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stellarik [79]
3 years ago
5

Ramon wants to make an acute triangle with three pieces of wood. So far, he has cut wood lengths of 7 inches and 3 inches. He st

ill needs to cut the longest side. What length must the longest side be in order for the triangle to be acute?
a) exactly inches

b) greater than inches but less than 10 inches

c) less than inches but greater than 7 inches

d) not enough information given
Mathematics
2 answers:
Alex787 [66]3 years ago
8 0

Answer:

Option c - less than \sqrt{58} inches but greater than 7 inches.

Step-by-step explanation:

Given : Ramon wants to make an acute triangle with three pieces of wood. So far, he has cut wood lengths of 7 inches and 3 inches.

To find :  What length must the longest side be in order for the triangle to be acute?  

Solution :

According to property of triangle,

If the square of larger side of triangle is equating to the sum of square of smaller side

If a^2 the triangle is acute triangle  

where, a is the larger side and b,c are the smaller side

According to question, Let a=a , b=7, c=3

a^2

a^2

a

Means to be a acute triangle third side must be less than \sqrt{58} inches but greater than 7 inches.

Therefore, Option c is correct.

Yuki888 [10]3 years ago
5 0

Answer: c

Step-by-step explanation:

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Step-by-step explanation:

P = 2 (L + W)

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P = 2(8x + 10)

P = 16x + 20

If x= 3

P = 16(3) + 20

P = 48 + 20

P = 68 inches

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Step-by-step explanation:

55 berries     1700 berries

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1 jar                   x jars

Using cross products

55x = 1700*1

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Verify that (a+b)+c = a+ (b+c) by taking a = -8 , b = (-8/11) , c = (-8/12)
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Step-by-step explanation:

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Two major automobile manufacturers have produced compact cars with engines of the same size. We are interested in determining wh
Molodets [167]

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.

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3 years ago
A farmers field is 32 feet on each side. How many square feet does she have to plow?
11111nata11111 [884]

Answer:

1024 sq. ft.

Step-by-step explanation:

Each side is 32 feet long, so you would have to multiply 32 by 32, assuming all the sides are the same length.

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