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Levart [38]
3 years ago
10

I need help with this ​

Mathematics
2 answers:
valentina_108 [34]3 years ago
4 0
Hopes this helps:

Answer: E. 7/12

How I know I use this app called Cymath.
Step2247 [10]3 years ago
3 0
<h2>Answer:</h2>

\sf \sqrt{ \frac{7}{8} } \times  \sqrt{ \frac{7}{18} }

\sf \frac{ \sqrt{7} }{2 \sqrt{2} }  \times  \frac{ \sqrt{7} }{3 \sqrt{2} }

\sf\frac{ \sqrt{7 \times 7} }{3 \times 2 \sqrt{2 \times 2} }

\sf \frac{7}{6 \times 2}

\sf\frac{7}{12} .

\sf\:Correct\:choice = [E] \:7/12.

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The confidence interval for mean of the "before-after" differences is \fbox{(-0.4037,1.8037)}

Further explanation:

Find the difference between the before pain and the after pain.

Difference = before-after

Kindly refer to the Table for the difference of between the before and after pain.

Sum of difference = 5.6

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Sample standard deviation s = 1.3201

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Formula for confidence interval = \left( \bar{X} \pm t_{n-1, \frac{\alpha}{2}\%} \frac{s}{\sqrt{n}} \right)

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confidence interval = \left( 0.7 \pm t_{7, \frac{5}{2}\%} \frac{1.3201}{\sqrt{8}} \right)

From the t-table.

The value of t_{7, \frac{5}{2}\%=2.365

Confidence interval = ( 0.7 \pm 2.365}\times \frac{1.3201}{\sqrt{8}}) \right)

Confidence interval = \left( 0.7 - 2.365}\times \0.4667,0.7 + 2.365}\times \0.4667) \right

Confidence interval = (0.7-1.1037,0.7+1.1037)

Confidence interval = \fbox{(-0.4037,1.8037)}

The 95\% confidence interval tells us about that 95\% chances of the true mean or population mean lies in the interval.

Yes, the hypnotism appear to be effective in reducing pain as confidence interval include includes the positive deviation from the mean.

Learn More:

1. Learn more about equation of circle brainly.com/question/1506955

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Answer Details:

Grade: College Statistics

Subject: Mathematics

Chapter: Confidence Interval

Keywords:

Probability, Statistics, Speed dating, Females rating, Confidence interval, t-test, Level of significance , Normal distribution, Central Limit Theorem, t-table, Population mean, Sample mean, Standard deviation, Symmetric, Variance.

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