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olga_2 [115]
3 years ago
10

A right triangle is removed from a rectangle as shown in the figure. Find the area of the remaining part of the rectangle. [Area

of a triangle = 1/2(b)(h)]
Mathematics
1 answer:
IrinaVladis [17]3 years ago
8 0
I found the same problem with its corresponding image.

The rectangle has a length of 8 inches and width of 6 inches.
The right triangle was taken from the width. Its short leg measures 2 inches and the remainder of the width was 2 inches.

Area of the rectangle = Length x Width
A = 8 inches * 6 inches
A = 48 square inches.

Area of a right triangle = 1/2 a h
a is the short leg = 2 inches
h is the long leg = width - remainder of the width = 6 in. - 2 in. = 4 inches.

Area = 1/2 * 2 in. * 4in.
Area = (1*2*4)/2
A = 8/2
A = 4 square inches.

Area of Rectangle - Area of Triangle = Area of remaining figure.

48 sq. in - 4 sq. in. = 44 sq. inches.
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If we get the 100 from number 1 each year for ten years and invest each payment in an account that earns 8% how much will be the
blsea [12.9K]

Answer:

$1,448.66

Step-by-step explanation:

The future value of an annuity with yearly deposits 'P' at an interest rate of 'r' invested for 'n' years is determined by:

FV = P[\frac{(1+r)^n-1}{r}]

For P = $100, r = 0.08 and n = 10 years:

FV = 100[\frac{(1+0.08)^{10}-1}{0.08}]\\FV=\$1,448.66

The amount at the end of the ten years is $1,448.66

4 0
3 years ago
How do I find Mean Absolute deviation again? I forgot. URGENT!
Luba_88 [7]

Answer:

To find the mean absolute deviation of the data, start by finding the mean of the data set. Find the sum of the data values, and divide the sum by the number of data values. Find the absolute value of the difference between each data value and the mean

Step-by-step explanation:

4 0
3 years ago
In a given year, the average annual salary of a NFL football player was $189,000 with a standard deviation of $20,500. If a samp
nika2105 [10]

Answer:

15.15% probability that the sample mean will be $192,000 or more.

Step-by-step explanation:

To solve this problem, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a random variable X, with mean \mu and standard deviation \sigma, a large sample size can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 189000, \sigma = 20500, n = 50, s = \frac{20500}{\sqrt{50}} = 2899.14

The probability that the sample mean will be $192,000 or more is

This is 1 subtracted by the pvalue of z when X = 192000. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{192000 - 189000}{2899.14}

Z = 1.03

Z = 1.03 has a pvalue of 0.8485.

1-0.8485 = 0.1515

15.15% probability that the sample mean will be $192,000 or more.

7 0
3 years ago
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