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balandron [24]
3 years ago
10

Divide and simplify 28 yd 2 ft 6 in ÷ 6

Mathematics
1 answer:
LUCKY_DIMON [66]3 years ago
3 0

Answer:

   4 yd 2 ft 5 in

Step-by-step explanation:

One straightforward way to do this is to convert to inches and back:

  28 yd 2 ft 6 in = (28 yd)(36 in/yd) + (2 ft)(12 in/ft) + 6 in

  = 1008 in + 24 in + 6 in = 1038 in

Then your division problem looks like ...

  (1038 in)/6 = 173 in

Converting this back to yards, feet, and inches can proceed like this ...

  (173 in)/(36 in/yd) = 4 yd remainder 29 in . . . . . find the number of yards first

  = 4 yd + (29 in)/(12 in/ft) = 4 yd 2 ft 5 in . . . . . then find feet and inches

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densk [106]

Answer:

  25.968

Step-by-step explanation:

The Google calculator will reliably use PEMDAS to evaluate an expression.

 = (2.1 +30.36)×0.8

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6 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

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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
How can you tell that the data in the table is function or not?
stealth61 [152]

that is not a function, because there are two outputs for three. two inputs can have one output, but one input cant have two outputs.

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3 years ago
Please help me on this
laiz [17]

Answer:

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Step-by-step explanation:

Angles 3 and 7 are corresponding angles. When the lines defining the base of the corresponding angles are parallel (as in this case where a is parallel to b), then the angles are equal.

That's the heavy duty definition. It just means that corresponding angles in parallel lines are equal.

So if <3 = 34 degrees, then <7 = 34 degrees.

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3 years ago
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vfiekz [6]
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If you meant milliliter, that is also equivalent to a cm^3, of which there are one thousand in a liter.

1000ml=L or 1000cm^3=L
4 0
3 years ago
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