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Sindrei [870]
3 years ago
15

In the clrcle represented by the equation (x-4)2+ (y - 3)* = 25, the diameter is...

Mathematics
1 answer:
Free_Kalibri [48]3 years ago
7 0
24 just finished and you gotta solve it yourself to make sure it’s right
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Using the technique in the model above, find the missing sides in this 30° 600-90 right triangle.longShort 7Hypotenuse3.571314
dalvyx [7]
The answer to this is 14. To find the hypotenuse from the short do 2S, and for Short to Long it is S Root 3. 

Hope this helped! Please Mark as Brainliest!
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3 years ago
Look at the image and answer You ONLY GET POINTS FOR ANSWERING CORRECTLY ​
SSSSS [86.1K]

Answer:

the measure of xy is 9

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3 years ago
Which is the following is a source of income
almond37 [142]

Answer:

Investment is a source of Income.

<h3>OR</h3>

Self Employment Income

6 0
3 years ago
The average Act score follows a normal distribution, with a mean of 21.1 and a standard deviation of 5.1. What is the probabilit
ohaa [14]

Answer:

0.43% probability that the mean IQ score of 50 randomly selected people will be more than 23

Step-by-step explanation:

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

Normal probability distribution

Problems of normally distributed samples are solved using 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 = 21.1, \sigma = 5.1, n = 50, s = \frac{5.1}{\sqrt{50}} = 0.7212

What is the probability that the mean IQ score of 50 randomly selected people will be more than 23

This is 1 subtracted by the pvalue of Z when X = 23. So

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

By the Central Limit Theorem

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

Z = \frac{23 - 21.1}{0.7212}

Z = 2.63

Z = 2.63 has a pvalue of 0.9957

1 - 0.9957 = 0.0043

0.43% probability that the mean IQ score of 50 randomly selected people will be more than 23

5 0
3 years ago
1) A bag contains six red marbles and eight blue marbles. You randomly pick a marble and then pick a second marble without retur
Elena-2011 [213]

Answer:

You would have 4 red marbles and 8 blue marbles since you didn't return the ones you took out to the bag.

Step-by-step explanation:

6 - 2 = 4

The 8 would stay the same

There for you would have 4 red marbles and 8 blue marbles left in the bag. Totalled you have 12 marbles in the bag and 2 out of the bag. (8 + 4 = 12)

Including the marbles in and out of the bag you have 14 marbles. The 12 inside the bag + the 2 outside of the bag = 14 marbles totalled.

5 0
3 years ago
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