real life problem that can be solved by statistical
​

Axiomatic semantics, a branch of formal semantics, is based on mathematical logic. It provides a formal framework for defining the behavior and meaning of programming languages or formal systems.

Mathematical logic serves as the foundation for axiomatic semantics, offering tools and methods to define and reason about formal systems. It encompasses propositional and predicate logic, set theory, and proof theory. In axiomatic semantics, mathematical logic is used to define syntax, semantics, and proof systems, allowing for precise specifications of program behavior and correctness.

While other branches of mathematics such as set theory and calculus may be utilized in defining underlying structures and functions, the core principles and techniques of axiomatic semantics are rooted in mathematical logic. This logical framework enables rigorous reasoning about program properties and supports the verification and analysis of programs and systems.

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The graph of y = -5x + 10 is a function because (d) yes, because it passes the vertical line test.

From the question, we have the following parameters that can be used in our computation:

y = -5x + 10

The above equation is a linear function

As a general rule of functions and relations

All linear functions are functions

This is because they pass the vertical line test

So, the true statement is (d)

Hence, the relation y = -5x + 10 is a function because (d) yes, because it passes the vertical line test.

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Complete question

Does this graph show a function? Explain how you know.

y = -5x + 10

A. No; there are y-values that have more than one x-value.

B. Yes; there are no y-values that have more than one x-value.

C. No; the graph fails the vertical line test.

D. Yes; the graph passes the vertical line test.

The areas of the circular sectors are listed below:

Case 7: A = 50π / 3 in²

Case 8: A = 177.884 cm²

Case 9: A = 937.312 m²

Case 10: A = 10π / 3 ft²

In this problem we must determine the areas of four circular sectors, whose area formula is equal to:

A = (θ / 360°) · π · r²

Where:

Now we proceed to determine the areas:

Case 7

A = (60 / 360) · π · (10 in)²

A = 50π / 3 in²

Case 8

A = (104 / 360) · π · (14 cm)²

A = 177.884 cm²

Case 9

A = (137 / 360) · π · (28 m)²

A = 937.312 m²

Case 10

A = (75 / 360) · π · (4 ft)²

A = 10π / 3 ft²

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Step-by-step explanation:

To find the equation of the tangent plane to the surface at (3, 4, ln 5), we need to first find the partial derivatives of h with respect to x and y:

hx(x, y) = 2y^2/x

hy(x, y) = 2x^2/y

Then, we can plug in the point (3, 4) to get the partial derivatives evaluated at that point:

hx(3, 4) = 2(4^2)/3 = 32/3

hy(3, 4) = 2(3^2)/4 = 9/2

Now we can use the point-normal form of the equation of a plane, where the normal vector is given by ⟨hx(3, 4), hy(3, 4), -1⟩:

hx(3, 4)(x - 3) + hy(3, 4)(y - 4) - (z - ln 5) = 0

Substituting in the values for hx(3, 4) and hy(3, 4), we get:

(32/3)(x - 3) + (9/2)(y - 4) - (z - ln 5) = 0

Simplifying, we get:

(32/3)x + (9/2)y - z = 55/6

So the equation of the tangent plane to the surface at (3, 4, ln 5) is (32/3)x + (9/2)y - z = 55/6.

The equation for g(x) in vertex form is [tex]g(x) = ax^2[/tex], where "a" represents a constant that determines the shape and direction of the parabola.

The vertex form of a quadratic equation is given by:

[tex]g(x) = a(x - h)^2 + k[/tex]

where (h, k) represents the vertex of the parabola.

Since g(x) is a translation of [tex]f(x) = x^2[/tex], the vertex of g(x) will be the same as the vertex of f(x). The vertex of [tex]f(x) = x^2[/tex] is (0, 0).

So, the equation for g(x) in vertex form is:

[tex]g(x) = a(x - 0)^2 + 0\\g(x) = a(x^2)\\g(x) = ax^2[/tex]

Therefore, the equation for g(x) in vertex form is [tex]g(x) = ax^2[/tex], where "a" represents a constant that determines the shape and direction of the parabola.

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The distance between the mirror and the 20-foot tree is 32 feet.

The idea of comparable triangles can be used to calculate the separation between the mirror and the 20-foot tree.

Let's think about the triangles the man, the mirror, and the tree created. Similar triangles have comparable sides that are equal in ratio.

The dude is standing 8 feet away from the mirror and is 5 feet tall. As a result, we may establish the following ratio:

(Height of the man) / (Distance of the man from the mirror) = (Height of the tree) / (Distance of the tree from the mirror)

Substituting the known values:

5 / 8 = 20 / x

Where x represents the distance of the tree from the mirror.

Now, we can solve for x:

5x = 8 * 20

5x = 160

x = 160 / 5

x = 32

Therefore, the distance between the mirror and the 20-foot tree is 32 feet.

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Answer:

**each problem is slightly different.  See explanations below**

Step-by-step explanation:

Problem 13. SSS

From the diagram, we're given that ML is congruent to CN.  Also, side NL is shared, so side NL is congruent to side LN.  We need the third side, so we need MN congruent to CL (tip to shared segment)

Problem 14. SAS

From the diagram, we're given that GF is congruent to XW.  Also, angle G is congruent to angle X.  To use SAS, we need two sides and the angle between them, so we need a side from each triangle that will "trap" the given angle.  Therefore, we need GH congruent to XY (angle vertex to outside)

Problem 15. SSS

From the diagram, we're given that DE is congruent to RS, and EF is congruent to ST.  For SSS, we need the third side, so we need DF congruent to RT (vertex touching side II to vertex touching side III)

Problem 16. ASA

From the diagram, we're given that angle C is congruent to angle G, and angle D is congruent to angle H.  To use ASA, we need two angles and the side between those two angles, so we need the sides from each triangle that are between the vertices of the two given angles.  Therefore, we need CD congruent to GH (side from angle I to angle II)

Problem 17. SAS

From the diagram, we're given that VW is congruent to EF, and WX is congruent to FG.  To use SAS, we need two sides and the angle between them, so we need a the angle trapped by the two given sides from each triangle.  Therefore, we need angle W congruent to angle F (angle between side I and side II)

Problem 18. ASA

From the diagram, we're given that angle XWV is congruent to angle HWV.  Also, the two triangles share side WV, so WV is congruent to WV.  To use ASA, we need two angles and the side between those two angles, so we need the other angle from each triangle that will trap the given side.  Therefore, we need angle XVW congruent to angle HVW (angle from outside vertex, to shared tip, along shared side)

Answer:

x = 47

Step-by-step explanation:

The sum of the angles of a triangle is 180

31+102 + x =180

x+133=180

Subtract 133 from each side

x = 180-133

x = 47

we know that,

★ Sum of angles of a triangles is 180°

# According To The Question:-

[tex] \sf \: \longrightarrow \: x + 102 + 31 = 180[/tex]

[tex] \sf \: \longrightarrow \: x + 133= 180[/tex]

[tex] \sf \: \longrightarrow \: x = 180 - 133[/tex]

[tex] \sf \: \longrightarrow \: x = 47 \degree[/tex]

_____________________________________

The solution is:  the dimensions of the rectangle is:

The length is 28.667 meters and the width is 56.334 meters.

Here, we have,

We know that to find the area of a rectangle its length x width

so to solve your problem you would do x+ 2 + 2x + 3 = 91

then solve it

add xs together x3 + 2 + 3 = 91

add other values x3 + 5 = 91

                                 -5      -5

                                  x3 = 86

the divide by 3

x = 26.667

Then to finish the question replace x with 26.667 and do the math

2(26.667) + 3 = 56.334

26.667 + 2 = 28.667

so, we get,

Width: 56.334

Length: 28.667

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Given that Y1, Y2, ..., Yn are independent and identically distributed random variables from a power family distribution with parameters alpha and theta = 3.

we need to find the expected value of Y1, i.e., E(Y1). Using the formula for the expected value of the power family distribution, we have:

E(Y1) = [alpha / (alpha + 1)] * theta = [alpha / (alpha + 1)] * 3

Substituting theta = 3, we get:

E(Y1) = 3 alpha / (alpha + 1)

To derive the method-of-moments estimator for alpha, we equate the sample mean with the population mean as follows:

sample mean = (1/n) * (Y1 + Y2 + ... + Yn) = [alpha / (alpha + 1)] * 3

Solving for alpha, we get:

alpha = (3 * sample mean) / (3 - sample mean)

Therefore, the method-of-moments estimator for alpha is (3 * sample mean) / (3 - sample mean).

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Answer:

b = 4[tex]\sqrt{3}[/tex] , c = 8

Step-by-step explanation:

using the tangent and cosine ratios in the right triangle and the exact values

tan60° = [tex]\sqrt{3}[/tex] , cos60° = [tex]\frac{1}{2}[/tex] , then

tan60° = [tex]\frac{opposite}{adjacent }[/tex] = [tex]\frac{b}{4}[/tex] = [tex]\sqrt{3}[/tex] ( multiply both sides by 4 )

b = 4[tex]\sqrt{3}[/tex]

then

cos60° = [tex]\frac{adjacent}{hypotenuse}[/tex] = [tex]\frac{4}{c}[/tex] = [tex]\frac{1}{2}[/tex] ( cross- multiply )

c = 4 × 2 = 8

Answer:

1.2 seconds

Step-by-step explanation:

100-4=96

96/80 = 1.2

Answer:      1 24/80 of a second

Step-by-step explanation:

Well so if you are at 4 ft after 1 second you need 16/80 of a second to reach 100 feet above because 80 then plus 16 plus the addition 4 ft that you are above the water would be 100 feet.

Yeah it is 264/1320 and I just divide both of them by smaller numbers multiple times until it can't be simplified anymore.

264/1320÷2=132/660

132/660÷2=66/330

66/330÷2=33/165

33/164÷11=3/15

3/15÷3=1/5

So the simplified version of 64/1320 is 1/5.

Hope this helps! :)

Answer:

Step-by-step explanation:

To calculate the probability of rolling a sum of 10 with two dice, we need to find the number of ways we can get a sum of 10 and divide that by the total number of possible outcomes. The sum of 10 can be obtained in three ways: (4, 6), (5, 5), and (6, 4). There are 36 possible outcomes when rolling two dice, since there are 6 possible outcomes for the first die and 6 possible outcomes for the second die. Therefore, the probability of rolling a sum of 10 is 3/36, which simplifies to 1/12.

The probability you will roll a sum of 10 is 1/12.

We have,

Probability determines the chances that an event would happen. The probability the event occurs is one and the probability that the event does not occur is 0. The more likely the event is to happen, the closer the probability value would be to 1. The less likely it is for the event not to happen, the closer the probability value would be to zero.

To calculate the probability of rolling a sum of 10 with two dice, we need to find the number of ways we can get a sum of 10 and divide that by the total number of possible outcomes.

The sum of 10 can be obtained in three ways: (4, 6), (5, 5), and (6, 4).

The probability you will roll a sum of 10 = total times a sum of 10 is derived / total sample spaces

so, we get,

total times a sum of 10 is derived = (4 + 6) , (6 +4) , (5 + 5)

There are 36 possible outcomes when rolling two dice, since there are 6 possible outcomes for the first die and 6 possible outcomes for the second die.

Total sample spaces = 36

The probability you will roll a sum of 10 = 3/36 = 1/12

Therefore, the probability of rolling a sum of 10 is 3/36, which simplifies to 1/12.

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-2 is the equivalent average rate of change of f(x) with the interval.

The formula for calculating the rate of change of a function is expressed as:

[tex]f'(x) = \frac{f(b)-f(a)}{b-a}[/tex]

Given the function f(x) = 2x² + 12x + 16 with the interval [-3, -2]

f(-3) =  2(-3)² + 12(-3) + 16

f(-3) = 2(9) - 36 + 16

f(-3) = 18 - 20

f(-3) = -2

Similarly:

f(-2) =  2(-2)^2 + 12(-2) + 16

f(-2) = 2(4) - 24 + 16

f(-2) = 8 - 8

f(-2) = 0

Substitute the resulting values:

[tex]f'(x) = \frac{f(-3)-f(-2)}{-3-(-2)}\\f'(x)=\frac{-2-0}{-1}\\f'(x)=-2[/tex]

Hence the average rate of change of f(x) within the given interval is -2.

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Answer:

To test the null hypothesis that the mean mark is equal to 100 against the alternative that the mean mark is greater than 100, we can use a one-sample t-test since the population variance is unknown. Here's how you can perform the test:

Step 1: State the null and alternative hypotheses:

- Null hypothesis (H₀): The mean mark is equal to 100.

- Alternative hypothesis (H₁): The mean mark is greater than 100.

Step 2: Set the significance level (α):

In this case, the significance level is given as 0.05 or 5%.

Step 3: Compute the test statistic:

The test statistic for a one-sample t-test is calculated using the formula:

t = (X - μ) / (s / √n)

where X is the sample mean, μ is the population mean under the null hypothesis, s is the sample standard deviation, and n is the sample size.

Given:

X = 110 (sample mean)

s = 8 (sample standard deviation)

n = 13 (sample size)

μ (population mean under the null hypothesis) = 100

Substituting the values into the formula, we get:

t = (110 - 100) / (8 / √13)

t = 10 / (8 / √13)

t ≈ 3.012

Step 4: Determine the critical value:

Since the alternative hypothesis is one-tailed (greater than), we need to find the critical value for a one-tailed test at a 5% significance level with (n - 1) degrees of freedom. In this case, the degrees of freedom are 13 - 1 = 12.

Using a t-distribution table or statistical software, the critical value at α = 0.05 and 12 degrees of freedom is approximately 1.782.

Step 5: Make a decision:

If the test statistic t is greater than the critical value, we reject the null hypothesis; otherwise, we fail to reject the null hypothesis.

In this case, the test statistic t is approximately 3.012, which is greater than the critical value of 1.782. Therefore, we reject the null hypothesis.

Step 6: State the conclusion:

Based on the sample data, there is sufficient evidence to support the claim that the mean mark is greater than 100.

Step-by-step explanation:

The given series is ∑(n!)(k^n)((kn)!)x^n. To find the radius of convergence, the radius of convergence for the given series is 0.

The given series is ∑(n!)(k^n)((kn)!)x^n. To find the radius of convergence, we can use the Ratio Test. The Ratio Test states that the radius of convergence R is given by:
R = 1/lim (n→∞) |(a_(n+1))/a_n|
where a_n represents the nth term of the series. For our series, a_n = (n!)(k^n)((kn)!)x^n. Let's find the ratio
|(a_(n+1))/a_n| = |[((n+1)!)(k^(n+1))((k(n+1))!)x^(n+1)]/[(n!)(k^n)((kn)!)x^n]|
Simplifying, we get
|(a_(n+1))/a_n| = |(n+1)(k)(((k(n+1))!))/((kn)!)x|
Now, let's take the limit as n approaches infinity:
lim (n→∞) |(n+1)(k)(((k(n+1))!))/((kn)!)x|
Since both the numerator and the denominator have factorials that grow rapidly, this limit is infinity. Therefore, the radius of convergence is:
R = 1/∞ = 0
So, the radius of convergence for the given series is 0.

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[tex]~~~~~~~~~~~~\textit{quadratic formula} \\\\ \stackrel{\stackrel{a}{\downarrow }}{1}x^2\stackrel{\stackrel{b}{\downarrow }}{-12}x\stackrel{\stackrel{c}{\downarrow }}{-35}=y \qquad \qquad x= \cfrac{ - b \pm \sqrt { b^2 -4 a c}}{2 a} \\\\\\ x= \cfrac{ - (-12) \pm \sqrt { (-12)^2 -4(1)(-35)}}{2(1)} \implies x = \cfrac{ 12 \pm \sqrt { 144 +140}}{ 2 } \\\\\\ x= \cfrac{ 12 \pm \sqrt { 284 }}{ 2 }\implies x= \cfrac{ 12 \pm 2\sqrt { 71 }}{ 2 }\implies x=6\pm\sqrt{71} \\\\[-0.35em] ~\dotfill[/tex]

[tex]x=6+\sqrt{71}\implies x-6-\sqrt{71}=0 \\\\[-0.35em] ~\dotfill\\\\ x=6-\sqrt{71}\implies x-6+\sqrt{71}=0 \\\\[-0.35em] ~\dotfill\\\\ ~\hfill {\Large \begin{array}{llll} (x-6-\sqrt{71})(x-6+\sqrt{71}) \end{array}}~\hfill[/tex]

When determining whether or not a measured effect can be distinguished from zero, we are interested in statistical significance.

Statistical significance refers to the likelihood that the results of a study are not due to chance. In other words, it assesses whether the effect observed in a sample is likely to be a true effect in the population, or whether it could have occurred by chance. Statistical significance is typically assessed using hypothesis testing and a significance level (usually set at 0.05), which represents the probability of obtaining the observed results or more extreme results under the assumption that the null hypothesis (i.e., no effect) is true. If the probability is less than the significance level, the result is said to be statistically significant, indicating that the null hypothesis can be rejected and the observed effect is likely a true effect. Practical significance, on the other hand, refers to the importance or relevance of the observed effect in the context of the research question or real-world application.

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The variable c indicates the number of crimes in a city with two neighborhoods—one rich and one poor—both of the same size, where the city employs a police force of 20 officers and p represents the number of police officers. Here option C is the correct answer.

To allocate police resources effectively between rich and poor neighborhoods, crime rates, severity, and community policing should be considered to ensure the safety and well-being of all residents.

The allocation of police resources in a city with two neighborhoods - one rich and one poor - presents a challenging issue. In this scenario, both neighborhoods have the same population size, but different socio-economic characteristics. The rich neighborhood may have lower crime rates due to better security measures and access to resources, while the poor neighborhood may experience higher crime rates due to factors such as poverty, lack of education, and unemployment.

Given the budgetary restrictions, the city employs a police force of 20 officers. This raises the question of how to allocate these officers between the two neighborhoods to ensure the most effective use of resources.

One approach to this issue is to allocate officers based on crime rates. If the rich neighborhood has lower crime rates, then fewer officers can be assigned there, while more officers can be allocated to the poor neighborhood where crime rates are higher. This approach ensures that police resources are used where they are most needed.

Another approach is to allocate officers based on the severity of crimes. If the rich neighborhood has fewer but more severe crimes, then more officers may need to be assigned there to handle these cases. On the other hand, if the poor neighborhood has more but less severe crimes, then fewer officers may be required, but they may need to be more vigilant and proactive in preventing crime.

It is also important to consider community policing as a strategy to improve relationships between police officers and residents in both neighborhoods. By building trust and fostering communication, residents may be more willing to work with law enforcement to prevent crime and promote safety.

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Complete question:

What does the variable c denote in a city with two neighborhoods - one rich and one poor - both with equal-sized populations, where the city employs a police force of 20 officers and p represents the number of police officers?

A) The number of police officers

B) The population of the rich neighborhood

C) The population of the poor neighborhood

D) The number of crimes.

Answer:

Step-by-step explanation:

total number of sticks = 47+36+31= 114

Because you draw with replacement to find the probability of two events happening you simply just multiply them

p(books without pics) = #books without pics /#sticks

47/114 = 41.2280702%

p(audiobooks)= #audiobooks/ #sticks

31/114= 27.1929825%

p(books without pics and audiobooks)= p(books without pics) * p(audiobooks)

41.2280702%*27.1929825% = 11.21%

So, the equivalent expression for sin(2β) * cos(β) is 2sin(β)cos²(β) for all values of β where sin(2β) * cos(β) is defined.

We need to find an expression equivalent to sin(2β) * cos(β) for all values of β where it is defined. To do this, let's use the double-angle identity for sine.
The double-angle identity for sine states that sin(2α) = 2sin(α)cos(α). In our case, we have sin(2β) instead of sin(2α), so we can replace α with β in the identity:
sin(2β) = 2sin(β)cos(β)
Now, we can substitute this expression for sin(2β) into our original expression:
sin(2β) * cos(β) = (2sin(β)cos(β)) * cos(β)
Next, we need to simplify the expression by multiplying the terms:
2sin(β)cos²(β)
So, the equivalent expression for sin(2β) * cos(β) is 2sin(β)cos²(β) for all values of β where sin(2β) * cos(β) is defined.

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We can see that the pattern progresses by adding 3 to the previous perfect square to obtain the next term. The next few terms of the sequence would be:

25 (16 + 3)

36 (25 + 3)

49 (36 + 3)

64 (49 + 3)

81 (64 + 3)

...

We can continue this pattern to find as many terms as desired.

What is Number Sequences?

In mathematics, a number sequence is an ordered list of numbers that follow a specific pattern or rule. Each number in the sequence is called a term, and the position of a term in the sequence is called its index.

The given pattern appears to be a sequence of perfect squares starting from 1 and increasing by 3 at each step. We can verify this by observing that:

The first term is 1 which is a perfect square.

The second term is 4 which is a perfect square and is obtained by adding 3 to the previous term 1.

The third term is 9 which is a perfect square and is obtained by adding 3 to the previous term 4.

The fourth term is 16 which is a perfect square and is obtained by adding 3 to the previous term 9.

Therefore, we can see that the pattern progresses by adding 3 to the previous perfect square to obtain the next term. The next few terms of the sequence would be:

25 (16 + 3)

36 (25 + 3)

49 (36 + 3)

64 (49 + 3)

81 (64 + 3)

...

We can continue this pattern to find as many terms as desired.

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Hello! To find the height of the first electronic computer with the given dimensions and volume, we can use the formula for the volume of a rectangular prism:

Volume = Length × Width × Height

We are given the following dimensions:
Length = 96 feet
Width = 2.5 feet
Approximate Volume = 3000 cubic feet

Let's solve for the height:

3000 = 96 × 2.5 × Height

First, we will multiply the length and the width:

240 = 96 × 2.5

Now, divide both sides by 240 to find the height:

Height = 3000 / 240

Height ≈ 12.5 feet

So, the height of the computer was approximately 12.5 feet.

B

H

E

C

Standard form must be between 1 and 9

Answer:

18.136 units of distance

Step-by-step explanation:

d = sqrt((x2 - x1)^2 + (y2 - y1)^2)

where (x1, y1) = (2, 1) and (x2, y2) = (12, 18)

d = sqrt((12 - 2)^2 + (18 - 1)^2)

= sqrt(10^2 + 17^2)

= sqrt(329)

≈ 18.136

Therefore, the rock traveled approximately 18.136 units of distance.

The gradient field of a function is a vector field that points in the direction of the maximum increase of the function.  In the case of f(x,y,z) = x^2/4 + y^2/4 + z^2 - 1/2, the gradient field is given by <x/2, y, 2z>.

The gradient of a scalar field is a vector field that points in the direction of the maximum rate of increase of the scalar field, and its magnitude represents the rate of increase.

To find the gradient field of f(x,y,z), we first calculate the partial derivatives of f with respect to x, y, and z. The partial derivative of f with respect to x is 2x/4y2/4z2, the partial derivative of f with respect to y is -x2/2y3/4z2, and the partial derivative of f with respect to z is -x2/4y2/2z3/2. The gradient of f is then given by the vector field (2x/4y2/4z2)i - (x2/2y3/4z2)j - (x2/4y2/2z3/2)k, where i, j, and k are the unit vectors in the x, y, and z directions, respectively. This vector field represents the direction and magnitude of the maximum rate of increase of f at any point in space.

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The slope of the line that passes through the points ( -4,5) and (2,-3) is -4/3

The slope of a line is a measure of its steepness. It is also called gradient. It is the change in value on the vertical axis to the change in value on the horizontal axis.

Y axis is the vertical axis and x axis is the horizontal axis.

slope = [tex]y_2 -y_1)/x_2-x_1[/tex]

[tex]y_2[/tex] = -3

[tex]y_1[/tex]= 5x2 = 2x1 = -4

slope = -3-5/(2-(-4)

= -8/6

= -4/3

Therefore the slope of the line is -4/3

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The 1st Quartile germination rate is 92%, the 1st Quartile germination rate represents the threshold below which 25% of the germination rates fall.

To determine this, we need to arrange the germination rates in ascending order and find the value that corresponds to the 25th percentile.

In this case, we have a packet of 160 seeds with 95% germination rate. To find the 1st Quartile germination rate, we need to consider the germination rates of the remaining 5% of seeds that did not germinate.

Since 92% is the claimed germination rate mentioned on the seed packet, we can assume that the 5% of seeds that did not germinate fall below this claimed rate. Therefore, the 1st Quartile germination rate is 92%.

The 1st Quartile, also known as the lower quartile or 25th percentile, divides a dataset into four equal parts. It represents the threshold below which 25% of the data points fall.

In this scenario, we have a packet of 160 seeds with a 95% germination rate. This means that 95% of the seeds successfully germinated. To find the 1st Quartile germination rate, we need to consider the remaining 5% of seeds that did not germinate.

Since the information on the seed packet claims a germination rate of 92%, we can assume that the 5% of seeds that did not germinate fall below this claimed rate.

As a result, the 1st Quartile germination rate is 92%. This indicates that 25% of the seeds in the packet had a germination rate below 92% while the remaining 75% had a germination rate equal to or higher than 92%.

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