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monitta
3 years ago
10

Companies whose stocks are listed in a stock exchange have their company name represented by either three, four, or five letters

(repetition of letters is allowed). What is the maximum number of companies that can be listed on the stock exchange?​
Mathematics
1 answer:
nlexa [21]3 years ago
5 0

Answer:

83330 Companies

Step-by-step explanation:

The answer is

26C3 + 26C4 + 26C5

= 2600 + 14950 + 65780

= 83330

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Step-by-step explanation:

divide the number on the y axis (i'm assuming it's inches of snow) by the number on the x axis (i'm assuming its hours)

by doing this you will get 3 inches per hour

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MariettaO [177]

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7.1

Step-by-step explanation:

If you count how many units are between the library and the park, it is seven units.

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2 years ago
Read 2 more answers
Suppose you are interested in the effect of skipping lectures (in days missed) on college grades. You also have ACT scores and h
DIA [1.3K]

Answer:

a) For this case the intercept of 2.52 represent a common effect of measure for any student without taking in count the other variables analyzed, and we know that if HSGPA=0, ACT= 0 and skip =0 we got colGPA=2.52

b) This value represent the effect into the ACT scores in the GPA, we know that:

\hat \beta_{ACT} = 0.015

So then for every unit increase in the ACT score we expect and increase of 0.015 in the GPA or the predicted variable

c) If we are interested in analyze if we have a significant relationship between the dependent and the independent variable we can use the following system of hypothesis:

Null Hypothesis: \beta_i = 0

Alternative hypothesis: \beta_i \neq 0

Or in other wouds we want to check if an specific slope is significant.

The significance level assumed for this case is \alpha=0.05

Th degrees of freedom for a linear regression is given by df=n-p-1 = 45-3-1 = 41, where p =3 the number of variables used to estimate the dependent variable.

In order to test the hypothesis the statistic is given by:

t=\frac{\hat \beta_i}{SE_{\beta_i}}

And replacing we got:

t = \frac{-0.5}{0.0001}=-5000

And for this case we see that if we find the p value for this case we will get a value very near to 0, so then we can conclude that this coefficient would be significant for the regression model .

Step-by-step explanation:

For this case we have the following multiple regression model calculated:

colGPA =2.52+0.38*HSGPA+0.015*ACT-0.5*skip

Part a

(a) Interpret the intercept in this model.

For this case the intercept of 2.52 represent a common effect of measure for any student without taking in count the other variables analyzed, and we know that if HSGPA=0, ACT= 0 and skip =0 we got colGPA=2.52

(b) Interpret \hat \beta_{ACT} from this model.

This value represent the effect into the ACT scores in the GPA, we know that:

\hat \beta_{ACT} = 0.015

So then for every unit increase in the ACT score we expect and increase of 0.015 in the GPA or the predicted variable

(c) What is the predicted college GPA for someone who scored a 25 on the ACT, had a 3.2 high school GPA and missed 4 lectures. Show your work.

For this case we can use the regression model and we got:

colGPA =2.52 +0.38*3.2 +0.015*25 - 0.5*4 = 26.751

(d) Is the estimate of skipping class statistically significant? How do you know? Is the estimate of skipping class economically significant? How do you know? (Hint: Suppose there are 45 lectures in a typical semester long class).

If we are interested in analyze if we have a significant relationship between the dependent and the independent variable we can use the following system of hypothesis:

Null Hypothesis: \beta_i = 0

Alternative hypothesis: \beta_i \neq 0

Or in other wouds we want to check if an specific slope is significant.

The significance level assumed for this case is \alpha=0.05

Th degrees of freedom for a linear regression is given by df=n-p-1 = 45-3-1 = 41, where p =3 the number of variables used to estimate the dependent variable.

In order to test the hypothesis the statistic is given by:

t=\frac{\hat \beta_i}{SE_{\beta_i}}

And replacing we got:

t = \frac{-0.5}{0.0001}=-5000

And for this case we see that if we find the p value for this case we will get a value very near to 0, so then we can conclude that this coefficient would be significant for the regression model .

7 0
3 years ago
(b) If the sum of two consecutive odd numbers is 48, find the numbers.​
Rudiy27

Answer:

23, 25

Step-by-step explanation:

let the first number be represented as A, since there are two odd numbers, the second number would be A + 2

A + A+2 = 48

2A + 2 = 48

2A = 48 - 2

2A = 46  ( divide both sides by 2)

A = 23

since we know the next number to be A + 2

= 23 + 2 = 25

the two numbers are 23 and 25

6 0
2 years ago
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Lostsunrise [7]

Answer:

Step-by-step explanation:

6 0
3 years ago
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