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2 years ago

Find the area a triangle with a base of 3 ft and a height of 2/3 ft

Mathematics

2 answers:

ASHA 777 [7]2 years ago

5 0

Answer:

1 ft^2

Step-by-step explanation:

The area of a triangle is given by

A = 1/2 bh where b is the base and h is the height

A = 1/2 ( 3) * ( 2/3)

A = 3/2* 2/3

A =1

madam [21]2 years ago

4 0

Answer:

1 ft^2

Step-by-step explanation:

The formula for the area of a triangle is as follows, a=b*h*1/2

Now, let's plug in the values to match your question. A=3*2/3*1/2

Lastly, solve. 3*2/3=6/3=2. Then divide 2 by 1/2=1.

Add the unit to make it 1 ft^2

Hope this helps!

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Hatshy [7]

Answer:

The first 4 are correct and the last one is incorrect

Step-by-step explanation:

1. The diameter of the circle is 30.8 m ( Correct )

Radius = 15.4 so diameter is 2 times the radius which is 30.8 m

2. The circumference in terms of π is 30.8 π ( Correct )

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Circumference = π × 30.8

Circumference = 30.8 π

3 . The circumference of the circle can be found using 2 × π × 15 . 4 ( Correct )

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Step-by-step explanation:

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3 years ago

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Dafna1 [17]

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lbvjy [14]

Answer:

Mean: 810.51

Standard deviation: 128.32

Step-by-step explanation:

First, we calculate the sample mean. We have 35 data samples, so we compute it as $\displaystyle \frac{562 + .... + 753}{35}$ .

In general, given a set of n samples $\{ X_1,...,X_n\}$ , we calculate the sample mean as

$\displaystyle \bar{X} = \sum_{i=1}^n \frac{X_i}{n}$ .

For the standard deviation $\sigma$ , we first begin by calculating it's square. It can be obtained from the formula

$\displaystyle \sigma ^2 = \sum_{i=1}^{n} \frac{(X_i - \bar{X})^2}{n-1}$

By taking square root after computing the right hand side, we attain the desired value.

The attached image shows the dot diagram of this sample. The bottom pink vertical line shows the mean, and the two horizontal pink lines have a lenght of $\sigma$ .

The standard deviation means "The average expected distance a new sample will be from the mean". That's why usually, data samples which are denser around the mean have smaller standard deviations (as opposed to distributions who have a lot of values far away from the mean, which will make the standard deviation grow bigger).

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