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viva [34]
3 years ago
14

What is 7/16 simplified

Mathematics
2 answers:
Georgia [21]3 years ago
7 0
You cant simplify it . it is already simplified 
Airida [17]3 years ago
6 0
You cannot simplify it further because it is already in its simplest form

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please help me answer this question Solve: y − x = 12 y + x = -26 (19, -7). (-7, 1). (7, 19). (-19, -7).
Tpy6a [65]

Answer:

(-19 , -7)

Step-by-step explanation:

y - x = 12

y + x = -25 we sum them to get

2y = -14 , y = -7

then we put -7 instead of y in any of the equations:

-7 - x = 12

-x = 19

x = -19,

finally (x , y) is (-19 , -7)

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3 years ago
Lots of point n brainliest SO help rq
nordsb [41]

Answer:

  • A. $6000

Step-by-step explanation:

Let the invested amount is x.

<u>Then the interest amount is:</u>

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Correct choice is A

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3 years ago
Concerns about the climate change and CO2 reduction have initiated the commercial production of blends of biodiesel (e.g. from r
natta225 [31]

Answer:

a) 99% of the sample means will fall between 0.933 and 0.941.

b) By the Central Limit Theorem, approximately normal, with mean 0.937 and standard deviation 0.0015.

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 normal distributions can be 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.

(a) If the true mean is 0.9370 with a standard deviation of 0.0090 within what interval will 99% of the sample means fail?

Samples of 34 means that n = 34

We have that \mu = 0.937, \sigma = 0.009

By the Central Limit Theorem, s = \frac{0.009}{\sqrt{34}} = 0.0015

Within what interval will 99% of the sample means fail?

Between the (100-99)/2 = 0.5th percentile and the (100+99)/2 = 99.5th percentile.

0.5th percentile:

X when Z has a pvalue of 0.005. So X when Z = -2.575.

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

By the Central Limit Theorem

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

-2.575 = \frac{X - 0.937}{0.0015}

X - 0.937 = -2.575*0.0015

X = 0.933

99.5th percentile:

X when Z has a pvalue of 0.995. So X when Z = 2.575.

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

2.575 = \frac{X - 0.937}{0.0015}

X - 0.937 = 2.575*0.0015

X = 0.941

99% of the sample means will fall between 0.933 and 0.941.

(b) If the true mean 0.9370 with a standard deviation of 0.0090, what is the sampling distribution of ¯X?

By the Central Limit Theorem, approximately normal, with mean 0.937 and standard deviation 0.0015.

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Assuming the function is x^2
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(-3,2); m = 4 write an equation of the line that passes through the given point and has the given slope
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2=4(-3) + b
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