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Crank
2 years ago
5

Question 1

Mathematics
1 answer:
nevsk [136]2 years ago
5 0

Answer:  " n = - 4 " .
<u>__________</u>

<u>Step-by-step explanation</u>:

<u>Given</u>:
 -n + 8  = 12 ;  solve for "n" ;

Subtract "8" from each side of the equation:

-n + 8 - 8 = 12 - 8 ;

to get:
 -n = 4 ;

Which is the same as:
 -1n = 4 ;

Divide each side of the equation by "-1" ; to isolate "n" on one side of the equation; and to solve for "n" :

  -1n / -1 = 4 / -1 ;

 to get:
    " n = - 4 " ;  which is our answer.
_______________

Now, let's check our answer:
_______________
→
by plugging in our value obtained for "n" ; which is " - 4 " ;
_______________
-(-4)  +  8 ≟  12 ?? ;
_______________

From the "left-hand sign" of the equation:
_______________
 " - (-4) = ⁺ 4 " ;  
_______________
<u>Note</u>:  The opposite of negative value; or the negative of a negative value; is equal to that very positive value.
_______________
⇒ " 4  +  8  ≟  12 ? ;

⇒ " 12  ≟  12 ? ;   Yes!

_______________
The correct answer is:  " n = - 4 " .
_______________

Hope this helps!  Best wishes!
_______________

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Answer:

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Step-by-step explanation:

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6 0
2 years ago
El agua de una psicina alcanza 250 cm de altura. Si la estatura de pablo es 1520 mm dentro de la piscina sin que el agua lo cubr
Andrews [41]

Respuesta:

Pablo se cubrirá de agua si se para en la piscina

Explicación paso a paso:

El nivel del agua en la piscina = 250cm.

Altura de Pablo = 1520 mm

Para saber si pablo podría pararse en la piscina sin estar cubierto de agua, necesitamos determinar la altura de Pablo en centímetros.

Convertir la altura de Pablo de milímetro a centímetro;

1 mm hasta 0,1 cm

1520 mm = (1520 * 0,1) = 152 cm

Por lo tanto, pablo mide 152 cm.

Esto significa que la altura del agua en la piscina es mayor que la altura de Pablo y esto lo cubrirá el agua si se para en la piscina.

6 0
2 years ago
A food distributor is being sued for racial discrimination because 12% of newly hired candidates are not white when 53% of all a
Musya8 [376]

Answer:

Check Explanation

Step-by-step explanation:

A) The null hypothesis would be that the proportion of newly hired candidates that are not white is not significantly different from the proportion of the applicants that are not white & there is no significant evidence that the company's hiring practices are discriminatory.

Mathematically,

H₀: μ₀ = 0.53

And the alternative hypothesis would be that there is a significant difference between the proportion of newly hired candidates that are not white is not significantly different from the proportion of the applicants that are not white. More specifically, that the proportion of newly hired candidates that are not white is significantly less than the proportion of applicants that are not white & there is significant evidence that the company's hiring practices are indeed discriminatory.

Mathematically,

Hₐ: μ₀ < 0.53

B) The two errors that can come up in this hypothesis testing include -

Type I error: We reject the null hypothesis because we obtain that the proportion of newly hired candidates that are not white is significantly less than the proportion of applicants that are not white and conclude that there is indeed significant evidence that the company's hiring practices are discriminatory when in reality, there is no significant difference and hence, no discrimination.

Type II error: We accept the null hypothesis (fail to reject the null hypothesis) because we obtained that there is no significant difference between the proportion of newly hired candidates that are not white & th proportion of applicants that are not white and conclude that there is no discrimination in the company's hiring practices when in reality, there is significant difference in the stated proportions above and significant evidence that there is indeed significant evidence that the company's hiring practices are discriminatory.

C) The power of the test increases as the significance level reduces. This is because t-statistic increases as significance level reduces.

D) The standard error of the mean used in computing the t-score is given as

σₓ = (σ/√n)

It is evident that as the value of n increases, the standard error reduces and this widens the effect of the test, hence, the power of the test increases.

Hope this Helps!!!

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Answer:

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