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lakkis [162]
2 years ago
9

URGENT 50 PTS

Mathematics
1 answer:
Len [333]2 years ago
6 0
Point c

explanation:
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You are given the following information: Stockholders' equity = $323 million; price/earnings ratio = 14; shares outstanding = 8,
vagabundo [1.1K]

Answer:

$282.59 per share

Step-by-step explanation:

Given that,

Stockholders' equity = $323 million

price/earnings ratio = 14

shares outstanding = 8,800,000

Market/book ratio =7.7

Book Value per share:

= Stockholders' equity ÷ shares outstanding

= $323,000,000 ÷ 8,800,000

= $36.70

Market price per share:

= Book Value per share × Market/book ratio

= $36.70 × 7.7

= $282.59 per share

3 0
3 years ago
A helicopter flies 240 miles in 2 hours 30 minutes.
shepuryov [24]
96 mph


step by step explanation:
240/2.5
8 0
2 years ago
Read 2 more answers
They are arranged randomly because manual typewriters tended to jam if the user typed too fast - therefore the arrangement was i
solmaris [256]

Answer:

Huh

Step-by-step explanation:

Huh......................

8 0
2 years ago
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What is the value of 452 tens?
Law Incorporation [45]
The anwser is 4,520. :D
6 0
3 years ago
Read 2 more answers
Consider the population regression of log earnings [Yᵢ, where Yᵢ= ln(Earningsᵢ)] against two binary variables:
puteri [66]

Answer:

A) allows the population effect on log earnings of being married to depend on gender

Step-by-step explanation:

The regression equation of a dependent variable based on two or more independent variables is of the form:

Y=b_{0}+b_{1}X_{1} +b_{2}X_{2}+b_{3}X_{1}X_{2}

Here,

<em>Y</em> = dependent variable

X_{1} and X_{2} = independent variables

X_{1}X_{2} = interaction term

b_{1},\ b_{2}\ and \ b_{3} = regression coefficients.

If there is a significant interaction effect present then this implies that the effect of one independent variable (X_{1} orX_{2} ) on the dependent variable (<em>Y</em>) differs every time with different value of the other independent variable  (X_{1} orX_{2} ) .

The provided regression equation is:

Y_{i}=\beta _{0}+\beta _{1}D_{1i}+\beta_{2}D_{2i}+\beta _{3}D_{1i}D_{2i}+u_{i}

Y_{i} = dependent variable

D_{1i} and D_{2i} = independent variables

In this case the interaction term is defined as follows:

The effect of being married on log earnings is dependent on different values of the variables D_{2i}, i.e. the gender of the i^{th}person.

Thus, the correct option is (A).

3 0
3 years ago
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