Start with 3. Add 6. 3. 9, 15, __, ___, ___
2 answers:
You might be interested in
<u>Answer:</u>
Broker1 with $66.
Broker2 with $54.25
Broker4 with $50
Broker3 with $47.5
Broker5 with $33.5
<u>Explanation : </u>
Total number of shares Cindy have : 300
Market Price per share : $25
Total price for the shares : 300 $25
= $7500
Now ,
<u>Case 1: </u>
Commission provided by broker1 = 0.75%
Online fees provided by broker1 = $ 10
Total price provided by broker1=
=$66.25
<u>Case 2: </u>
Commission provided by broker2= 0.5%
Online fees provided by broker2=$17
Total price provided by broker2=
=$54.5
<u>Case 3: </u>
Commission provided by broker 3= 0.6% for 100 0r few
Not applicable because the total shares are 300
For over 100 shares
Commission provided= 0.5%
Online fees = $10
Total price =
=$47.5
<u>Case 4: </u>
For more than 100 shares
Online fees for buying and sharing= $50
Total price = $50
<u>Case5 : </u>
Commision for a share bought or sold = 0.05%
Online fees =$30
Total Price=
=$33.75
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 .