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viktelen [127]
2 years ago
7

Find the zeros for 3x2-8=-2x

Mathematics
1 answer:
Monica [59]2 years ago
4 0

Answer:

Here is the answer ..hope it helps:)

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The area of a trapezoid field is 480 square m. The distance between two parallel sides is 15 m and one of the parallel sides is
Makovka662 [10]

Answer:

44m

Step-by-step explanation:

area  of a trapezoid = (a+b)* h/2

since the distance between two parallel sides is 15, that would be your height

plug everything in and you get:

480 = (20 + b) *15/2

b = 44

4 0
3 years ago
Given x=-3, y=6, and z=-4 xz/-2y
zimovet [89]

Answer:

-1

Step-by-step explanation:

sub in the values of x, y and z into the equation

you get:

(-3)(-4)/(-2)(6)

= 12/-12

= -1

8 0
3 years ago
Read 2 more answers
The population of Philadelphia in 1990 was 1,585,577. In 2010 the population was 1,526,006. What is the percent change the popul
UNO [17]

Answer:

-3.9% I.e there is decrease in the population

Step-by-step explanation:

Population @ 1990 = 1585577

Population @ 2010 = 1526006

% change =

(1526006-1585577)/1526006 × 100%

= -59571/1526006 ×100%

= -3.9%

7 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
Simplify using appropriate identity 0.85 × 0.85 +2 × 0.85 ×0.15 × 0.15
spayn [35]

The answer is <u><em>0.76075</em></u>!

<em>Hope this helps!</em>

7 0
3 years ago
Read 2 more answers
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