The heights of 11 plants, in inches, are listed. 14, 15, 16, 16, 17, 17, 17, 18, 18, 19, 22 If another plant with a height of 14 inches is added to the data, how would the range be impacted? The range would decrease to 8 inches. The range would stay the same value of 8 inches. The range would increase to 17 inches. The range would stay the same value of 18 inches.

The correct interpretation of an odds ratio of 0.75 would be (a) If not exposed the outcome is less likely since the odds ratio is less than 1.

An odds ratio of less than 1 indicates a decreased odds of the outcome in the exposed group compared to the unexposed group. Specifically, an odds ratio of 0.75 suggests that the odds of the outcome occurring in the exposed group is 25% lower than the odds of the outcome occurring in the unexposed group.

Option b is incorrect as an odds ratio of 0.75 is not necessarily close to 0, and option c is incorrect because an odds ratio of 0.75 means that the odds of the outcome in the exposed group is lower than the unexposed group, not 75 times greater. Option d is also incorrect as a protective effect would be observed if the odds ratio were less than 1.

Therefore, the correct option is (a)  If not exposed the outcome is less likely since the odds ratio is less than 1.

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The given question is incomplete, the complete question is:

How do you interpret an odds ratio of 0.75? a) If not exposed the outcome is less likely since the odds ratio if less than 1 b) There is no difference between groups because the odds ratio is close to 0 c) If exposed the outcome is 75 times greater than for the unexposed. d) if exposed the outcome is 75 the odds of the outcome in the unexposed (there is a protective effect)

Step-by-step explanation:

sine and cosine have a full cycle every 180° or pi (as the full circle is 360° or 2pi).

cosine starts with the value 1 (for theta = 0), goes to 0 for 90° or pi/2, then to -1 for 180° or pi, then again to 0 for 270° or 3pi/2. and back to 1 for 360° or 2pi.

and the next cycle begins ...

so,

cos(theta) = 0 for

theta = pi/2 and 3pi/2

Answer:

A = 3 1/4 + 2 1/4 = 5 2/4 = 5 1/2

B = 2 1/4 + 1 1/2 = 2 1/4 + 1 2/4 = 3 3/4

C = A + B = 5 1/2 + 3 3/4 = 5 2/4 + 3 3/4 =

8 5/4 = 9 1/4

Answer:

a.  a = 144, b = 67

Step-by-step explanation:

a + 36 = 180  they are consecutive interior angles, so they add up to 180

a = 180 - 36 = 144

b + 113 = 180  they are consecutive interior angles, so they add up to 180

b = 180 - 113 = 67

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Comparing using volume , The party store can 27 more smaller party hats on the shelf than larger party hats.

A cone is a three-dimensional geometric shape that tapers smoothly from a circular base to a point called the apex or vertex. It has a curved surface that extends from the base to the vertex and a circular base that is perpendicular to the axis of the cone.

We need to compare the number of smaller party hats that can fit on the shelf to the number of larger party hats that can fit on the same shelf. Since the hats are in the shape of cones, we need to use the formula for the volume of a cone to calculate their sizes.

The volume of a cone can be calculated using the formula:

[tex]V = \frac{1}{3}\pi r^2h[/tex]

where V is the volume, r is the radius of the base, h is the height of the cone, and π is the mathematical constant pi (approximately equal to 3.14).

Let's assume that the larger party hats have a radius of 1.5 feet and a height of 3 feet, while the smaller party hats have a radius of 1 foot and a height of 2 feet.

The volume of a larger party hat is:

[tex]V_1 = \frac{1}{3}\times\pi\times (1.5 ft)^2\times(3 ft) =3.14 ft^3[/tex]

The volume of a smaller party hat is:

[tex]V_2 = \frac{1}{3}\times\pi\times (1 ft)^2\times(2 ft) =0.21 ft^3[/tex]

The total volume of the shelf is 6 feet long and its cross-section is a rectangle, so its volume is:

[tex]V_{shelf} = (6 ft)\times(1 ft)\times(1 ft) = 6 ft^3[/tex]

To find out how many larger party hats can fit on the shelf, we need to divide the volume of the shelf by the volume of a single large party hat:

[tex]n_1 =\frac{ V_{shelf}} { V_1} = 1.91[/tex]

To find out how many smaller party hats can fit on the shelf, we need to divide the volume of the shelf by the volume of a single small party hat:

[tex]n_2 =\frac{ V_{shelf}}{ V2} = 28.57[/tex]

Rounding to the nearest whole number, we get:

n1 = 2

n2 = 29

Therefore, the party store can fit 29 - 2 = 27 more smaller party hats on the shelf than larger party hats.

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Answer: so there are two party hats, one is smaller with a radius of 4 inches and a volume of 100.5 cubic inches. The other one is larger with a radius of 6 inches and a volume of 209.4 cubic inches.

First, let's find out how many of the larger party hats can fit on the shelf. The shelf is 6 feet long, which is 72 inches long. We're gonna divide the length of the shelf by the length of the larger party hat.

So, for the larger party hat, the height is 6 inches, and the radius is 6 inches. The formula to find the volume of a cone is V = (1/3) * π * r^2 * h. Plugging in the values, we get V = (1/3) * 3.14 * 6^2 * 6 = 452.16 cubic inches.

To find out how many of the larger party hats can fit on the shelf, we'll divide the length of the shelf by the length of the larger party hat. 72 inches divided by 6 inches gives us 12.

So, 12 of the larger party hats can fit on the shelf.

Now, let's do the same for the smaller party hat. The height is 8 inches, and the radius is 4 inches. Using the same formula, V = (1/3) * 3.14 * 4^2 * 8 = 134.19 cubic inches.

To find out how many of the smaller party hats can fit on the shelf, we'll divide the length of the shelf by the length of the smaller party hat. 72 inches divided by 8 inches gives us 9.

So, 9 of the smaller party hats can fit on the shelf.

Now, to find out how many more of the smaller party hats can fit on the shelf than the larger party hats, we subtract the number of larger party hats from the number of smaller party hats. 9 minus 12 gives us -3.

The result is negative, which means that we can't fit more smaller party hats than the larger ones. In fact, we can fit 3 fewer smaller party hats on the shelf than the larger ones.

Step-by-step explanation: I hope this helps.

When measuring the effects of a new diuretic medication, hourly urine output represents the ratio level of measurement.

What is ratio level of measurement?

Ratio level of measurement is a type of measurement that features a true zero point, meaning that the value 0 represents the absence of the characteristic being measured.

Some examples of ratio level measurements include weight, height, length, distance, speed, and many others. In this case, the hourly urine output of subjects is measured to determine the effects of a new diuretic medication.

The hourly urine output is a ratio measurement because it has a true zero point, which is the absence of urine output. In other words, if there is no urine output, the value would be 0, which represents the absence of the characteristic being measured.

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The probability that exactly 5 of the next 7 patients survive the operation is approximately 0.123, or 12.3%.

To find the probability that exactly 5 out of the next 7 patients survive the operation, we can use the binomial probability formula, which is:
[tex]P(X=k) = C(n, k) * p^k * (1-p)^(n-k)[/tex]
where:
- P(X=k) represents the probability of exactly k successes (survivals) in n trials (operations)
- C(n, k) is the number of combinations of n items taken k at a time
- n is the number of trials (in this case, 7 patients)
- k is the number of successful outcomes (5 patients surviving)
- p is the probability of a successful outcome (0.9 for a patient surviving the operation)
Applying the formula, we have:
[tex]P(X=5) = C(7, 5) * 0.9^5 * (1-0.9)^(7-5)[/tex]
First, let's calculate the number of combinations C(7, 5):
C(7, 5) = 7! / (5! * (7-5)!)
C(7, 5) = 7! / (5! * 2!)
C(7, 5) = (7 * 6 * 5 * 4 * 3 * 2 * 1) / (5 * 4 * 3 * 2 * 1 * 2 * 1)
C(7, 5) = 21
Now, we can plug this into the binomial probability formula:
[tex]P(X=5) = 21 * 0.9^5 * 0.1^2[/tex]
P(X=5) = 21 * 0.59049 * 0.01
P(X=5) ≈ 0.1232019.

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The measure of ZL in parallelogram JKLM is 14x - 5.

A parallelogram is a quadrilateral with two pairs of parallel sides. That is, opposite sides are parallel and congruent. Parallelograms have several properties that make them useful in geometry and other fields.

In a parallelogram, opposite sides are parallel and congruent. Therefore, we can set up an equation that relates the measures of the opposite sides of parallelogram JKLM:

KL = MJ

We can use this equation to solve for x, and then find the measure of ZL.

Starting with KL, we have:

KL = 15x - 12

Now, for MJ, we need to notice that MJKL is a rectangle because it has a right angle at K. In a rectangle, opposite sides are congruent. Therefore, we have:

MJ = KL = 15x - 12

Now we can use the given expression for MJ to set up an equation for JL in terms of x:

JL = 14x - 5

We can use the fact that JKLM is a parallelogram to set up another equation that relates JL and ZL:

JL = ZL

Putting the two equations together, we get:

JL = JL

14x - 5 = JL = ZL

Therefore, ZL = 14x - 5.

We can substitute the expression we found earlier for JL into this equation to get:

ZL = 14x - 5 = JL = 14x - 5

Simplifying, we get:

ZL = 14x - 5

Therefore, the measure of ZL in parallelogram JKLM is 14x - 5.

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Answer: F= 4

Step-by-step explanation:

rise over run!

-4 (from the run in the slope) plus 8 (your x axis) is 4

To solve the problem, we need to subtract the cost of lunch from Avery's initial amount of money:

$25.69 - $10.50 = $15.19

Therefore, Avery had $15.19 in her wallet after buying lunch.

The measures of diabetes mellitus, coronary artery disease, and renal disease in study subjects represent the nominal level of measurement. This is because these measures are categorical in nature and cannot be ranked or ordered.

Nominal level of measurement is the simplest form of measurement which assigns a name or number to an attribute. The attributes can be classified into different categories or classes without any ranking.

Nominal level of measurement is commonly used in research to represent things like gender, race, marital status, religion, and so on. In this case, the attributes being measured are the different chronic diseases. These are categorical and cannot be ranked.

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Answer:

√9797

The result can be shown in multiple forms.

Exact Form:√9797

Decimal Form:9.84885780…

Approximately 58.33% of the workers in the group are making over $25 an hour. The percentage was obtained by finding the area under the uniform distribution curve above the value of $25.

Since the hourly wages of the workers are uniformly distributed on the interval [20, 32], the probability density function is constant on this interval. The area under the probability density function between any two points a and b gives the probability that a randomly chosen worker's wage will be between a and b. Therefore, the probability that a worker's wage is above $25 is given by the area under the probability density function from 25 to 32, which is (32-25)/(32-20) = 7/12 or approximately 58.33%. Thus, approximately 58.33% of the workers are making over $25 an hour.

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The missing frequency in the given table is 24.

What is frequency?

To find the missing frequency, we need to use the information given in the histogram and the frequency table.

We can see from the histogram that the missing class interval is 26-28.

The total frequency for all class intervals is the sum of the frequencies in the table:

110 + 36 + 180 + f = 326 + f

We also know that the total frequency is the number of phones recorded by the manufacturer, so we can assume that the total frequency is a whole number.

Since the sum of the frequencies in the table is 326, the missing frequency must be:

f = total frequency - sum of the other frequencies

f = 350 - 326

f = 24

Therefore, the missing frequency is 24.

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The equation of ellipse will be  [tex]\frac{(x-4)^{2} }{16 } + \frac{(y-5)^{2} }{9 } =1[/tex]

An ellipse is the locus of all those points in a plane such that the sum of their distances from two fixed points , which is a constant. Those fixed points are known as the foci in singular term focus. The fixed line is known as directrix and the constant ratio is called the eccentricity of ellipse.

The ellipse with vertices (0, 5) and (8, 5) and minor axis of length 6.

Now the midpoint is( [tex]\frac{0+8}{2}[/tex] , [tex]\frac{5+5}{2}[/tex] )

                                 ( 4, 5)

So the center is (4, 5)

The equation  of the ellipse is

[tex]\frac{(x-h)^{2} }{b^{2} } + \frac{(y-k)^{2} }{a^{2} } =1[/tex]   where b is the semi major axis and a is the semi minor axis.

where (h, k) is the center. Here it is ( 4, 5)

Here 2a= 6 and 2b=8

Hence, the equation of ellipse will be

 [tex]\frac{(x-4)^{2} }{16 } + \frac{(y-5)^{2} }{9 } =1[/tex]

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The probability that a rental car delivered to the firm will need a tune-up is 0.03% or 0.000306 and the probability that it came from agency 2 is 39.15% or 0.3915.

(a) Let P(A1), P(A2), and P(A3) be the probabilities that a rental car comes from agency 1, agency 2, and agency 3, respectively, and let P(T) be the probability that a rental car needs a tune-up. Then, using the law of total probability, we have:

P(T) = P(T|A1)P(A1) + P(T|A2)P(A2) + P(T|A3)P(A3)

P(T) = 0.05(0.0036) + 0.02(0.0006) + 0.02(0.0058)

P(T) = 0.00018 + 0.000012 + 0.000116

P(T) = 0.000306

Therefore, the probability that a rental car delivered to the firm will need a tune-up is 0.03% (or 0.000306 as a decimal).

(b) Using Bayes' theorem, we can calculate the conditional probability that a rental car came from agency 2 given that it needs a tune-up:

P(A2|T) = P(T|A2)P(A2) / P(T)

P(A2|T) = 0.02(0.0006) / 0.000306

P(A2|T) = 0.3915

Therefore, if a rental car delivered to the firm needs a tune-up, the probability that it came from agency 2 is 39.15% (or 0.3915 as a decimal).

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The special two-item character sequence that represents special characters like \n is known as an Escape Sequence. So the option B is correct.

An escape sequence is a sequence of characters that does not represent itself when used inside a character or string literal, but is translated into another character or a sequence of characters. It is used to signal an alternative interpretation of a series of characters. Common examples are the escape sequences used in C/C++ and other programming languages, such as "\n" for newline, "\t" for tab, and "\\" for a backslash. So the option B is correct.

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The complete question is:

The special two-item character sequence that represents special characters like \n is known as a(n) ?

a. backslash code

b. escape sequence

c. Unicode spec

d. literal character

Answer: 12 yards

Step-by-step explanation:

Melanie bought 12 yards of ribbon.

(1 yard = 3 feet)

Answer:

the answer for the equations is

[tex]x = - 11[/tex]

Answer:

Square: [tex]A = s^{2}[/tex]

Parallelogram: [tex]A = b x h[/tex]

Trapezoid: [tex]A = \frac{1}{2} xh x (base_{1} +base_{2})[/tex]

Triangle: [tex]A = \frac{1}{2} x b x h[/tex]

Answer:     Square:

    Parallelogram:

Square:

Parallelogram:

Trapezoid:

Triangle:

    Trapezoid:

       Triangle:

Step-by-step explanation:

The probability that a rental car delivered to the firm needs a tune-up is 0.0000308, or approximately 0.0031%. The probability that a car comes from agency 2 needs a tune-up is 0.0234, or approximately 2.34%.

The probability that an event will occur or a claim will be true is measured by probability theory, a branch of mathematics. The probability of an occurrence is a number from 0 as well as 1, where around 0 represents how likely the occurrence would be to occur while 1 represents certainty. A probability is just a numeric illustration of the possibility that a specific occurrence will take place. Probabilities can also be expressed as percentages ranging between 0% to 100% or even from 0 to 1. the ratio of the number of outcomes to the proportion of occurrence in a whole set of equally probable options that lead to a specific occurrence.

given,

(a) Let's denote the event that a car comes from agency i as Ai and the event that a car needs a tune-up as T. We want to find the probability that a rental car delivered to the firm will need a tune-up, which can be written as P(T).

P(T) = P(T|A1)P(A1) + P(T|A2)P(A2) + P(T|A3)P(A3)

Substituting the given probabilities, we get:

P(T) = 0.05% * 0.36% + 0.02% * 0.06% + 0.02% * 0.58%

P(T) = 0.000018 + 0.0000012 + 0.0000116

P(T) = 0.0000308

Therefore, the probability that a rental car delivered to the firm will need a tune-up is 0.0000308, or approximately 0.0031%.

(b) Let's denote the event that a car comes from agency 2 as A2. We want to find the probability that a car comes from agency 2 given that it needs a tune-up, which can be written as P(A2|T).

P(A2|T) = P(T|A2)P(A2) / P(T)

Substituting the given probabilities, we get:

P(A2|T) = 0.02% * 0.06% / 0.0000308

P(A2|T) = 0.00000072 / 0.0000308

P(A2|T) = 0.0234

Therefore, the probability that a rental car delivered to the firm needs a tune-up and came from agency 2 is 0.0234, or approximately 2.34%.

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The total cost to operate his car for the year is then the sum of his fixed costs and his variable costs, or $10,018.00.

Annual variable is measured or observed over a 12-month period.

The annual variable costs for Anwar Mabak is $7,200.00. This can be calculated by multiplying the total number of miles driven (22,500) by the cost per mile ($0.32).

Annual Variable Costs = 22,500 x $0.32

      = $7,200.00

The total cost to operate his car for the year is then the sum of his fixed costs and his variable costs, or $10,018.00.

Total Costs = Fixed Costs + Variable Costs

    = $2,818.00 + $7,200.00

    = $10,018.00

Anwar Mabak's variable costs are a direct result of the number of miles he drives during the year, since he pays a certain amount for each mile he drives. This is why his variable costs increase or decrease depending on the number of miles he drives.

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Answer:

The distance between points A and D is 9 units.

The distance between points E and F is approximately 7.28 units.

Step-by-step explanation:

Answer:

The cost of an adult ticket is 7.

Step-by-step explanation:

4t + 21 = 49

    - 21 = 28

4t = 28

/4 = 7

t = 7

The standard error of the mean (SEM) in statistics is a measure of the variability or dispersion of a sample mean.

The standard error of M in statistics is the standard deviation of the distribution of sample means. It is a measure of the standard distance between the sample means and the actual population mean.

It indicates the degree of sampling variability of a sample mean. It is a very important tool in inferential statistics that allows the determination of the margin of error in a statistical estimation.

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70% of the population prefers coca-cola over pepsi, the probability that both prefer coca-cola is 0.49.

Probability refers to potential. A random event's occurrence is the subject of this area of mathematics. The range of the value is 0 to 1. Mathematics has included probability to forecast the likelihood of certain events. The degree to which something is likely to happen is basically what probability means.

Probability is a way to gauge how likely something is to happen. Several things are difficult to forecast with absolute confidence. With it, we can only make predictions about the likelihood of an event happening, or how likely it is. Probability can vary from 0 to 1, with 0 being an impossibility and 1 denoting a certainty. For pupils in Class 10, probability is a crucial subject since it teaches all the fundamental ideas of the subject. One is the probability of every event in a sample space.

70% of the population prefers Coca-Cola over Pepsi,

that is 0.7

The probability of the Pepsi is 30% = 0.3

The probability that both prefers coca cola is 0.7 x 0.7 = 0.49.

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For supplementary angles 13x + 14 = A, 11x + 28= B​ and A is parallel B, A=B

Therefore x=7

A and B's corresponding angles are congruent if A and B are parallel. As a result, we may equalize the formulas for the respective angles and find x:

13x + 14 = 11x + 28

2x = 14

x = 7

Consequently, we must fix x equal to 7 in order to make A and B parallel. When we insert this value into the formulas for A and B, we obtain:

A = 13(7) + 14 = 105

B = 11(7) + 28 = 105

The corresponding angles of A and B are now congruent, and A and B are equal and parallel.

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For two populations for which μ₁ = 31,σ₁ = 2, μ₂ = 27, and σ₂ = 4. The shape of the distribution is approximately normal. So, the correct choice for answer is option (b). The mean of normal distribution is equals to 4.

In statistics, the collected data distribution shape sometimes normal and sometimes non-normal. In testing of hypothesis, to use the test statistics we have to check whether data is normally or not. Here we have, two populations. In first population : mean μ₁ = 31,

standard deviations,σ₁ = 2,

sample size, n₁ = 49

In case of second sample, mean, μ₂ = 27,

standard deviations, σ₂ = 4.

Sample size, n₂ = 59

Since, population standard deviation are known and sample sizes are greater than 30, therefore the shape of the sampling distribution of the difference of sample means is approximately normal. The shape of the distribution is approximately normal. Mean of the sampling distribution of [tex] \bar x_1 - \bar x_2[/tex] are

[tex]\mu_{ \bar x_1 - \bar x_2} = \mu_1 - \mu_2 [/tex]

= 31 - 27 = 4

Hence, Mean of the distribution is 4.

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Complete question:

Consider two populations for which μ₁ = 31,σ₁ = 2, μ₂ = 27, and σ₂ = 4. Suppose that two independent random samples of sizes n₁ = 49 and n₂ = 59 are selected. Describe the approximate sampling distribution of x₁ bar - x₂ bar (center, spread, and shape). What is the shape of the distribution?

a) The distribution would be non-normal.

b) The distribution is approximately normal.

c) The shape cannot be determined.

What is the mean of the distribution?

This two are characteristics of frequency tables

1. They can be used for quantitative data.

2. They can be used for qualitative data.

Frequency tables have the following characteristics:
1. They can be used for quantitative data:

Frequency tables display the number of occurrences of each value in a dataset, which is particularly useful when dealing with numerical or quantitative data.
2. They can be used for qualitative data:

Frequency tables can also be used for non-numerical or qualitative data, such as categories or groups, by counting the number of occurrences for each category.
4. No observation can fit into more than one class:

In a frequency table, each observation or data point is assigned to only one class or category, ensuring that there is no overlap between classes.

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