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4vir4ik [10]
3 years ago
6

The ends of a triangular prism are right triangles with a base of 12 inches and height of 9 inches. The height of the prism is 1

1 inches what is the surface area?
Mathematics
1 answer:
Ostrovityanka [42]3 years ago
8 0

Given:

The bases of triangular prism are right triangles with a base of 12 inches and height of 9 inches.

The height of the prism is 11 inches.

To find:

The surface area of the triangular prism.

Solution:

Using the Pythagoras theorem, the hypotenuse of the bases of the triangular prism is:

Hypotenuse^2=Base^2+Height^2

Hypotenuse^2=12^2+9^2

Hypotenuse^2=144+81

Hypotenuse^2=225

Taking square root on both sides.

Hypotenuse=15

The surface after of the triangular prism contains 3 rectangles of dimensions 12 inches by 11 inches, 9 inches by 11 inches, 15 inches by 11 inches and two triangles with base 12 inches and height 9 inches.

Area of the rectangle:

Area=Length \times Width

So, the area of three rectangles are:

A_1=12 \times 11

A_1=132

A_2=9 \times 11

A_2=99

A_3=15 \times 11

A_3=165

Area of a triangle is:

Area=\dfrac{1}{2}\times base \times height

So, the area of the triangles is:

A_4=\dfrac{1}{2}\times 12 \times 9

A_4=6 \times 9

A_4=54

And, the triangles have same dimensions so their areas are equal.

A_4=A_5=54

Now,

Area=A_1+A_2+A_3+A_4+A_5

Area=132+99+165+54+54

Area=504

Therefore, the surface area of the triangular prism is 504 sq. inches.

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Two major automobile manufacturers have produced compact cars with engines of the same size. We are interested in determining wh
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Answer:

(A) The mean for the differences is 2.0.

(B) The test statistic is 1.617.

(C) At 90% confidence the null hypothesis should not be rejected.

Step-by-step explanation:

We are given that a random sample of eight cars from each manufacturer is selected, and eight drivers are selected to drive each automobile for a specified distance.

The following data (in miles per gallon) show the results of the test;

Driver         Manufacturer A               Manufacturer B

   1                      32                                       28

  2                      27                                       22

  3                      26                                       27

  4                      26                                       24

  5                      25                                       24

  6                      29                                       25

  7                       31                                       28

  8                      25                                       27

Let \mu_1 = mean MPG for the fuel efficiency of Manufacturer A brand

\mu_2 = mean MPG for the fuel efficiency of Manufacturer B brand

SO, Null Hypothesis, H_0 : \mu_1-\mu_2=0  or  \mu_1= \mu_2    {means that there is a not any significant difference in the mean MPG (miles per gallon) when testing for the fuel efficiency of these two brands of automobiles}

Alternate Hypothesis, H_A : \mu_1-\mu_2\neq 0  or  \mu_1\neq  \mu_2   {means that there is a significant difference in the mean MPG (miles per gallon) for the fuel efficiency of these two brands of automobiles}

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

                      T.S.  = \frac{(\bar X_1-\bar X_2)-(\mu_1-\mu_2)}{s_p\sqrt{\frac{1}{n_1}+\frac{1}{n_2}  } }  ~ t__n__1+_n__2-2

where, \bar X_1 = sample mean MPG for manufacturer A = \frac{\sum X_A}{n_A} = 27.625

\bar X_2 = sample mean MPG for manufacturer B =\frac{\sum X_B}{n_B} = 25.625

s_1 = sample standard deviation for manufacturer A = \sqrt{\frac{\sum (X_A-\bar X_A)^{2} }{n_A-1} } = 2.72

s_2 = sample standard deviation manufacturer B = \sqrt{\frac{\sum (X_B-\bar X_B)^{2} }{n_B-1} } = 2.20

n_1 = sample of cars selected from manufacturer A = 8

n_2 = sample of cars selected from manufacturer B = 8

Also, s_p=\sqrt{\frac{(n_1-1)s_1^{2}+(n_2-1)s_2^{2}  }{n_1+n_2-2} }   =  \sqrt{\frac{(8-1)\times 2.72^{2}+(8-1)\times 2.20^{2}  }{8+8-2} }  = 2.474

(A) The mean for the differences is = 27.625 - 25.625 = 2

(B) <u><em>The test statistics</em></u>  =  \frac{(27.625-25.625)-(0)}{2.474 \times \sqrt{\frac{1}{8}+\frac{1}{8}  } }  ~  t_1_4

                                     =  1.617

(C) Now at 10% significance level, the t table gives critical values between -1.761 and 1.761 at 14 degree of freedom for two-tailed test. Since our test statistics lies within the range of critical values of t, so we have insufficient evidence to reject our null hypothesis as it will not fall in the rejection region due to which <u>we fail to reject our null hypothesis</u>.

Therefore, we conclude that there is a not any significant difference in the mean MPG (miles per gallon) when testing for the fuel efficiency of these two brands of automobiles.

5 0
4 years ago
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