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lesya [120]
3 years ago
9

What is the midpoint of line segment EF

Mathematics
2 answers:
Levart [38]3 years ago
8 0

E is located at (-2,-4)

F is located at (2,2)


To find the midpoint, add the 2 X values together and divide by two, then do the same with the y values:


X = -2 + 2 = 0/2 = 0

Y = -4 + 2 = -2/2 = -1


The midpoint is located at (0,-1)

Vikentia [17]3 years ago
7 0
To find midpoint you use the equation they gave you! First find point E and F by looking at the coordinates of the graph!
E(-2,-4)
F(2,2)
Now simply plug them in and simplify!
((-2+2)/2),((-4+2)/2))
(0/2,-2/2)
(0,-1) is your midpoint!
I hope this helps!
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Is 70 thousand written in standard form or word form ? Explain
Stolb23 [73]
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5 0
3 years ago
The head of maintenance at XYZ Rent-A-Car believes that the mean number of miles between services is 3639 3639 miles, with a var
Andrei [34K]

Answer:

96.6% probability that the mean of a sample would differ from the population mean by less than 126 miles

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

A reminder is that the standard deviation is the square root of the variance.

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this question:

\mu = 3639, \sigma = \sqrt{145161} = 381, n = 41, s = \frac{381}{\sqrt{41}} = 59.5

Probability that the mean of the sample would differ from the population mean by less than 126 miles

This is the pvalue of Z when X = 3639 + 126 = 3765 subtracted by the pvalue of Z when X = 3639 - 126 = 3513. So

X = 3765

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{3765 - 3639}{59.5}

Z = 2.12

Z = 2.12 has a pvalue of 0.983

X = 3513

Z = \frac{X - \mu}{s}

Z = \frac{3513 - 3639}{59.5}

Z = -2.12

Z = -2.12 has a pvalue of 0.017

0.983 - 0.017 = 0.966

96.6% probability that the mean of a sample would differ from the population mean by less than 126 miles

3 0
3 years ago
Is (-1,2) a solution of the system y&gt;x and x+y=&gt;
valentina_108 [34]
(-1,2) is a solution

y>x

2>-1 is correct

in this case yes

x+y≥x

 -1+2≥-1 

1≥-1 is correct: Yes

in this case no

x+y≥y

1≥2 

is not correct. No


8 0
3 years ago
Find the rate of change for the situation. You run 3 miles in one hour and 6 miles in two hours.
Alex787 [66]

Answer:

Both situations have the same rate of change

3 miles/hr

Step-by-step explanation:

situation 1

"3 miles in one hour" = 3 miles/hr

situation 2

"6 miles in two hours" = 6 miles / 2 hours =6/2 miles/hr = 3 miles./hr

Hence both are the same

4 0
3 years ago
5/6 divided by 1/2 simplified
balu736 [363]
You flip the second fraction and you multiply. 1 and 2/5 or 1.4
7 0
3 years ago
Read 2 more answers
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