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3 years ago

Which rule explains why these triangles aren't congruent? see picture below.

Mathematics

1 answer:

Lisa [10]3 years ago

7 0

Answer:

SSS

Step-by-step explanation:

Well, the picture says asks why the triangles are congruent but your question asks why they aren't congruent, so I will just assume that you made a typo, and you really meant: "Which rule explains why these triangles are congruent?"

Well, the triangles have two congruent sides, and they have a common shared side that are both congruent (due to reflexive property), so the triangle theorem SSS (Side-Side-Side) proves that the triangles are both congruent.

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3 years ago

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Lena [83]

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3 years ago

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3 years ago

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Sindrei [870]

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Step-by-step explanation:

3 0

3 years ago

Assume that women's heights are normally distributed with a mean given by mu equals 62.5 in,and a standard deviation given by

Misha Larkins [42]

Answer:

(a) 0.5899

(b) 0.9166

Step-by-step explanation:

Let X be the random variable that represents the height of a woman. Then, X is normally distributed with

$\mu$ = 62.5 in

$\sigma$ = 2.2 in

the normal probability density function is given by

$f(x) = \frac{1}{\sqrt{2\pi}2.2}\exp{-\frac{(x-62.5)^{2}}{2(2.2)^{2}}}$ , then

(a) $P(X < 63) = \int\limits_{-\infty}^{63}f(x) dx$ = 0.5899

(in the R statistical programming language) pnorm(63, mean = 62.5, sd = 2.2)

(b) We are seeking $P(\bar{X} < 63)$ where n = 37. $\bar{X}$ is normally distributed with mean 62.5 in and standard deviation $2.2/\sqrt{37}$ . So, the probability density function is given by

$g(x) = \frac{1}{\sqrt{2\pi}\frac{2.2}{\sqrt{37}}}\exp{-\frac{(x-62.5)^{2}}{2(2.2/\sqrt{37})^{2}}}$ , and

$P(\bar{X} < 63) = \int\limits_{-\infty}^{63}g(x)dx$ = 0.9166

(in the R statistical programming language) pnorm(63, mean = 62.5, sd = 2.2/sqrt(37))

You can use a table from a book to find the probabilities or a programming language like the R statistical programming language.

4 0

3 years ago