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3 years ago

Jasmine can run 4 5/6 miles in 2/3 of an hour. how many miles can she run 1 hour simplify comepletly

Mathematics

1 answer:

Vikentia [17]3 years ago

7 0

Remark

the question depends on d= r * t

d = the distance in miles.

r = the rate of travel in miles per hour

t = the time in hours.

Step One

Rearrange the formula so you are solving for the rate.

d = r * t Divide by t

4 5/6 = (4*6 + 5)/6 = 29/6

r = d / t

Step Two

Substitute into the equation.

$r = \dfrac{\dfrac{29}{6}}{\dfrac{2}{3} }$

Step Three

Turn the bottom fraction upside down. Multiply these two together.

r = $\dfrac{29}{6} * \dfrac{3}{2}$

r = 29/4 miles hour.

Step Four

Solve for d when t = 1 hour.

d = ??

r = 29/4 miles / hour

t = 1 hour.

d = 29/4 * 1

d = 29/4 miles

That's as simple as you can get it unless you want 7 1/4 miles or 7.25 miles

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BaLLatris [955]

Answer:

The null hypothesis is $H_o : \mu_1 = \mu_2$

The alternative hypothesis $H_a : \mu_1 > \mu_2$

$p-value = 0.232$

The decision rule is

Fail to reject the null hypothesis

Step-by-step explanation:

From the question we are told that

The value given is

S/N

1 7 5

2 4 3

3 8 7

4 8 8

5 7 9

6 7 5

7 6 5

Generally the sample mean for the first sample is mathematically represented as

$\= x _1 = \frac{\sum x_i }{n}$

=> $\= x _1 = \frac{7 +4 + \cdots + 6}{7}$

=> $\= x _1 = 6.714$

Generally the sample mean for the second sample is mathematically represented as

$\= x _2 = \frac{\sum x_i }{n}$

=> $\= x _2 = \frac{5 + 3+ \cdots + 5}{7}$

=> $\= x _2 = 6$

Generally the sample standard deviation for the first sample is mathematically represented as

$s_1 = \sqrt{\frac{\sum (x_i - \= x_1)^2 }{n-1 } }$

=> $s_1 = \sqrt{\frac{ (7 - 6.714 )^2 +(4 - 6.714 )^2 + \cdots + (6 - 6.714 )^2 }{7-1 } }$

=> $s_1 = 1.905$

Generally the sample standard deviation for the second sample is mathematically represented as

$s_2 = \sqrt{\frac{\sum (x_i - \= x_2)^2 }{n-1 } }$

=> $s_2 = \sqrt{\frac{ (5 - 6.714 )^2 +(3 - 6.714 )^2 + \cdots + (5 - 6.714 )^2 }{7-1 } }$

=> $s_1 = 4.33$

Generally the pooled standard deviation is

$s = \sqrt{\frac{(n_1 - 1 )s_1^2 + (n_2 - 1 )s_2^2}{n_1 + n_2 -2 } }$

=> $s = \sqrt{\frac{(7 - 1 )1.905^2 + (7 - 1 )4.333^2}{7 + 7 -2 } }$

=> $s = 1.766$

The null hypothesis is $H_o : \mu_1 = \mu_2$

The alternative hypothesis $H_a : \mu_1 > \mu_2$

Generally the test statistics is mathematically represented as

$t = \frac{\= x _1 - \= x_2 }{s * \sqrt{\frac{1}{n_1} + \frac{1}{n_2}} }$

=> $t = \frac{6.714 - 6 }{1.766 * \sqrt{\frac{1}{7} + \frac{1}{7}} }$

=> $t = 0.757$

Generally the degree of freedom is mathematically represented as

$df = n_1 + n_2 - 2$

=> $df = 7 + 7 - 2$

=> $df = 12$

From the t distribution table the probability of $t = 0.757$ at a degree of freedom of $df = 12$ is

$t_{ 0.757 , 12} = 0.232$

Generally the p-value is

$p-value = t_{ 0.757 , 12} = 0.232$

From the values obtained we see that $p-value > \alpha$ hence

The decision rule is

Fail to reject the null hypothesis

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