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Naily [24]
2 years ago
15

select the correct answer from each drop-down menu. How are confidence intervals affected by interval size? When creating a conf

idence interval, higher confidence corresponds to a smaller or larger interval, and lower confidence corresponds to larger or smaller interval. ​
Mathematics
1 answer:
11111nata11111 [884]2 years ago
6 0
<h3>Answer:</h3>

When creating a confidence interval, higher confidence corresponds to a <u>   larger   </u> interval, and lower confidence corresponds to a <u>   smaller   </u> interval.

==============================================

Explanation:

Imagine you are going fishing for an elusive sea creature of some kind. Casting a very wide net means we are more confident in catching the creature, in comparison to using a smaller net.

The fishing net is analogous to the width of the confidence interval. The wider the confidence interval, the more confident that we're capturing the parameter we're trying to measure.

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If a = 10, then what is the value of 6a + 15?
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2x+7=16

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3 years ago
Historically, the proportion of people who trade in their old car to a car dealer when purchasing a new car is 48%. Over the pre
choli [55]

Answer:

z=\frac{0.4 -0.48}{\sqrt{\frac{0.48(1-0.48)}{115}}}=-1.717  

p_v =P(z  

So the p value obtained was a very low value and using the significance level given \alpha=0.1 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of people that have traded in their old car is lower than 0.48 or 48%.  

Step-by-step explanation:

Data given and notation

n=115 represent the random sample taken

X=46 represent the number of people that have traded in their old car.

\hat p=\frac{46}{115}=0.4 estimated proportion of people that have traded in their old car

p_o=0.48 is the value that we want to test

\alpha=0.1 represent the significance level

Confidence=90% or 0.9

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 the proportion is less than 0.48.:  

Null hypothesis:p\geq 0.48  

Alternative hypothesis:p < 0.48  

When we conduct a proportion test we need to use the z statistic, 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{0.4 -0.48}{\sqrt{\frac{0.48(1-0.48)}{115}}}=-1.717  

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=0.1. 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 low value and using the significance level given \alpha=0.1 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of people that have traded in their old car is lower than 0.48 or 48%.  

4 0
4 years ago
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