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Archy [21]
3 years ago
5

Help me please?!?!??!?!!

Mathematics
1 answer:
Debora [2.8K]3 years ago
7 0

Answer:

It's D.

Step-by-step explanation:

Because, it equals to the equation written.

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Kevin is 4 times as old as Daniel and is also 6 years older than Daniel.<br> How old is Kevin?
tester [92]

Answer:

kevin = 8 - hope this helped

:)

Step-by-step explanation:

Kevin = 4d  Kevin is 4 times as old as Daniel

Kevin = d + 6  Kevin is 6 years older than Daniel

4d = d + 6 They both equal K, so they are equal

3d = 6 subtracts D from both sides

d=6/3 = 2

If Daniel is 2 then Kevin is 4x2=8

If Daniel is 2 then Kevin is 2+6 = 8

Kevin is 8

Daniel is 2

3 0
2 years ago
2(x+1.25)=3,5<br><br> Find x
Arte-miy333 [17]

Step-by-step explanation:

\tt{2(x+1.25)=3.5  } ⠀

\tt{ 2x+2.5=3.5 } ⠀

\tt{ 2x=3.5-2.5 } ⠀

\tt{2x=1  } ⠀

\tt{ x=\dfrac{1}{2}=0.5 } ⠀

7 0
3 years ago
A square based prism and a cylinder both have
Anna11 [10]

Answer:

Parameter of base = 70.88 inch (Approx.)

Step-by-step explanation:

Given:

Volume of cylinder = 3768 cubic inch

Height of Prism = 12 inch

Find;

Parameter of base

Computation:

Volume of cylinder = Volume of Prism

3768 = (L)(B)(H)

3768 = (L)(B)(12)

(L)(B) = 314

L = B

So.

L = 17.72 inch

B = 17.72 inch

Parameter of base = 2[l+b]

Parameter of base = 2[17.72 + 17.72]

Parameter of base = 70.88 inch (Approx.)

8 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 .

7 0
3 years ago
Bethany has a circular table that she needs to carry inside her house to paint. Her front door is a rectangle and has a width of
RoseWind [281]
I thought I knew this but nvm
4 0
3 years ago
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