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adelina 88 [10]
3 years ago
6

Can you help me with all these I want to know if they're right!!!!!!!!!!!!!!!!?????????????????

Mathematics
1 answer:
Natali5045456 [20]3 years ago
7 0

Answer:

they are right and your smart don't second guess yourself

Step-by-step explanation:

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Find each measurement indicated.
nekit [7.7K]

Answer:

D) 24

explanation:

Sana makatulong

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3 years ago
it is known that the population proton of utha residnet that are members of the church of jesus christ 0l6 suppose a random samp
Lady_Fox [76]

Answer:

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

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 z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes 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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

Proportion of 0.6

This means that p = 0.6

Sample of 46

This means that n = 46

Mean and standard deviation:

\mu = p = 0.6

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.6*0.4}{46}} = 0.0722

Probability of obtaining a sample proportion less than 0.5.

p-value of Z when X = 0.5. So

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

By the Central Limit Theorem

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

Z = \frac{0.5 - 0.6}{0.0722}

Z = -1.38

Z = -1.38 has a p-value of 0.0838

0.0838 = 8.38% probability of obtaining a sample proportion less than 0.5.

8 0
3 years ago
Please answer this now in two minutes
postnew [5]

Answer:

8

Step-by-step explanation:

1 2 3 4 5 6 7 8 quick math

6 0
3 years ago
Can someone help me with this problem
balandron [24]

Hi! Your answer should be, 1,960.89

Hope this helps you!

3 0
3 years ago
12 is what percentige of 48
Bas_tet [7]

Answer:

25%

Step-by-step explanation:

100% = 48

1% = 48 ÷ 100 = 0.48

12 ÷ 0.48 = 25%

8 0
3 years ago
Read 2 more answers
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