This is a two part paper. Course Project Part I Required ResourcesRead/review the following resources for this activity: Textbook: Chapter 8 Lesson Scenario/SummaryYou will complete a Course Project in this course that will span two weeks. The final project is due the Sunday of Week 7. The project is broken into two parts and it would be most effective to complete Part I in Week 6 and Part II in Week 7. In Week 6, Confidence Intervals will be explored and in Week 7 Hypothesis testing will be explored.A confidence interval is a defined range of values such that there is a specified probability that the value of a parameter lies within the interval.In Part I of this project, you will pick a topic, complete research and provide a write-up that includes calculations. Round all values to two decimal places when appropriate.DeliverablesChoose a Topic where you can gather at least 50 pieces of data. Examples of Topics The Golden Gate Warriors Points Per Game in 2016 (use the points scored in the first 50 games). High School Graduation Rates by State (use the graduation rates for all 50 states) Average Tuition Rates in the US (You have to find the tuition rates of 50 college/universities). The prices of a hotel room per night in a major city (You have to find the price of the same night of hotels in one city). Weights of 50 babies at birth. Write at least a 1-Page ReportOpen a Word Document Introduction--Provide a description of your topic and cite where you found your data. Sample Data—Include a 5x10 table including your 50 values in your report. You must provide ALL of your sample data. Problem Computations—For the topic you chose, you must answer the following: Determine the mean and standard deviation of your sample. Find the 80%, 95%, and 99% confidence intervals. Make sure to list the margin of error for the 80%, 95%, and 99% confidence interval. Create your own confidence interval (you cannot use 80%, 95%, and 99%) and make sure to show your work. Make sure to list the margin of error. Problem Analysis—Write a half-page reflection. What trend do you see takes place to the confidence interval as the confidence level rises? Explain mathematically why that takes place. Provide a sentence for each confidence interval created in part c) which explains what the confidence interval means in context of topic of your project. Explain how Part I of the project has helped you understand confidence intervals better? How did this project help you understand statistics better? Required SoftwareMicrosoft Office: Word and ExcelUse a personal copy or access the software at https://application.chamberlain.edu (Links to an external site.).GradingThis activity will be graded based on the Course Project grading rubric. You can view the rubric below.Course Project Rubric Criteria Ratings Pts Part I: Topic & Introduction 4.0 pts 3.0 ptsAbove Average Student picks appropriate topic and introduces data. No citation. 2.0 ptsAverage. Student does not pick a topic that is appropriate for the project, introduces the data but does not cite source. 1.0 ptsNeeds Improvement Students provides topic without descritption and citation. 0.0 ptsNo Effort. No topic, descritpion or citation is provided. 4.0 pts Part I: Sample Data 4.0 ptsProficient Student provides ALL 50 pieces of data. 3.0 ptsAbove Average Student provides 30-49 pieces of data. 2.0 ptsAverage Student provides 20 - 29 pieces of data. 1.0 ptsNeeds Improvement Student provides 1-19 pieces of data. 0.0 ptsNo Effort. No Data was provided. 4.0 pts Part I: Mean & Standard Deviation 5.0 ptsProficient Mean & Sample Standard Deviation of the data set is correct with no rounding error. . 4.0 ptsAbove Average Mean & Sample Standard Deviation of the data set is correct but with roujnding error. 3.0 ptsAverage One Value (either mean or sample standsrd deviation) is correct but the other is not correct. 1.0 ptsNeeds Improvement Both the Mean & Sample Standard Deviation are incorrect but it was attempted. 0.0 ptsNo Effort. The mean and sample standard deviation 5.0 pts Part I: Constructing the 80%, 95%, 99% Confidence Intervals 15.0 ptsProficient Computes the 80%, 95%, and 99% confidence intervals correclty making sure to note the margin of error for each. 12.0 ptsAbove Average Computes the 80%, 95%, and 99% confidence intervals correclty but is missing margin of errors (or some of the margin of errors are incorrect). 10.0 ptsAverage Computes the 80%, 95%, and 99% confidence intervals but there are some errors in the calculations. 6.0 ptsNeeds Improvement Computes the 80%, 95%, and 99% confidence intervals but all of the values are incorrect. The component was attempted. 0.0 ptsNo Effort. No Confidence Intervals are provided. 15.0 pts Part I: Creating a new confidence interval 7.0 ptsProficient. Student computes a confidence interval (not 80%, 95%, 99%) correctly making sure to list the margin of error. 5.0 ptsAbove Average. Student computes a confidence interval (not 80%, 95%, 99%) correctly making sure to list the margin of error but there is rounding error. 4.0 ptsAverage. Student computes a confidence interval (not 80%, 95%, 99%) correctly but does not highlight the margin of error. 3.0 ptsNeeds Improvement Student computes a confidence interval (not 80%, 95%, 99%) but it was not done correctly. 0.0 ptsNo Effort. The student did not create a new confidence interval. 7.0 pts Part I: Problem Analysis 10.0 ptsProficient. Student addresses trend that takes place when the confidence level rises. Provides a sentence for each confidence interval created explaining what the confidence interval means in context of the data collected. Provides a reflection for Part I of the project. 8.0 ptsAbove Average. Student addresses trend that takes place when the confidence level rises. Provides sentences for each confidence interval created explaining what the confience interval means in context of the data collected. Does NOT provide a Reflection. 7.0 ptsAverage. Student may or may not address the trend that takes place when the confidence level rises. Provides a sentence for SOME confidence intervaSl created explaining what the confidence interval means in context of the data collected. A reflection Part I of the project may or may not be provided. 5.0 ptsNeeds Improvement. Majority of the analysis is missing. 0.0 ptsNo Effort. No Problem Anaylsis is provided. 10.0 pts Part II: Choose a Data Set & Preliminary Data 5.0 ptsProficient. Student computes all 4 Preliminary Data Values. 4.0 ptsAbove Average. Student computes all 3 Preliminary Data Values. 3.0 ptsAverage. Student computes all 2 Preliminary Data Values. 1.0 ptsNeeds Improvement. Student computes all 1 Preliminary Data Values. 0.0 ptsNo Effort. No Preliminary Data 5.0 pts Part II: Hypothesis Testing 20.0 ptsProficient. Completes 4 Hypothesis Tests highlighting the null/alternate hypothesis, value of test statistic, and report p-value. 16.0 ptsAbove Average. Completes 3 Hypothesis Tests highlighting the null/alternate hypothesis, value of test statistic, and report p-value. 14.0 ptsAverage. Completes 2 Hypothesis Tests highlighting the null/alternate hypothesis, value of test statistic, and report p-value. 10.0 ptsNeeds Improvement: Completes 1 Hypothesis Test highlighting the null/alternate hypothesis, value of test statistic, and report p-value. 0.0 ptsNo Effort. No Hypothesis Tests were completed. 20.0 pts Part II: Hypothesis Testing Analysis 10.0 ptsProficient. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for ALL 4 Problems. 8.0 ptsAbove Average. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 3 Problems. 7.0 ptsAverage. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 2 Problems. 5.0 ptsNeeds Improvement. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 1 Problem 0.0 ptsNo Effort. No conclusion/explanations were given. 10.0 pts Part II: Proposal and computations for new hypothesis test 10.0 ptsProficient. Student creates an original Hypothesis Test based on one of the data sets highlighting the null/alternate hypothesis, value of test statistic, report p-value, conclusion and explanation. 8.0 ptsProficient. Student creates an original Hypothesis Test based on one of the data sets correclty and has MOST of the content: highlighting the null/alternate hypothesis, value of test statistic, report p-value, conclusion and explanation. 7.0 ptsAverage. Student creates an original Hypothesis Test based on one of the data sets and MISSING MOST of the content: highlighting the null/alternate hypothesis, value of test statistic, report p-value, conclusion and explanation. 5.0 ptsNeeds Improvement. Student creates an original Hypothesis Test based on one of the data sets but there are multiple mistakes and/or conclusions are not valid. 0.0 ptsNo Effort. The student did not propose/compute a new hypothesis test. 10.0 pts Total Points: 90.0

The goal of this assignment is to help you understand the logic underlying the estimation of RSE (Random Sampling Error) based on simulated computation (estimation) using height data. See Excel Sheet 1 on Excel contains 1620 people’s height data These 1620 people’s height are 54 sets of 30 samples – this means that sample size(n) is 30 and you have 54 of them. Therefore, in this assignment we make following assumptions: Height data of 1620 people (54 sets of samples containing 30 people’s height) are population (I know this actually is a set of sample, but we pretend that this is a population: N = 1620) 30 people’s height within each set of sample is a set of sample: therefore sample size is 30 (n n=30) and there are 54 sets of samples. Based on these assumptions, please compute: Population mean (mean of the 1620 people’s height) Sample mean (mean of the 30 people) – please choose a specific sample from 54 samples, and compute the sample mean based on 30 samples in that particular set.Population standard deviation based on 1620 people as population Sample standard deviation (population standard deviation estimated based on your own sample of 30 – so you need to compute the SD on 30 people’s height in your own sample that you chose) Create a sampling distribution of the mean based on these 54 sets of samples and compare the shape (characteristics) of the sampling distribution with population distribution of height that I provided (sheet 2 grouped frequency polygon) by following these steps: Then step 1 compute the mean of 30 people’s height for each of all the 54 sets of samples – so you need 54 sample means for 54 sets of sample step 2 create a group frequency distribution table based on the computed means (54) – this is a grouped frequency table for sampling distribution of the 54 means Compare the shape of frequency distributions between Population of Height (one I provided) and Sampling distribution of the means (54 sets of Means you created). For your reference I am providing the grouped frequency polygon representing the population distribution (the third sheet of the excel) and answer the following questions: What is the relation between population mean and the mean of the 54 means? – same or differentWhich of the two distributions (population distribution of 1620 height data vs sampling distribution of the 54 means) has a narrower distribution clustered around the population mean? to what extent, the observation of the above two (a and b) aspects of the sampling distribution lend support to the Central Limit Theorem? – this requires you read CLM and understand it. RSE as difference between your own sample mean and the mean of the sampling distribution of mean (average of the 54 sets of sample mean)RSE as Standard Error of the Mean which is the Standard Deviation computed based on sampling distribution of the mean – this means computing a SD based on 54 sample means. For this use the sampling distribution of the mean that you created in the above (you need to use population St Dev computation function in Excel – see below). RSE as Standard Error of the Mean approximated by population standard deviation (based on 1620 data) divided by the square root of n (n=30) RSE as Standard Error of the Mean approximated by sample standard deviation (based on your own sample of n=30) (use of n-1 in denominator – sample standard deviation in Excel – see below) divided by the square root of n (n=30)(This is a bonus point of 5 on top of 30) I assume that 6-3 and 6-4 are different even though they are supposed to be similar according to the lecture. Speculate on the reason why they are different.Based on what you have learned on the four different approaches of estimating RSE, they should be the same. But they are different in this one. Why? Hint: the nature of the sample (30 people’s height)? You can include any questions or comments based on this process. Your points is not entirely based on whether your answer is correct; it is mainly based on evidence of THINKING you put here. 6 ) Estimate the Random Sampling Error in the following four different ways based on your understanding of the definition of RSE we just covered in the class: In computing Means and SD, use excel’s computational functions: For mean (average) see: https://www.youtube.com/watch?v=5_OHS-18RbU\ For standard deviation see: https://www.youtube.com/watch?v=uZWQXQG37Zs There are STD. P (population where the denominator is n) and STD.S (sample where the denominator is n-1). Be careful to use appropriate one. You should, by now, know which one to use when. If you have question on this, please send me an email. In sum your assignment needs to address all these questions Population mean Sample mean Population standard deviation Sample standard deviation (population standard deviation estimated based on your own sample) RSE as difference between your sample mean and the mean of the sampling distribution of mean (average of the 54 sets of sample mean) RSE as Standard Error of the Mean which is Standard Deviation computed on the sampling distribution of the mean. RSE as Standard Error of the Mean approximated by population standard deviation divided by the square root of n (n=30) RSE as Standard Error of the Mean approximated by sample standard deviationofyour own sample) divided by the square root of n (n=30)(bonus points) consideration of why 6-3 and 6-4 are different. 5-aWhat is the relation between population mean and the mean of the 54 means? 5-b. Which of the two distributions (population vs sampling distribution of the means) has a narrower distribution clustered around the population mean? 5-c.To what extent, the observation of the above two (a and b) aspect of the sampling distribution lend support to the Central Limit Theorem?