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LekaFEV [45]
3 years ago
13

A university dean is interested in determining the proportion of students who receive some sort of financial aid. Rather than ex

amine the records for all students, the dean randomly selects 200 students and finds that 118 of them are receiving financial aid. Use a 99% confidence interval to estimate the true proportion of students on financial aid, with limits rounded to four decimal places.
Mathematics
1 answer:
schepotkina [342]3 years ago
6 0

Answer:

Step-by-step explanation:

Mean = np

Where

n = number of students

p = probability of success

n = 200

p = 118/200 = 0.59

mean = 200 × 0.59 = 118

Standard deviation, s = √npq

q = 1 - p = 1 - 0.59

q = 0.41

s = √(200 × 0.59 × 0.41)

s = √48.38 = 6.956

For a confidence level of 99%, the corresponding z value is 2.58. This is determined from the normal distribution table.

We will apply the formula

Confidence interval

= mean ± z ×standard deviation/√n

It becomes

118 ± 2.58 × 6.956/√200

= 118 ± 2.58 × 0.492

= 118 ± 1.2694

The lower end of the confidence interval is 118 - 1.2694 = 116.7306

The upper end of the confidence interval is 118 + 1.2694 = 119.2694

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8 0
3 years ago
Let n1equals50​, Upper X 1equals30​, n2equals50​, and Upper X 2equals10. Complete parts​ (a) and​ (b) below. a. At the 0.05 leve
Viefleur [7K]

Answer:

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

z=\frac{0.6-0.2}{\sqrt{0.4(1-0.4)(\frac{1}{50}+\frac{1}{50})}}=4.082    

p_v =2*P(Z>4.082)=4.46x10^{-5}  

So the p value is a very low value and using any significance level for example \alpha=0.05 always p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion 1 is significantly different from proportion 2.

Step-by-step explanation:

1) Data given and notation  

X_{1}=30 represent the number of people with a characteristic in 1

X_{2}=10 represent the number of people with a characteristic in 2

n_{1}=50 sample of 1 selected  

n_{2}=50 sample of 2 selected  

p_{1}=\frac{30}{50}=0.6 represent the proportion of people with a characteristic in 1

p_{2}=\frac{10}{50}=0.2 represent the proportion of people with a characteristic in 2

z would represent the statistic (variable of interest)  

p_v represent the value for the test (variable of interest)  

2) Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the proportion 1 is different from proportion 2 , the system of hypothesis would be:  

Null hypothesis:p_{1} = p_{2}  

Alternative hypothesis:p_{1} \neq p_{2}  

We need to apply a z test to compare proportions, and the statistic is given by:  

z=\frac{p_{1}-p_{2}}{\sqrt{\hat p (1-\hat p)(\frac{1}{n_{1}}+\frac{1}{n_{2}})}}   (1)  

Where \hat p=\frac{X_{1}+X_{2}}{n_{1}+n_{2}}=\frac{30+10}{50+50}=0.4  

3) Calculate the statistic  

Replacing in formula (1) the values obtained we got this:  

z=\frac{0.6-0.2}{\sqrt{0.4(1-0.4)(\frac{1}{50}+\frac{1}{50})}}=4.082    

4) Statistical decision

For this case we don't have a significance level provided \alpha, but we can calculate the p value for this test.    

Since is a two sided test the p value would be:  

p_v =2*P(Z>4.082)=4.46x10^{-5}  

So the p value is a very low value and using any significance level for example \alpha=0.05 always p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion 1 is significantly different from proportion 2.  

3 0
3 years ago
Plz help.
zvonat [6]
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A)  a said solve for p so we will solve for p in the equation.

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-215     -215  

c - 215 = 5p Now divide both sides by 5.

p = c/5 - 43  

B)  If c is the total cost  of hosting a birthday party then we will input 300 into the equation for c and solve for p.

300 = 5p + 215    First subtract 215 from both sides

-215             -215

 85 = 5p      Divide both sides by 5

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This means  17 people can attend the meeting if Allies parents are willing to spend $300.

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Hope helps!-Aparri

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