Question 2:This question concerns approximations to the Normal Distribution.(i) Explain in your own words how the Poisson Approximation to the NormalDistribution arises and why this is important.(ii) It is known that in the Australian Population, 15% of people are over 180cmtall. Showing your working, what is my chance of having at least 11 people of over180cm tall with a sample size of 100.(iii). If I had a sample of at least 1000 people (from the Population in (ii)), wouldthat be enough to be 99.9% sure of obtaining at least 100 people over 180cm tall?Please explain your reasoning.

i)The central limit theorem's application leads to the Poisson approximation of the normal…

Answered: This question concerns approximations…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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In the year 2033, Sarai Patterson is a leading traveling nurse. Sarai is interested in reducing the mean recovery time for patients after experiencing a serious injury (assume recovery times are normally distributed). Suppose the mean recovery time is presently 8.6 months. Sarai takes a random sample of 46 patients that have experienced serious injury to participate in a new treatment program and finds the sample mean is 8.1 months and a sample standard deviation of 1.2 months. Using α = 0.05, answer the following questions. a) What is the setup for your null and alternative hypothesis? b) What is the value of the test statistic? c) What is/are the critical value(s)?
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You take a simple random sample of size 25 from a very large population in which the true proportioni p=0.1. Which statement below best describes what you know about the sampling distribution of p? (0.1)(0.9) (a) H,-0.1; o,- the distribution is skewed right. 25 (0.1)(0.9). 25 (b) H,=0.1; o,=. ; the distribution is skewed left. (0.1)(0.9). (c) ,=0.1; o,= the distribution is approximately Normal. %3D 25 (0.1)(0.9) (d) , the distribution is not approximately Normal. 25 =0.1; we cannot use the formula o, (0.1)(0.9) ; the distribution is approximately Normal. 25 (e) =0.1; we cannot use the formula o,
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