Dean took out a 10-year loan for $40,000 at an APR of 4% compounded monthly. What will his balance be after he has made exactly
2 answers:
Answer:
The balance be after he has made exactly half of his monthly payments is $56881.4.
Step-by-step explanation:
Given : Dean took out a 10-year loan for $40,000 at an APR of 4% compounded monthly.
To find : What will his balance be after he has made exactly half of his monthly payments?
Solution :
Formula of monthly payment ,
Discount factor
Where, Amount = $40,000
Rate r= 4% compounded monthly
Time = 10 years
Now, put all the values we get,
Half of the monthly payment is $807.345
Payment for 10 years is
The balance is $96881.4-$40000=$56881.4
Therefore, The balance be after he has made exactly half of his monthly payments is $56881.4.
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12 will be opposite to 24. Then the number of the people are sitting at the table will be 24.
<h3>What is Algebra?</h3>The analysis of mathematical representations is algebra, and the handling of those symbols is logic.
The several people are sitting evenly spaced around a circular table and the positions are labelled 1, 2, 3 and so on.
The people at positions 3 and 15 are directly opposite each other.
Then the number of the people are sitting at the table will be
1 is opposite to 13
2 is opposite to 14
3 is opposite to 15
Similarly, 12 will be opposite to 24.
Then the number of the people are sitting at the table will be 24.
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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 .