MATHEMATICS COLLEGE

A commercial jet has been instructed to climb from its present altitude of 6000 feet to a cruising altitude of 30,000 feet. If the plane ascends at a rate of 4000 ​ft/min, how long will it take to reach its cruising​ altitude? The plane will take nothing minutes.

Answers

Answer 1
Answer: An easier way of doing this would be to subtract the initial attitude from the final attitude and divide by the rate of increase
= 30000 - 6000÷4000
= 24000÷4000
=6mins

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Write in slope-intercept form with the given information

Answers

you have to use point slope form

point slope form: y - y1 = m(x - x1)

x1 and y1 are the x and y values of the given point

m is the slope

so, just plug in the numbers:

y-3 = -2(x + 8)

now solve to put into slope intercept form (y = mx + b)

y-3 = -2x - 16

ANSWER: y = -2x -13

Answer:

y=-2x-13

Step-by-step explanation:

I am not sure if these what they want.

y-b=m(x-a)

y-3=-2(x--8)

y-3=-2x-16

add 3 to each side

y=-2x-13

Enter your answer in the box

____

Answers

Answer:

  \boxed{2144}

Step-by-step explanation:

The sum can be found by adding the parts:

  \sum\limits_(n=1)^(32){(4n+1)}=4\sum\limits_(n=1)^(32){n}+\sum\limits_(n=1)^(32){1}=4\cdot(32\cdot 33)/(2)+32\n\n= 2112+32=\boxed{2144}

__

The sum of numbers 1 to n is n(n+1)/2.

An experiment consists of drawing 1 card from a standard 52 card deck? What is the probability of drawing a queen?

Answers

4/52, or 1/13, or 8 percent(not very accurate or precise).  You take the number of queens in a deck(4) and put it over the total number of cards in a deck(52).  This gives you a probability of 1 in 13 or about 8 percent
4 out of 52         which is equal to 1/13

Tanya enters a raffle at the local fair, and is wondering what her chances of winning are. If her probability of winning can be modeled by a beta distribution with α = 5 and β = 2, what is the probability that she has at most a 10% chance of winning?

Answers

Answer:

P(X<0.1)= 5.5x10^(-5)

Step-by-step explanation:

Previous concepts

Beta distribution is defined as "a continuous density function defined on the interval [0, 1] and present two parameters positive, denoted by α and β, both parameters control the shape. "

The probability function for the beta distribution is given by:

P(X)= (x^(\alpha-1) (1-x)^(\beta -1))/(B(\alpha,\beta))

Where B represent the beta function defined as:

B(\alpha,\beta)= (\Gamma(\alpha)\Gamma(\beta))/(\Gamma(\alpha+\beta))

Solution to the problem

For our case our random variable is given by:

X \sim \beta (\alpha=5, \beta =2)

We can use the following R code to plot the distribution for this case:

> x=seq(0,1,0.01)

> plot(x,dbeta(x,5,2),main = "Beta distribution a=5, b=2",ylab = "Probability")

And we got as the result the figure attached.

And for this case we want this probability, since we want the probability that she has at most 10% or 0.1 change of winning:

P(X<0.1)

And we can find this probability with the following R code:

> pbeta(0.1,5,2)

[1] 5.5e-05

And we got then this : P(X<0.1)= 5.5x10^(-5)

Given the exponential equation y = yoxQq describe each of the following below:y is
yo is
x is
Q is
q is

Answers

Answer:

Step-by-step explanation:

In 1970, 36% of first year college students thought that being "very well off financially is very important or essential." By 2000 the percentage had increased up to 74%. These percentages are based on nationwide multistage cluster samples.a) Is the difference important? Or does teh question make sense?
b) Does it make sense to ask if the difference is statisically significante? Can you answer on the basis of the informations given?
c) Repeat b), assuming the percentages are based on independant simple random samples of 1,000 first year college students drawn each year.

Answers

Answer:

a.  The difference is important but the question does not make sense

b. Yes, it makes sense to ask if the difference is statistically significant.

c. Please check explanation

Step-by-step explanation:

From the question, we identify the following relation;

H_(o): P-P_(1) = 0

H_(A) : P-P_(1) ≠ 0

a) The difference is important as asked, but the cultural atmosphere difference of over 30 years makes the question somehow not making sense

b) Yes, it makes sense. In order to answer, it is necessary to know the sample size of the year  2000 survey.

We can answer the question on the basis of the information given.

c) We proceed here as follows;

α = 0.05 , Z_(alpha/2) = 1.96 ( This is the critical value)

Thus, z = (0.74-0.36)/√(0.36-0.64)/1000 = 25.03

We make the following conclusions; Since 25.03 > 1.96, the null hypothesisH_(o)  is rejected which means that the proportion of people who think being well officially is important has changed since 1970.
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