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kotegsom [21]
2 years ago
14

A sailor judges the distance to a lighthouse by holding a ruler at arm's length and measuring the apparent height of the lightho

use. He knows that the lighthouse is actually 60 feet tall. If it appears to be 3 inches tall when the ruler is held 2 feet from his eye, how far away is it?

Mathematics
2 answers:
telo118 [61]2 years ago
8 0
<span>The ratio of the ruler’s height to the distance from eye to ruler, which is the tangent of the angle subtended at the eye by the ruler’s height, must be the same as the ratio of the lighthouse’s height to its distance, which is the tangent of the same angle. Since 3 inches is ¼ foot, we have ¼/2=60/D, and solving for D gives D= 2×60/¼ = 4 × 120 = 480 feet</span>
Oksanka [162]2 years ago
6 0

Solution:

Actual Height of Light House = 60 Feet

Comparing with the ruler

Height of Ruler = 3 inches

Distance between eye and Ruler = 2 feet

Let Actual Distance between Light house and Ruler = x feet

As the two triangles are similar by AA Criteria, so their sides  will be proportional to each other, i.e

\frac{60}{3}=\frac{x}{2}\\\\ 20=\frac{x}{2}\\\\ x=40 feet

So, Distance between Light house and Ruler = 40 feet


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The information below is the number of daily emergency service calls made by the volunteer ambulance service of Walterboro, Sout
mafiozo [28]

Answer:

Step-by-step explanation:

Hello!

The variable of interest is

X: The number of emergency service calls made by the volunteer ambulance service of Walterboro, South Carolina for 50 days.

a)

In the first column, you have the possible number of emergency calls made, in the second column, you have the observed absolute frequency (fi) for each value of the variable.

To establish the probability distribution you have to calculate the relative frequency (hi) for each value of X.

The formula for the relative frequency is

hi= fi*n where i= 0, 1, 2, 3, 4

X₁= 0

f₁= 8

h₁= 8/50= 0.16

X₂= 1

f₂= 10

h₂= 0.20

X₃= 2

f₃= 22

h₃= 22/50= 0.44

X₄= 3

f₄= 9

h₄= 9/50= 0.18

X₅= 4

f₅= 1

h₅= 1/50= 0.02

(See attachment)

b)

The variable of interest is a cuantitative discrete variable, so this is an example of a driscrete distribution.

Discrete variables are numerical and take certain numbers within its range of definition, contrary to the continuous variables that can take any value within the range of definition of the variable.

Another example of a discrete variable is "the money", If the variable is "I have at most 10 dollars in my wallet", the range of definition goes from 0 dollars to 10 dollars.

c) To calculate the mean when the data is arranged in a frequency table you have to use the following formula:

X[bar]= ∑Xihi= (0*0.16)+(1*0.2)+(2*0.44)+(3*0.18)+(4*0.02)= 1.7

This means that they expect an average of 1.7 calls per day.

d) The formula for the standard deviation is:

S=\sqrt{\frac{1}{n-1}[sumX^2fi-\frac{(sumXfi)^2}{n} ] }

∑X²fi= (0²*8)+(1²*10)+(2²*22)+(3²*9)+(4²*1)=  195

∑Xfi= (0*8)+(1*10)+(2*22)+(3*9)+(4*1)= 85

S=\sqrt{\frac{1}{49}[195-\frac{(85)^2}{50} ] }= 1.015

I hope this helps!

3 0
2 years ago
13 over 15 divided by 7 over 10 in simplest form
PilotLPTM [1.2K]
If you would like to write (13/15) / (7/10) in the simplest form, you can calculate this using the following steps:

(13/15) / (7/10) = <span>(13/15) * (10/7) = (13 * 2) / (3 * 7) = 26/21 = 1 5/21
</span>
The correct result would be <span>26/21.</span>
8 0
2 years ago
You’re working in a pharmacy, and are making a table to help with dosage amounts for a certain drug. The recommended dosage is 4
Sergeu [11.5K]

Answer: The children weighing 10 pounds, 15 pounds and 30 pounds require 12 teaspoons , 18 teaspoons, 36 teaspoons respectively.

Step-by-step explanation:

Given, The recommended dosage is 40 milligrams per 2.2 pounds of body weight, divided into three daily doses and taken every 8 hours.

i.e. for 1 pound of body weight required dosage per day= \dfrac{40}{2.2}=18.18\ ml

Each dose consist = \dfrac{18.18}{3}=6.06\ ml drug.

so, 1 pound of body weight required 6.06 ml for each dose.

Then, 10 pounds of body weight require 10 x 6.06 ml drug= 60.6 ml

If 1 teaspoon = 5 ml,  then 10 pounds of body weight require (60.6 ml ÷5) = 12.12 ≈12 teaspoons.

15 pounds of body weight require 15 x 6.06 ml drug= 90.9 ml

Then 15 pounds of body weight require (90.9 ml ÷5) = 18.18≈18 teaspoons.

30 pounds of body weight require  30 x 6.06 ml drug= 181.8 ml

Then  30 pounds of body weight require (181.8 ml ÷5) = 36.36 ≈ 36 teaspoons.

Hence, the children weighing 10 pounds, 15 pounds and 30 pounds require 12 teaspoons , 18 teaspoons, 36 teaspoons respectively.

7 0
2 years ago
The average density of Styrofoam is 1.00 kg/m^3. If a Styrofoam cooler is made with outside dimensions of 50.0 x 35.0 x 30.0 cm
Nadusha1986 [10]

Answer:

View graph

Step-by-step explanation:

The closest by default to 1100 cubic inches is taking two side and two front covers and that would give you 1080.12 cubic inches since two of the covers you must subtract 3 cm per side and side which would add 6 cm in total so outside would be 35 cm and indoor 29 cm . According the graph

29*50*3= 4350 * 2 lid = 8700 cm3

30*50*3= 4500*2 lid = 9000 cm3

So 8700+9000 = 17700 cm3 to inches 3 = 1080.12 cm3

5 0
2 years ago
Consider the following regression model: Humidity = β0 + β1Temperature + β2Spring + β3Summer + β4Fall + β5Rain + ε, where the du
FinnZ [79.3K]

Answer:

The regression equation for the winter rainy days is "Humidity = (β0 + β5) + β1Temperature".

Step-by-step explanation:

Given:

Humidity = β0 + β1Temperature + β2Spring + β3Summer + β4Fall + β5Rain + ε ...........(1)

Since there can be only one of spring, summer,fall, and winter at a point in time or in a season, we will have the following when there are winter rainy days:

Spring = 0

Summer = 0

Fall = 0

Rain = 1

Substituting all the relevant values into equation (1) and equating ε also to 0, a reduced form of equation (1) can be obtained as follows:

Humidity = β0 + β1Temperature + (β2 * 0) + (β3 * 0) + (β4 * 0) + (β5 * 1) + 0

Humidity = β0 + β1Temperature + 0 + 0 + 0 + β5 + 0

Humidity = (β0 + β5) + β1Temperature

Therefore, the regression equation for the winter rainy days is "Humidity = (β0 + β5) + β1Temperature".

3 0
2 years ago
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