Answer:
The height of water in the second tank is 2ft
Step-by-step explanation:
In this question, we are asked to calculate the height of water in a second tank if the content of a first tank is poured into the second tank.
The plot twist to answering this question is that we need to note the volume of water in the first tank. Although the first tank has dimensions of 2ft by 3ft by 2ft height, the water in the tank only rose to a height of 1 feet.
Hence, to calculate the volume of the water in the first tank, the width and the length of the tank still remain the same, the only difference here is that we work with a height of 1 feet since the Water is not full.
Mathematically, the volume of water present in the tank will be;
V = l * b * h
V = 4 * 3 * 1 = 12 cubic feet
Now, this content is emptied into a second tank. Since the volume of water here is the same; this means;
12 cubic feet = 3 * 2 * h
We ignore the 4ft height as it is just the height of the tank and not the height of the water in the tank
6h = 12 cubic feet
h = 12/6 = 2 ft
Answer:
65°
Step-by-step explanation:
All triangles equal 180 degrees. So just subtract the other values.
Answer:
The volume is 418.93 ft^3
Step-by-step explanation:
Here, we want to find the volume of a cone
Mathematically, we use the formula;
V = 1/3 * pi * r^2 * h
r = 5 ft
h = 16 ft
Substituting these values;
V = 1/3 * 3.142 * 5^2 * 16
V = 418.93 ft^3
Answer: Yes they could.
Step-by-step explanation:
The two pairs of sides given are proportional: 3/7 : 9/21
The two triangles have the side:side ratio, meaning they are similar
Because they are similar, their hypotenuses <em>could</em> lie along the same line, not guaranteed, but possible.
When n is small (less than 30), how does the shape of the t distribution compare to the normal distribution then"it is flatter and wider than the normal distribution."
<h3>What is normal distribution?</h3>
The normal distribution explains a symmetrical plot of data around the mean value, with the standard deviation defining the width of the curve. It is represented graphically as "bell curve."
Some key features regarding the normal distribution are-
- The normal distribution is officially known as the Gaussian distribution, but the term "normal" was coined after scientific publications in the nineteenth century demonstrated that many natural events emerged to "deviate normally" from the mean.
- The naturalist Sir Francis Galton popularized the concept of "normal variability" as the "normal curve" in his 1889 work, Natural Inheritance.
- Even though the normal distribution is a crucial statistical concept, the applications in finance are limited because financial phenomena, such as expected stock-market returns, do not fit neatly within a normal distribution.
- In fact, prices generally follow a right-skewed log-normal distribution with fatter tails.
As a result, relying as well heavily on the a bell curve when forecasting these events can yield unreliable results.
To know more about the normal distribution, here
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