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statuscvo [17]
3 years ago
5

A study was conducted to determine whether there were significant differences between medical students admitted through special

programs (such as retention incentive and guaranteed placement programs) and medical students admitted through the regular admissions criteria. It was found that the graduation rate was 91.3% for the medical students admitted through special programs. If 10 of the students from the special programs are randomly selected, find the probability that at least 9 of them graduated.
Mathematics
1 answer:
Mekhanik [1.2K]3 years ago
3 0

Answer:

P(X\geq 9)=P(X=9)+P(X=10)

And using the probability mass function we got:

P(X=9)=(10C9)(0.913)^9 (1-0.913)^{10-9}=0.383  

P(X=10)=(10C10)(0.913)^{10} (1-0.913)^{10-10}=0.402  

And replacing we got:

P(X \geq 9) = 0.383 +0.402= 0.785

Step-by-step explanation:

Let X the random variable of interest "number of  students graduated", on this case we now that:  

X \sim Binom(n=10, p=0.913)  

The probability mass function for the Binomial distribution is given as:  

P(X)=(nCx)(p)^x (1-p)^{n-x}  

Where (nCx) means combinatory and it's given by this formula:  

nCx=\frac{n!}{(n-x)! x!}  

We want to find the following probability:

P(X\geq 9)=P(X=9)+P(X=10)

And using the probability mass function we got:

P(X=9)=(10C9)(0.913)^9 (1-0.913)^{10-9}=0.383  

P(X=10)=(10C10)(0.913)^{10} (1-0.913)^{10-10}=0.402  

And replacing we got:

P(X \geq 9) = 0.383 +0.402= 0.785

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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
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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 colGPA=2.52

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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.

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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

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And replacing we got:

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7 0
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Nitella [24]

Answer:

1

Step-by-step explanation:

Solve. Remember to follow PEMDAS.

PEMDAS  is the order of operation, and =

Parenthesis

Exponent (& Roots)

Multiplication

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Addition

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54/(-6) = -9

Next, combine the terms.

10 + (-9) = 10 - 9 = 1

1 is your answer.

~

6 0
3 years ago
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