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3 years ago

Has endpoints q(4, 10) and s(–2, 3). find the coordinates of the midpoint of . (1, 6.5) (1, 13) (6.5, 3.5) (6.5, 1)

1 answer:

5 0

The midpoint is (1, 6.5)

The best way to find the midpoint of a line is by taking the average of its respective coordinates.

The average of the x coordinates 4 and -2 is 1 because when they are added together and divided by 2 you get 1.

Similarly for the y coordinates, which are 10 and 3. Added together they give an answer of 13 and when that is divided by 2 we get 6.5.

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a) The critical value on this case would be $t_{crit}=1.325$

b) The critical value on this case would be $t_{crit}=-1.345$

c) The critical values on this case would be $t_{crit}=\pm 2.201$

Step-by-step explanation:

Part a

The system of hypothesis on this case would be:

Null hypothesis: $\mu \leq \mu_0$

Alternative hypothesis: $\mu > \mu_0$

Where $\mu_0$ is the value that we want to test.

In order to find the critical value we need to find first the degrees of freedom, on this case that is given df=20. Since its an upper tailed test we need to find a value a such that:

$P(t_{20}>a) = 0.1$

And we can use excel in order to find this value with this function: "=T.INV(0.9,20)". The 0.9 is because we have 0.9 of the area on the left tail and 0.1 on the right.

The critical value on this case would be $t_{crit}=1.325$

Part b

The system of hypothesis on this case would be:

Null hypothesis: $\mu \geq \mu_0$

Alternative hypothesis: $\mu < \mu_0$

Where $\mu_0$ is the value that we want to test.

In order to find the critical value we need to find first the degrees of freedom, given by:

$df=n-1=15-1=14$

Since its an lower tailed test we need to find b value a such that:

$P(t_{14}$

And we can use excel in order to find this value with this function: "=T.INV(0.1,14)". The 0.1 is because we have 0.1 of the area accumulated on the left of the distribution.

The critical value on this case would be $t_{crit}=-1.345$

Part c

The system of hypothesis on this case would be:

Null hypothesis: $\mu = \mu_0$