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White raven [17]
3 years ago
12

A pizza has a diameter of 16 inches.

Mathematics
2 answers:
neonofarm [45]3 years ago
5 0
Pixd = circumference...
3.14 x 16 = 50.2...
so your answer is C. 50.2 inches...
hope this helps!
olga55 [171]3 years ago
3 0

Answer:

Option C 50.2\ in

Step-by-step explanation:

we know that

The circumference of a circle is equal to

C=\pi D

where

D is the diameter of the circle

we have

D=16\ in

substitute

C=3.14*(16)=50.2\ in

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3 years ago
Bottles of a popular cola drink are supposed to contain 300 ml of cola. There is some variation from bottle to bottle because th
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Answer:

We conclude that the mean contents of cola bottles is more than or equal to the advertised 300 ml.

Step-by-step explanation:

We are given that Bottles of a popular cola drink are supposed to contain 300 ml of cola. The distribution of the contents is normal with standard deviation of 3 ml.

A student who suspects that the bottler is under-filling measures the contents of six bottles. The results are: 299.4, 297.7, 301.0, 298.9, 300.2, 297.0

<u><em>Let </em></u>\mu<u><em> = mean contents of cola bottles.</em></u>

SO, Null Hypothesis, H_0 : \mu \geq  300 ml   {means that the mean contents of cola bottles is more than or equal to the advertised 300 ml}

Alternate Hypothesis, H_A : \mu < 300 ml   {means that the mean contents of cola bottles is less than the advertised 300 ml}

The test statistics that will be used here is <u>One-sample z test statistics</u> as we know about the population standard deviation;

                       T.S.  = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n} } }  ~ N(0,1)

where, \bar X = sample mean contents of cola bottle = \frac{\sum X}{n} = 299.03 ml

            \sigma = population standard deviation = 3 ml

            n = sample of bottles = 6

So, <em><u>test statistics</u></em>  =  \frac{299.03-300}{\frac{3}{\sqrt{6} } }     

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Therefore, we conclude that the mean contents of cola bottles is more than or equal to the advertised 300 ml.

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=======================================================

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If we apply this transformation to every point on f(x), then it will flip the f(x) curve over the horizontal x axis.

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