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USPshnik [31]
2 years ago
8

PLEASE HELP!! WILL REQARD A LOT

Mathematics
2 answers:
____ [38]2 years ago
7 0

Answer:

17,500 hits

Step-by-step explanation:

Soloha48 [4]2 years ago
3 0

9514 1404 393

Answer:

  17,500

Step-by-step explanation:

The problem can be written as a proportion:

  hits/revenue = 1000/(£2) = x/(£35)

Multiplying by £35 gives ...

  x = 1000(35/2) = 35000/2 = 17,500

17500 hits are required for revenue of £35.

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Mark thinks the equation y=6x+4 will match the red solid graph. Mia thinks it will match the blue dotted graph. Who’s right? Exp
Rudiy27

Answer:

Technically neither, but Mia is correct.

Step-by-step explanation:

Slope-Intercept Form: y = mx + b

Since our slope <em>m</em> is equal to 6, it is a positive number. That means that the slope/line will be positive, so the line should be going up, not down. That means the blue line would be correct. Therefore, Mia is correct.

Technicality:

Since the blue line is dotted, the equation should be a <em>inequality </em>and not a linear equation. No solutions on the line would technically work. If the equation was y < 6x + 4 or something with an inequality sign, then it would be correct.

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3 years ago
A box of pens contains only red pens and blue pens. The ratio of the number of red pens to the total number of pens in the box i
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The Director of Admissions at Kinzua University in Nova Scotia estimated the distribution of student admissions for the fall sem
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Answer:

Variance = 24900

Standard Deviation = 157.7973        

Step-by-step explanation:

We are given the following in the question:

Number of admissions:    1000     1200    1500

Admissions Probability:     0.6        0.3       0.1

Formula:

E(x) = \displaystyle\sum x_iP(x_i)\\E(x) = 1000(0.6) + 1200(0.3) + 1500(0.1)\\E(x) = 1110\\E(x^2) =  \displaystyle\sum x_i^2P(x_i)\\E(x^2) = (1000)^2(0.6) + (1200)^2(0.3) + (1500)^2(0.1)\\E(x^2) = 1257000

Variance =

\sigma^2 = E(x^2) - (E(x))^2\\\sigma^2 = 1257000 -(1110)^2\\\sigma^2 =24900

Thus, the variance is 24900.

Standard Deviation =

\sigma = \sqrt{\sigma^2} = \sqrt{24900} = 157.7973

Thus, the standard deviation is 157.7973

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