Alex believes the honor roll students at his school have an unfair advantage in being assigned to the science class they request
. He asked 500 students at his school the following questions: "Are you on the honor roll?" and "Did you get the science class you requested?" The results are shown in the table below:
Honor roll Not on honor roll Total
Received science class requested 64 315 379
Did not get science class requested 80 41 121
Total 144 356 500
Help Alex determine if all students at his school have an equal opportunity to get into the science class they requested. Show your work, and explain your process for determining the fairness of the class assignment process.
Honor roll Not on honor roll Total
Received science class requested 64 315 379
Did not get science class requested 80 41 121
Total 144 356 500
Help Alex determine if all students at his school have an equal opportunity to get into the science class they requested. Show your work, and explain your process for determining the fairness of the class assignment process.
2 answers:
Answer:
-The Honor Roll students would have a disadvantage to Non-Honor Roll students.
Step-by-step explanation:
-The first thing that needs to be done is to compare the probabilities of getting a class that is requested whether a student is in the Honor Roll or not.
P(received class requested; Honor Roll) is 64/144 = 0.444 or about 44%
P(received class requested; Not Honor Roll) is 315/356 = 0.884 or about 88%
-This shows us that students who <u>aren't </u>in Honor Roll have a higher chance of receiving the class requested than those who <u>are</u>.
(Btw I took the test)
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Answer:
(C) The slope of the regression equation is not significantly different from zero
Step-by-step explanation:
Let's suppose that we have the following linear model:
Where Y is the dependent variable and X the independent variable. represent the intercept and
the slope.
In order to estimate the coefficients we can use least squares estimation.
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 is our slope is significant.
In order to conduct this test we are assuming the following conditions:
a) We have linear relationship between Y and X
b) We have the same probability distribution for the variable Y with the same deviation for each value of the independent variable
c) We assume that the Y values are independent and the distribution of Y is normal
The significance level is provided and on this case is
The standard error for the slope is given by this formula:
Th degrees of freedom for a linear regression is given by since we need to estimate the value for the slope and the intercept.
In order to test the hypothesis the statistic is given by:
The confidence interval for the slope would be given by this formula:
And using the last formula we got that the confidence interval for the slope coefficient is given by:
IF we analyze the confidence interval contains the value 0. So we can conclude that we don't have a significant effect of the slope on this case at 5% of significance. And the best option would be:
(C) The slope of the regression equation is not significantly different from zero
we know that
The measure of the interior angle is the half-sum of the arcs comprising it and its opposite.
so
<u>Find the measure of the angle LAM</u>
m∠LAM is equal to
<u>Find the measure of the angle MAJ</u>
we know that
m∠LAM+m∠MAJ=° ------> by supplementary angles
m∠MAJ=
m∠MAJ=°
therefore
<u>the answer is</u>
The measure of the angle MAJ is