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azamat
3 years ago
8

What is the square root of 88 plus(+) the square root of 95?

Mathematics
1 answer:
Tju [1.3M]3 years ago
5 0
Square root of 88 is 9.38083152
Square root of 95 is 9.746794345
9.38083152 + 9.746794345 = 19.12762586

You might be interested in
if a minute hand on a clock turns 1 degree every minute, how many minutes have passed when it's 1/8 of the way around the clock?
Lynna [10]
There's 60 min, so 1/8 of 60

60/8= 7.5 minutes in 1/8 of 60
4 0
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
What is the answer to this question?
Elena-2011 [213]
Where’s the question-
3 0
3 years ago
Evaluate a2 - 6 for a = 4 and b = 17
Natalija [7]

Answer:

The answer is -94 but where is b

Step-by-step explanation:

2(4)-6(17)=-94

7 0
2 years ago
Evaluate pq÷4; use p=14, and q=14​
Zolol [24]

Answer:

49

Step-by-step explanation:

14x14 = 196

196/4 = 49

4 0
3 years ago
Read 2 more answers
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