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Nastasia [14]
3 years ago
12

California has 143deaths from heart disease and 137deaths from cancer per100,000 residents. Which rate is more extreme compared

to other states? A.Perform any needed computations here: b. Is California's rate for heart disease or for cancer more extreme compared to the other states? Explain:
Mathematics
1 answer:
belka [17]3 years ago
3 0

Answer:

California's rate for heart disease is more extreme than Cancer

Step-by-step explanation:

Given

Represent Cancer with C and Heart Disease with H

H = 143

C = 137

Population = per 100,000

First we need to determine the probability of both.

For H

P(H) = H/100000

P(H) = 143/100000

P(H) = 0.00143

For C

P(C) = C/100000

P(C) = 137/100000

P(C) = 0.00137

By comparison,

0.00143 > 0.00137

So, California's rate for heart disease is more extreme than Cancer.

Reason: P(H) > P(C)

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Step-by-step explanation:

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3 years ago
] It is claimed that 42% of US college graduates had a mentor in college. For a sample of college graduates in Colorado, it was
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Answer:

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The p value for this case would be given by:

p_v =P(z>3.930)=0.0000443  

For this case the p value is lower than the significance level so then we have enough evidence to reject the null hypothesis so then we can conclude that the true proportion is significantly higher than 0.42

Step-by-step explanation:

Information given

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\hat p=\frac{502}{1045}=0.480 estimated proportion of college graduates with a mentor

p_o=0.42 is the value that we want to test

z would represent the statistic

p_v represent the p value

Hypothesis to test

We want to test if the true proportion is higher than 0.42, the system of hypothesis are.:  

Null hypothesis:p \leq 0.42  

Alternative hypothesis:p > 0.42  

The statistic is given by:

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

Replacing the info we got:

z=\frac{0.480 -0.42}{\sqrt{\frac{0.42(1-0.42)}{1045}}}=3.930  

The p value for this case would be given by:

p_v =P(z>3.930)=0.0000443  

For this case the p value is lower than the significance level so then we have enough evidence to reject the null hypothesis so then we can conclude that the true proportion is significantly higher than 0.42

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Step-by-step explanation: I hope this helps :)

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