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il63 [147K]
3 years ago
7

Why does the margin of error increase as the level of confidence​ increases? Choose the correct answer below. A. The margin of e

rror increases as the level of confidence increases because of the law of large numbers. B. The margin of error increases as the level of confidence increases​ because, as the level of confidence​ increases, the sample size n decreases. C. The margin of error increases as the level of confidence increases because the smaller the expected proportion of intervals that will contain the​ parameter, the larger the margin of error. D. The margin of error increases as the level of confidence increases because the larger the expected proportion of intervals that will contain the​ parameter, the larger th
Mathematics
1 answer:
Debora [2.8K]3 years ago
3 0

Answer:

The margin of error increases as the level of confidence increases because the larger the expected proportion of intervals that will contain the​ parameter, the larger the margin error.

Step-by-step explanation:

Margin of Error is a statistical measure of random sampling error insurvey results.

Level of confidence reflects percentage range around sample mean, that can be expected to contain population actual parameter.

High level of confidence means larger range band of confidence interval, supposed to contain the population parameter. This further implies  high expected variation between sample statistic & actual parameter i.e Margin Error increases.

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How do you solve and graph -82 is less than or equal to 9x OR -1 is less than or equal to -28
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05.06)Which of the following best describes interval C on the graph shown?
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3 years ago
A manufacturer of a new medication on the market for Alzheimer's disease makes a claim that the medication is effective in 65% o
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Answer:

z=\frac{0.639 -0.65}{\sqrt{\frac{0.65(1-0.65)}{180}}}=-0.309  

p_v =P(z  

So the p value obtained was a very high value and using the significance level given \alpha=0.05 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of adults with the medication was effective is not significantly less than 0.65

Step-by-step explanation:

Data given and notation

n=180 represent the random sample taken

X=115 represent the adults with the medication was effective

\hat p=\frac{115}{180}=0.639 estimated proportion of adults with the medication was effective

p_o=0.65 is the value that we want to test

\alpha=0.05 represent the significance level

Confidence=95% or 0.95

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that true proportion is less than 0.65.:  

Null hypothesis:p \geq 0.65  

Alternative hypothesis:p < 0.65  

When we conduct a proportion test we need to use the z statisitc, and the is given by:  

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

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.639 -0.65}{\sqrt{\frac{0.65(1-0.65)}{180}}}=-0.309  

Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The significance level provided \alpha=0.05. The next step would be calculate the p value for this test.  

Since is a left tailed test the p value would be:  

p_v =P(z  

So the p value obtained was a very high value and using the significance level given \alpha=0.05 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of adults with the medication was effective is not significantly less than 0.65

3 0
3 years ago
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