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aalyn [17]
3 years ago
6

Pencils come in packages of 10 . Erasers come in package of 12 . Phillip wants to purchase the smallest number of pencils and er

asers so that he will have exactly 1 eraser per pencil . How many packages of pencils and erasers should Phillip buy ?
Mathematics
1 answer:
Maslowich3 years ago
6 0

Answer: 60

Step-by-step explanation:

From the question, we are informed that pencils come in packages of 10 while erasers come in package of 12 .

We are further told that Phillip wants to purchase the smallest number of pencils and erasers so that he will have exactly 1 eraser per pencil, this simply means that we have to calculate the lowest common multiple for 10 and 12.

Multiples of 10 = 10, 20, 30, 40, 50, 60,

Multiples of 12 = 12, 24, 36, 48, 60, 72

Therefore, the packages of pencils and erasers that Phillip should buy will be 60

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scoundrel [369]

Answer:

The equations represent circles that result in the same graph.

Step-by-step explanation:

we have

-10x^{2}-10y^{2}=-300

Divide by -10 both sides

x^{2}+y^{2}=30 -----> equation A

This is the equation of a circle centered at origin with radius r=\sqrt{30} \ units

and

5x^{2}+5y^{2}=150

Divide by 5 both sides

x^{2}+y^{2}=30 -----> equation B

This is the equation of a circle centered at origin with radius r=\sqrt{30} \ units

equation A and equation B are equal

therefore

The system has infinite solutions, because the equations represent circles that result in the same graph.

4 0
3 years ago
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 .

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Andreas93 [3]

Answer:

(-4, 3)

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Citrus2011 [14]
If you need clarification just reply back so I can help

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