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3 years ago

Rays PQ and PS are perpendicular to each other. What is the measure of LRPS plzzzzz

Mathematics

1 answer:

inna [77]3 years ago

3 0

Answer:

m<RPS = 53 degrees

Step-by-step explanation:

Find the diagram attached

From the diagram shown;

m<QPR + m<RPS = 90

Given that;

m<QPR = x

m<RPS = x+16

Substitute into the formula;

m<QPR + m<RPS = 90

x+x+16 = 90

2x+16 = 90

2x = 90-16

2x = 74

x = 74/2

x = 37degrees

Get m<RPS;

Since m<RPS = x+16

m<RPS = 37 + 16

m<RPS = 53 degrees

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nika2105 [10]

Answer: 8

Step-by-step explanation:

slope = rise/run

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3 years ago

Read 2 more answers

4- A manufacturing process produces items whose weights are normally distributed. It is known that 22.57% of all the items produ

galben [10]

Answer:

$\\ \mu = 118\;grams\;and\;\sigma=30\;grams$

Step-by-step explanation:

We need to use z-scores and a standard normal table to find the values that corresponds to the probabilities given, and then to solve a system of equations to find $\\ \mu\;and\;\sigma$ .

<h3>First Case: items from 100 grams to the mean</h3>

For finding probabilities that corresponds to z-scores, we are going to use here a Standard Normal Table for cumulative probabilities from the mean (Standard normal table. Cumulative from the mean (0 to Z), 2020, in Wikipedia) that is, the "probability that a statistic is between 0 (the mean) and Z".

A value of a z-score for the probability P(100<x<mean) = 22.57% = 0.2257 corresponds to a value of z-score = 0.6, that is, the value is 0.6 standard deviations from the mean. Since this value is below the mean ("the items produced weigh between 100 grams up to the mean"), then the z-score is negative.

Then

$\\ z = -0.6\;and\;z = \frac{x-\mu}{\sigma}$

$\\ -0.6 = \frac{100-\mu}{\sigma}$ (1)

<h3>Second Case: items from the mean up to 190 grams</h3>

We can apply the same procedure as before. A value of a z-score for the probability P(mean<x<190) = 49.18% = 0.4918 corresponds to a value of z-score = 2.4, which is positive since it is after the mean.

Then

$\\ z =2.4\;and\; z = \frac{x-\mu}{\sigma}$