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Svetllana [295]
3 years ago
8

-7 x (4+8) = ?? Please a aswer?

Mathematics
2 answers:
attashe74 [19]3 years ago
6 0
First parentheses.
-7 × (4+8) =
-7 × (12) =

Then Multiply.
-7 × 12 = -84

Answer is -84.

- A good tip is to follow this rule :

PEMDAS

Parentheses, exponent, Multiplication, division, addition, subtraction.

Do it in that same order and you will get your answer.
Colt1911 [192]3 years ago
5 0
The answer would be -84.

Here are the steps I did.

1. Simplify 4 + 8 to 12 ( -7 * 12 )

2. Now lastly simplify and u get -84.
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Please any one help me ​
Ulleksa [173]

\qquad\qquad\huge\underline{{\sf Answer}}♨

Since it's a Trapezoid with its non - parallel sides equal to one another,

\qquad \sf  \dashrightarrow \:\angle A + \angle P = 180

[ By forming co - interior angle pair ]

\qquad \sf  \dashrightarrow \:\angle A +100 = 180

\qquad \sf  \dashrightarrow \:\angle A = 180 - 100

\qquad \sf  \dashrightarrow \:\angle A = 80

Now, similarly,

\qquad \sf  \dashrightarrow \:\angle A + \angle R = 180

\qquad \sf  \dashrightarrow \: \angle R + 80 = 180

\qquad \sf  \dashrightarrow \: \angle R  = 100

Similarly,

\qquad \sf  \dashrightarrow \angle K + \angle R = 180

\qquad \sf  \dashrightarrow \angle K + 100 = 180

\qquad \sf  \dashrightarrow \angle K  = 80

3 0
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
2 years ago
Ill mark brainist plss help
worty [1.4K]

Answer:

3.3 cm

Step-by-step explanation:

262/80 = 3.275 ≈ 3.3

3 0
3 years ago
Hector entered a 3-day bike race. He traveled 20t miles on the first day, 15(t+6) miles the second day, and 25(t-3) miles the th
madreJ [45]
20t +15t+90+25t-75=60t+15
60t+15/3=20t+5 as the average
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8 0
3 years ago
Read 2 more answers
HELP ASPAP!!!!! WILL MARK BRAINIEST standard deviation
Umnica [9.8K]

Answer:

The standard deviation of the given data is 11.34.

Step-by-step explanation:

We have to find the standard deviation for the given data;

Grade on     No. of students          

 test (X)        with that score (f)        X \times f       ( X - \bar X)^{2}        f \times ( X - \bar X)^{2}

     50                  1                       50      1073.218      1073.2176

     57                 2                       114      663.578      1327.1552

     60                 4                       240       518.018     2072.0704

     65                 3                       195       315.418      946.2528

     72                 3                       216        115.778       347.3328

     75                12                       900        60.218       722.6112

     77                10                       770        33.178       331.776

     81                 6                       486        3.098       18.5856

     83                 6                       498        0.058        0.3456

     88                9                       792        27.458      247.1184

     90                12                      1080        52.418      629.0112

     92                12                       1104        85.378     1024.5312

     95                 2                        190        149.818      299.6352

     99                 4                        396        263.738     1054.9504

    100          <u>       5   </u>                 <u>    500    </u>     297.218   <u>   1486.088     </u>

   Total             <u>      91       </u>                <u>    7531     </u>                       <u>    11580.68    </u>

Firstly, the mean of the above data is given by;

            Mean, \bar X  =  \frac{\sum X \times f}{\sum f}

                             =  \frac{7531}{91}  =  82.76

Now, the standard deviation of the data is given by;

          Standard deviation, S.D.  =  \sqrt{\frac{\sum f(X-\bar X)^{2} }{\sum f-1}}

                                                     =  \sqrt{\frac{11580.68}{91-1}}

                                                     =  11.34

Hence, the standard deviation of the given data is 11.34.

5 0
3 years ago
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