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stiks02 [169]
3 years ago
7

Guysss i need helppppp.... please answer all of them and if u dont know please dont answer

Mathematics
2 answers:
lukranit [14]3 years ago
8 0

Answer:

This says middle school.. What grade are you in? I am in 8th grade and do not know any of that...

I have never seen work near that.........

kirza4 [7]3 years ago
5 0
I’m in 10th and i’ve never seen that.
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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.

6 0
3 years ago
A solid aluminum cube has sides each of length l . A second cube of the same material has sides four times the length of the fir
timofeeve [1]
The formula to find the volume of cube

cube = s^3

Therefore volume is equal to I^3

The second cube has 4x the First cube

4 × (I^3) = 4 ×I^3

Total volume of the second cube= 4I^3 cm3

Fact: the density(mass ÷ volume) of aluminium is 2.40g/cm3

Making mass the subject of the formula:

D = M ÷ V
(Times volume to remove deno minator)

Mass = Density × Volume

Mass = 2.40 × 4I ^3

Mass = 8.40I^3

By physics

weight= m × g

where
M = mass
g = acceleration due to gravity (= 9.8)

W = 8.40 I^3 × 9.8

Weight of aluminium = 82.32I^3
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Similarly,

P(A\mid B)=\dfrac{P(A\cap B)}{P(B)}=\dfrac{0.18}{0.3}=0.6

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The answer is 4.8 inches
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