Answer:27.272614
Step-by-step explanation: I did the working on paper for you
AB ← → is tangent to circle O at point A. If m∠AOB = 55°, what is m∠ABO ?
2 answers:
Answer:
<h3>Step-by-step explanation:
Given AB is a tangent to the circle O and touch the circle at point A.
We know that tangent is a line which touches the circle only at one point .
We know that the radius of circle is perpendicular to the tangent.
In the figure OA is radius of given circle
AB is a tangent line
Radius OA is perpendicular to the tangent AB.
Therefore,
We know that sum of angles of a triangle is .
By sum of angle of triangle property
Therefore,in triangle OAB
OAB+
ABO+
AOB=
By angle sum of triangle property
90+55+
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Answer:
A. 7 in.
Step-by-step explanation:
We have been given that the perimeter of a rectangle is 16 inches. The equation that represents the perimeter of the rectangle is , where l represents the length of the rectangle and w represents the width of the rectangle.
We know that perimeter of rectangle is 2 times the sum of width and length of rectangle.
To be a rectangle length cannot be 8 as length and width of the rectangle is 8 inches.
Therefore, 7 inches the possible value for the length of the rectangle.
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
b) This value represent the effect into the ACT scores in the GPA, we know that:
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:
Alternative hypothesis:
Or in other wouds we want to check if an specific slope is significant.
The significance level assumed for this case is
Th degrees of freedom for a linear regression is given by , where p =3 the number of variables used to estimate the dependent variable.
In order to test the hypothesis the statistic is given by:
And replacing we got:
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
(b) Interpret from this model.
This value represent the effect into the ACT scores in the GPA, we know that:
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:
(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:
Alternative hypothesis:
Or in other wouds we want to check if an specific slope is significant.
The significance level assumed for this case is
Th degrees of freedom for a linear regression is given by , where p =3 the number of variables used to estimate the dependent variable.
In order to test the hypothesis the statistic is given by:
And replacing we got:
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 .
