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Vera_Pavlovna [14]
3 years ago
14

Using a tape measure, Melanie found that the circumference of the great

Mathematics
2 answers:
polet [3.4K]3 years ago
6 0

Circumference is pi x diameter so we have to divide 600 by pi to get the actual diameter. 600÷3.14=191cm, so her estimate was a little too small

Ludmilka [50]3 years ago
3 0

Answer:

Step-by-step explanation:

A. Little too large

Because

C= (Pi)*d

600=(pi)*200

So the answer is the A.

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There are no lines of symmetry on the us flag,in one red rectangle

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Two statistics teachers both believe that each has the smarter class. To put this to the test, they give the same final exam to
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Answer:

We conclude that there is no difference between the two classes.

Step-by-step explanation:

We are given that two statistics teachers both believe that each has a smarter class.

A summary of the class sizes, class means, and standard deviations is given below:n1 = 47, x-bar1 = 84.4, s1 = 18n2 = 50, x-bar2 = 82.9, s2 = 17

Let \mu_1 = mean age of student cars.

 \mu_2 = mean age of faculty cars.

So, Null Hypothesis, H_0 : \mu_1=\mu_2      {means that there is no difference in the two classes}  

Alternate Hypothesis, H_A : \mu_1\neq \mu_2      {means that there is a difference in the two classes}

The test statistics that will be used here is <u>Two-sample t-test statistics</u> because we don't know about the population standard deviations;

                         T.S.  =  \frac{(\bar X_1-\bar X_2)-(\mu_1-\mu_2)}{s_p \times \sqrt{\frac{1}{n_1}+\frac{1}{n_2} } }   ~  t_n_1_+_n_2_-_2

where, \bar X_1 = sample mean age of student cars = 8 years

\bar X_2  = sample mean age of faculty cars = 5.3 years  

s_1 = sample standard deviation of student cars = 3.6 years  

s_2 = sample standard deviation of student cars = 3.7 years  

n_1 = sample of student cars = 110  

n_2 = sample of faculty cars = 75  

Also, s_p=\sqrt{\frac{(n_1-1)\times s_1^{2}+(n_2-1)\times s_2^{2} }{n_1+n_2-2} }  = \sqrt{\frac{(47-1)\times 18^{2}+(50-1)\times 17^{2} }{47+50-2} }  = 17.491

So, <u><em>the test statistics</em></u> =  \frac{(84.4-82.9)-(0)}{17.491 \times \sqrt{\frac{1}{47}+\frac{1}{50} } }  ~  t_9_5

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The value of t-test statistics is 0.422.

<u>Now, the P-value of the test statistics is given by;</u>

P-value = P(t_9_5 > 0.422) = From the t table it is clear that the P-value will lie somewhere between 40% and 30%.

Since the P-value of our test statistics is way more than the level of significance of 0.04, so <u><em>we have insufficient evidence to reject our null hypothesis</em></u> as our test statistics will not fall in the rejection region.

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