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Inessa05 [86]
4 years ago
8

Help please lol I’m confused

Mathematics
2 answers:
Lunna [17]4 years ago
7 0
70 x = this is unswer
emmainna [20.7K]4 years ago
4 0

Answer:

40 degrees = x

Step-by-step explanation:

As you can see in the picture, there are two lines that indicate that those two lines are equal. So, this triangle is an isosceles triangle, and the base angles of an isosceles triangle are equal. To identify the base angle, check the angles opposite to the side equal. So, we find that 70 is a base angle, so there are two 70 degrees  angles. So,

70 + 70 + x = 180 (The angle sum property of triangles)

=> 140 + x = 180

=> x = 180 - 140

=> x = 40

If this helped, please mark me as the brainliest!

Thank you!

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insens350 [35]

Answer:

A.  12.68 - 14.72 hours

B. Normal distribution.

Step-by-step explanation:

Part A

This question is using quantitative data. A 99% confidence interval means that you want to know the range where 99% of the population will be. To find this you have to convert the 99% CI into the z-score which is -2.58SD to + 2.58SD.  

Note that the standard deviation(SD) is from the sample, not the population. We still need to find the standard deviation of the population. The formula is:

population SD = \frac{o}{\sqrt[]{n} }

Where the o= sample SD = 7.4

n= number of sample = 463

The calculation will be:

population SD = \frac{o}{\sqrt[]{n} }

population SD = \frac{7.4}{\sqrt[]{463} }= 0.3951

The bottom limit will be:

Mean - SD * z-score= 13.7 - 0.3951*2.58 = 12.68 hours

The upper limit will be:

Mean + SD * z-score= 13.7 + 0.3951*2.58 =14.72 hours

The 99% CI range will be 12.68 - 14.72 hours

Part B

The table used to convert confidence interval into z-score depends on the distribution type of the data. Most data is classified as normal distributed, a data type that will concentrated at mean and spread equally from the mean. Normal distribution data will look like a bell which make it also called bell curve.  

The question tells you that the data is normal distribution, but that doesn't mean every data is normally distributed. There are a lot of other data distribution type so we have to do some tests to know the normality of the data in real-life data.

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Step-by-step explanation:

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