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sergejj [24]
2 years ago
15

Help plz i need a anwser

Mathematics
2 answers:
Blababa [14]2 years ago
8 0

Answer:

Your answer would be B: $25.20

24 x 5% is 1.2

$24 + 1.2 is 25.2

Step-by-step explanation:

Galina-37 [17]2 years ago
5 0

Answer:

the answer is B 25.20

Step-by-step explanation:

multiply 24 by 0.05 then add that to w4

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Bought to video games for a total of $55 their prices have a difference of $15
shepuryov [24]

Answer:

The answer is 40

Step-by-step explanation:

55-15=40

5 0
3 years ago
Part of the arena is being turned into a public darkroom. The floor needs covering in rubber tiles before work can begin on the
vladimir2022 [97]

The number of tiles used is 300 tiles.

According to the statement

We have given that:

The tiles are 20 cm by 30 cm. And the dark room floor is 6 meters by 3 meters.

And we have to find that the number of tiles used to prepare the dark room.

So, For this purpose we have to find the area of the room floor.

The area of the floor is 6 *3.

The area of the floor is 18 meter per square.

The area of the tile is 0.2*0.3

The area of the tile is 0.06 meter per square.

Now,

The number of tiles used is 18/0.06

The number of tiles used is 300.

So, The number of tiles used is 300 tiles.

Learn more about Area here brainly.com/question/10090807

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7 0
2 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
2 years ago
What is the slope of y = -4?
densk [106]

Answer:

-4 is the slope

Step-by-step explanation:

equation is y=mx + b

m = slope

b= y intercept

6 0
2 years ago
Read 2 more answers
At Sunday’s Best Ice Cream in New Orleans, the price of Ice Cream was $4.00 for a large sundae. Due to the holidays, they are de
dimulka [17.4K]

the answer is $3.88

Step-by-step explanation:

because the ice cream was $4.00 and they subtracted it by 12% which would be $4.00 minus .12 which would give you $3.88

6 0
2 years ago
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