Change in x-axis, Δx)

Rate of change (slope) = rise/run

Rate of change (slope) = (y₂ - y₁)/(x₂ - x₁)

By substituting the given data points into the formula for the slope of a line, we have the following;

Rate of change (slope) = (y₂ - y₁)/(x₂ - x₁)

Rate of change (slope) = (10 - 8)/(16 - 5)

Rate of change (slope) = 2/11

Based on the graph, the rate of change is the change in y-axis with respect to the x-axis and it is equal to 2/11.

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The probability that Tate will hit 2 home runs in a row is P ( R ) = 4/81

Given data ,

Let the total number of throws be = 9

And , the number of times Tate hits a home run in 9 throws = 2

Now , the probability of Tate hitting a home run in a single at-bat is 2/9

The probability of hitting a home run in two consecutive at-bats is the product of the probabilities of hitting a home run in each individual at-bat, assuming that the outcomes of the at-bats are independent.

Therefore, the probability of Tate hitting 2 home runs in a row is P ( R )

P ( R ) = (2/9) x (2/9)

P ( R ) = 4/81

Hence , the probability is 4/81

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Answer: That is correct. In a binary tree, each node has at most two child nodes (hence the name "binary"), and the height of the tree is the length of the longest path from the root node to a leaf node.

If the tree has n leaves, then the number of nodes in the tree is at most 2n-1 (since each node can have at most 2 child nodes and there is only one root node), and the height of the tree is log2(2n) = log2n + 1 (since there are 2n nodes at level log2n, and we need to add 1 for the root node).

However, if the tree is not perfectly balanced, it is possible for the height to be slightly larger than log2n + 1. Nonetheless, log2n is still a tight upper bound on the height of a binary tree with n leaves.

If three coins are thrown, the probability of obtaining at least one head is 0.875.

Probability refers to likely of an event occurring. The probability of an event occurring is expressed as

P = [tex]\frac{favourable\,outcome}{Total\,number\,of\,outcome}[/tex]

The events that can occur when three coins are thrown are HHH, HHT, HTH, HTT, TTT, TTH, THT, THH where T is the tail side obtained

and H is the head side obtained.

Total number of outcomes possible = 8

The events in which at least one head is obtained are HHH, HHT, HTH, HTT, THH, THT, TTH

Number of events in which at least one head is obtained = 7

Probability = [tex]\frac{7}{8}[/tex] = 0.875

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The largest integer that can be in the data-set is given as follows:

13.

The data-set in this problem has five integers, hence the median of 5 is the third element, given as follows:

x, y, 5, w, z.

The mean is also of 5, meaning that the sum of the other elements is 20, that is:

x + y + w + z = 20.

z will be maximized when x = 1,  y = 1 and w = 5, hence:

1 + 1 + 5 + z = 20

z = 13.

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The requried, positive angle less than 360 that is Coterminal with 695 is 335 degrees.

To find an angle that is coterminal with 695 and less than 360 degrees, we can subtract 360 degrees from 695 until we get an angle that is less than 360 degrees.

695 - 360 = 335

335 is an angle that is coterminal with 695 and less than 360 degrees.

Thus, a positive angle less than 360 that is Coterminal with 695 is 335 degrees.

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The chi-square test statistic is 4.54.

Thus, option C. 4.54 is correct.

We can calculate the chi-square test statistic using the formula:

χ² = Σ((O - E)² / E)

where:

O = observed frequency

E = expected frequency

Given the observed frequencies:

Monday: 20 calls

Tuesday: 12 calls

Wednesday: 10 calls

Thursday: 18 calls

And the expected frequency: 15 calls each day

Let's calculate the chi-square test statistic step by step:

For Monday:

χ² = ((20 - 15)² / 15)

   = 1.67

For Tuesday:

χ² = ((12 - 15)² / 15)

   = 0.6

For Wednesday:

χ² = ((10 - 15)² / 15)

   = 1.67

For Thursday:

χ² = ((18 - 15)² / 15)

   = 0.6

Now, we sum up all the individual chi-square values:

χ² = 1.67 + 0.6 + 1.67 + 0.6

    = 4.54

Therefore, the chi-square test statistic is 4.54.

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The question attached here seems to be incomplete, the complete question is:

Robert recorded the number of calls he made at work during the week:

Day Calls

Monday 20

Tuesday 12

Wednesday 10

Thursday 18

He expected to make 15 calls each day. To determine whether the number of calls follows a uniform distribution, a chi-square test for goodness of fit should be performed (alpha = 0.05).

Using the data above, what is the chi-square test statistic? Answer choices are rounded to the hundredths place.

a.)0.67

b.)0.42

c.)4.54

d.)3.75

Answer:

  21 units

Step-by-step explanation:

You want the height (x) of a cone with base radius 9 units and volume 567π cubic units.

The volume of a cone is given by the formula ...

  V = 1/3πr²h

Solving for the height, and using x for the height, we find ...

  x = 3V/(πr²) = 3(567π units³)/(π(9 units)²) = 21 units

The height of the cone is 21 units.

The reason why some data mining algorithms require that variables are standardized to zero mean and standard deviation of 1.0 is because it helps to normalize the data and make it more comparable across different variables.

Standardizing the data helps to remove the impact of the scale of the variables on the analysis, allowing for more accurate comparisons and correlations between variables. By doing this, it ensures that no one variable has an undue influence on the results of the analysis. Standard deviation is a statistical measure that is used to measure the amount of variability or dispersion in a dataset. When data is standardized, it allows for a more accurate assessment of the relationship between variables and can improve the accuracy of the analysis. Overall, standardizing variables is a crucial step in the data mining process, as it helps to ensure that the results of the analysis are reliable and accurate.

The reason some data mining algorithms require variables to be standardized (or normalized) to a zero mean and a standard deviation of 1.0 is to ensure consistent and comparable scales for all variables involved. Standardizing variables helps in improving the performance and accuracy of the algorithms.

When variables have different scales or units, it can be challenging for algorithms to interpret their relative importance accurately. By transforming variables to have a zero mean and a standard deviation of 1.0, the algorithms can more effectively process and analyze the data. This standardization process is particularly important for distance-based and gradient-based algorithms, where scale differences can significantly impact the results.

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The ratio problem of a manufacturing plant produces 917 units in 7 hours so it would take approximately 11 hours to produce 1,441 units at the same consistent production rate.

We can use a proportion to solve this problem.

Let's call the number of hours it takes to produce 1,441 units "x". We know that the plant produces 917 units in 7 hours, so we can set up the following proportion:

917 units / 7 hours = 1441 units / x hours

To solve for x, we can cross-multiply and simplify:

917 units × x hours = 7 hours × 1441 units

x = (7 hours × 1441 units) / 917 units

x ≈ 11 hours

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The correct set of transformations is "Dilation by a scale factor of 2 followed by reflection about the x-axis".

Compare the corresponding side lengths to find the scale factor of the dilation.

For example, the distance between X and Y is √2 in triangle XYZ, and the distance between X'' and Y'' is 2√2 in triangle X''Y''Z''.

Therefore, the scale factor of the dilation is 2.

Now, find the direction of the reflection.

The y-coordinates of corresponding points in the two triangles have the same absolute values but opposite signs, which suggests a reflection about the x-axis.

Therefore, the correct set of transformations is:

Dilation by a scale factor of 2 followed by reflection about the x-axis.

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Answer:

C. $5.31

Step-by-step explanation:

35.40*0.15=5.31

0.15 is 15%

In order to create a regression model predicting employee salary at a company based on the given predictor variables, we would need to dummy code the job title variable.

The other variables, experience, tenure, and age, can be used as continuous variables without the need for dummy coding. Dummy coding the job title variable would involve creating separate binary variables for each job title category, with a value of 1 indicating that the employee holds that job title and a value of 0 indicating they do not. This would allow us to include job title as a predictor variable in the regression model while accounting for the fact that job titles are not continuous or ordinal variables.

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Answer: 10

Step-by-step explanation:

| –10 | = 10

Because that's the number of spaces it's from 0. :-)

Answer:

The Correct answer is A

Step-by-step explanation:

b) because r²=q²+p²,p²=r²-q² not

r²+q²

c) (p+q)²=r²

is not correct because

(p+q)²=(p+q)(p+q)

d) p²+r²=q² wrong

because

q²=r²-p²

Step-by-step explanation:

It is a CUBE   so each of the SIX sides has area   2/3  X  2/3

the TOTAL area is then    SIX * (2/3 X 2/3) = 2 2/3 units^2

Answer: x^2 + bx/a + c/a = 0

Step-by-step explanation:

the step simplifies the division of a:

0 divided by anything is still zero, so you can remove the a denominator

a/a = 1, and is therefore irrelevant, so ax^2 / a = x^2

the rest can stay

Answer:

look the picture for the representation

thank you

The best day to sell both stocks is Day 2, since the total value of both stocks is highest on that day, option C is correct.

On Day 1, the total value of the 30 shares of Metropolis stock is:

30 shares x $17.95 per share = $538.50

And the total value of the 55 shares of Suburbia stock is:

55 shares x $5.63 per share = $309.65

So the total value of both stocks on Day 1 is:

$538.50 + $309.65 = $848.15

On Day 2, the total value of the shares of Metropolis stock is:

30 shares x $18.28 per share = $548.40

And the total value of the shares of Suburbia stock is:

55 shares x $5.88 per share = $323.40

The total value of both stocks on Day 2 is: $871.8

for Day 3, total value of both stocks on Day 3 is $$821.40

Therefore, we can see that the best day to sell both stocks is Day 2, since the total value of both stocks is highest on that day:

$871.80 - $848.15 = $23.65

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The measure of arc angle DC is 60.

The measure angle A is  45⁰.

The measure angle B  is 50⁰.

The measure angle C is  45⁰.

The measure angle D  is 50⁰.

The measure of arc angle DC is calculated as follows;

arc DC = 360 - (100 + 110 + 90) (sum of angles in a circle)

arc DC = 60

The measure angle A is calculated as follows;

m∠A = ¹/₂( arc BC ) (intersecting chord theorem)

m∠A = ¹/₂ x 90

m∠A = = 45⁰

The measure angle B  is calculated as follows;

m∠B = ¹/₂( arc AD ) (intersecting chord theorem)

m∠B = ¹/₂ x 100

m∠B  = 50⁰

The measure angle C is calculated as follows;

m∠C = m∠A (vertical opposite angles)

m∠C = = 45⁰

The measure angle D is calculated as follows;

m∠D = m∠B  (vertical opposite angles)

m∠C = = 50⁰

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