_In a large clinical trial, 394,521 children were randomly assigned to two groups. The treatment group consisted of 198,315 children given a vaccine for a certain disease, and 40 of those children developed the disease. The other 196,206 children were given a placebo, and 138 of those children developed the disease. Consider the vaccine treatment group to be the first sample. Complete parts (a) through (d) below.__a. Assume that a 0.10 significance level will be used to test the claim that $ p_1 < p_2 $. Which is better: A hypothesis test or a confidence interval?_\[ \boxed{\text{(Select one of the options)}} \] is better._b. In general, when dealing with inferences for two population proportions, which two of the following are equivalent: confidence interval method, P-value method, critical value method?_\[ \boxed{\text{(Select two methods)}} \] are equivalent in that they will always lead to the same conclusion. Both of these methods use a standard deviation based on \[ \boxed{\text{(Select one: Combined sample proportion, Weighted average)}} \] whereas the other method uses a standard deviation based on \[ \boxed{\text{(Select one: Combined sample proportion, Weighted average)}} \] _c. If a 0.10 significance level is to be used to test the claim that $ p_1 < p_2 $, what confidence level should be used?_\[ \boxed{\text{(Type an integer or a decimal)}} \% \]_d. If the claim in part (c) is tested using this sample data, we get this confidence interval - $ 0.000589 < p_1 - p_2 < -0.000415 $. What does this confidence interval suggest about the claim?_Because the confidence interval \[ \boxed{\text{contains/does not contain}} \] zero, there \[ \boxed{\text{(is/is not)}} \] a significant difference between the two proportions. Because the confidence interval consists \[ \boxed{\text{(entirely of negative values/entirely of positive values)}} \], it appears that the first proportion is \[ \boxed{\text{(less than/greater than/equal to)}} \] the second proportion. There is \[ \boxed{\text{(sufficient/

In a large clinical trial, 394,521 children were randomly assigned to two groups. The treatment group consisted of 198,315 children given a vaccine for a certain diseas and 40 of those children developed the disease. The other 196,206 children were given a placebo, and 138 of those children developed the disease. Consider the vaccine treatment group to be the first sample. Complete parts (a) through (d) below. a. Assume that a 0.10 significance level will be used to test the claim that p,

In a large clinical trial, 394,521 children were randomly assigned to two groups. The treatment group consisted of 198,315 children given a vaccine for a certain diseas and 40 of those children developed the disease. The other 196,206 children were given a placebo, and 138 of those children developed the disease. Consider the vaccine treatment group to be the first sample. Complete parts (a) through (d) below. a. Assume that a 0.10 significance level will be used to test the claim that p,

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

Estimation

A new framework of data analysis where the new statistical methods are used for interpreting the results and analyzing the data is known as estimation in statistics.

Question

_In a large clinical trial, 394,521 children were randomly assigned to two groups. The treatment group consisted of 198,315 children given a vaccine for a certain disease, and 40 of those children developed the disease. The other 196,206 children were given a placebo, and 138 of those children developed the disease. Consider the vaccine treatment group to be the first sample. Complete parts (a) through (d) below._

_a. Assume that a 0.10 significance level will be used to test the claim that $ p_1 < p_2 $. Which is better: A hypothesis test or a confidence interval?_

\[ \boxed{\text{(Select one of the options)}} \] is better.

_b. In general, when dealing with inferences for two population proportions, which two of the following are equivalent: confidence interval method, P-value method, critical value method?_

\[ \boxed{\text{(Select two methods)}} \] are equivalent in that they will always lead to the same conclusion. Both of these methods use a standard deviation based on \[ \boxed{\text{(Select one: Combined sample proportion, Weighted average)}} \] whereas the other method uses a standard deviation based on \[ \boxed{\text{(Select one: Combined sample proportion, Weighted average)}} \]

_c. If a 0.10 significance level is to be used to test the claim that $ p_1 < p_2 $, what confidence level should be used?_

\[ \boxed{\text{(Type an integer or a decimal)}} \% \]

_d. If the claim in part (c) is tested using this sample data, we get this confidence interval - $ 0.000589 < p_1 - p_2 < -0.000415 $. What does this confidence interval suggest about the claim?_

Because the confidence interval \[ \boxed{\text{contains/does not contain}} \] zero, there \[ \boxed{\text{(is/is not)}} \] a significant difference between the two proportions. Because the confidence interval consists \[ \boxed{\text{(entirely of negative values/entirely of positive values)}} \], it appears that the first proportion is \[ \boxed{\text{(less than/greater than/equal to)}} \] the second proportion. There is \[ \boxed{\text{(sufficient/

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