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3 years ago

Solve the system of equations without graphing. Show your reasoning. 2y=x-4 4x + 3y = 5

Mathematics

2 answers:

Deffense [45]3 years ago

6 0

Answer:

x=2 and y= -1

Step-by-step explanation:

1) we transform first equation

2y= x-4

2y +4= x

So x= 2y+4

2) we insert equation from 1) into second equation

4*(2y+4)+3y=5

8y+16+3y=5

11y+16=5

11y= -11

y= -1

3) insert y into 1)

x= 2*(-1)+4

x= -2+4

x= 2

skad [1K]3 years ago

3 0

Answer:

the answers are x=-1 and y=-2

Step-by-step explanation:

becuz mafs

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The Census Bureau's Current Population Survey shows that 28% of individuals, ages 25 and older, have completed four years of col

gizmo_the_mogwai [7]

Answer:

19.35% probability that five will have completed four years of college

Step-by-step explanation:

For each individual chosen, there are only two possible outcomes. Either they have completed fourr years of college, or they have not. The probability of an adult completing four years of college is independent of any other adult. So the binomial probability distribution is used to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

In which $C_{n,x}$ is the number of different combinations of x objects from a set of n elements, given by the following formula.

$C_{n,x} = \frac{n!}{x!(n-x)!}$

And p is the probability of X happening.

28% of individuals

This means that $p = 0.25$

For a sample of 15 individuals, ages 25 and older, what is the probability that five will have completed four years of college?

This is P(X = 5) when n = 15. So

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

$P(X = 5) = C_{15,5}.(0.28)^{5}.(0.72)^{10} = 0.1935$

19.35% probability that five will have completed four years of college

5 0

3 years ago

A) choose the linear model that passes through the most data points on the scatterplot.

irina1246 [14]

Answer: b

Explanation:
The line of best fit to a scattergram is obtained in linear regression analysis by minimizing the sum of the squared errors.
For example, in the diagram shown below, there are n data points in the scattergram.
The error for the i-th data point is $e_{i}$ .
The coefficients (a and b) for the line of best fit are determined using calculus, to minimize $\sum_{i=1}^{n} e_{i}^{2}$ .