(Minimum of 2 Pages Written)This week you will begin working on Phase 4 of your course project. For Phase 4 of your course project, you will want to review your instructor's feedback from your Phase 1, Phase 2, and Phase 3 submissions to make any necessary corrections. Remember if you have questions about the feedback to ask your instructor for assistance.Once you have made your corrections, you will compile your information from Phase 1, Phase 2, Phase 3 and your final conclusion into one submission and submit this as your rough draft for Phase 4 of the course project. Below is a summary of the expectations for Phase 4 of the course project:Introduce your scenario and data set.Provide a brief overview of the scenario you are given above and the data set that you will be analyzing.Classify the variables in your data set.Which variables are quantitative/qualitative?Which variables are discrete/continuous?Describe the level of measurement for each variable included in your data set.Discuss the importance of the Measures of Center and the Measures of Variation.What are the measures of center and why are they important?What are the measures of variation and why are they important?Calculate the measures of center and measures of variation. Interpret your results in context of the selected topic.MeanMedianModeMidrangeRangeVarianceStandard DeviantionDiscuss the importance of constructing confidence intervals for the population mean.What are confidence intervals?What is a point estimate?What is the best point estimate for the population mean? Explain.Why do we need confidence intervals?Based on your selected topic, evaluate the following:Find the best point estimate of the population mean.Construct a 95% confidence interval for the population mean. Assume that your data is normally distributed and σ is unknown.Please show your work for the construction of this confidence interval and be sure to use the Equation Editor to format your equations.Write a statement that correctly interprets the confidence interval in context of your selected topic.Based on your selected topic, evaluate the following:Find the best point estimate of the population mean.Construct a 99% confidence interval for the population mean. Assume that your data is normally distributed and σ is unknown.Please show your work for the construction of this confidence interval and be sure to use the Equation Editor to format your equations.Write a statement that correctly interprets the confidence interval in context of your selected topic.Compare and contrast your findings for the 95% and 99% confidence interval.Did you notice any changes in your interval estimate? Explain.What conclusion(s) can be drawn about your interval estimates when the confidence level is increased? Explain.Discuss the process for hypothesis testing.Discuss the 8 steps of hypothesis testing?When performing the 8 steps for hypothesis testing, which method do you prefer; P-Value method or Critical Value method? Why?Perform the hypothesis test.If you selected Option 1:Original Claim: The average salary for all jobs in Minnesota is less than $65,000.Test the claim using α = 0.05 and assume your data is normally distributed and σ is unknown.If you selected Option 2: Original Claim: The average age of all patients admitted to the hospital with infectious diseases is less than 65 years of age.Test the claim using α = 0.05 and assume your data is normally distributed and σ is unknown.Based on your selected topic, answer the following:Write the null and alternative hypothesis symbolically and identify which hypothesis is the claim.Is the test two-tailed, left-tailed, or right-tailed? Explain.Which test statistic will you use for your hypothesis test; z-test or t-test? Explain.What is the value of the test-statistic? What is the P-value? What is the critical value?5.) What is your decision; reject the null or do not reject the null?Explain why you made your decision including the results for your p-value and the critical value.State the final conclusion in non-technical terms.ConclusionRecap your ideas by summarizing the information presented in context of your chosen scenario.Please be sure to show all of your work and use the Equation Editor to format your equations.This assignment should be formatted using APA guidelines and a minimum of 2 pages in length.

Learn by DoingMatched Pairs: In this lab you will learn how to conduct a matched pairs T-test for a population mean using StatCrunch. We will work with a data set that has historical importance in the development of the T-test.Paired T hypothesis test: μD = μ1 - μ2 : Mean of the difference between Regular seed and Kiln-dried seed H0 : μD = 0 HA : μD > 0 Hypothesis test results: Difference Mean Std. Err. DF T-Stat P-value Regular seed - Kiln-dried seed -33.727273 19.951346 10 -1.6904761 0.9391 Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer.Here are the directions, grading rubric, and definition of high-quality feedback for the Learn by Doing discussion board exercises.A list of StatCrunch directions is provided at the bottom of this page.ContextGosset's Seed Plot DataWilliam S. Gosset was employed by the Guinness brewing company of Dublin. Sample sizes available for experimentation in brewing were necessarily small. At that time, Gosset contacted a famous statistician Karl Pearson (1857-1936) and was told that there were no techniques for developing probability models for small data sets. Gosset studied under Pearson, and the outcome of his study was perhaps the most famous paper in statistical literature, "The Probable Error of a Mean" (1908), which introduced the T-distribution.Since Gosset was employed by Guinness, any work he produced would be owned by Guinness, so he published under a pseudonym, "Student"; hence, the T-distribution is often referred to as Student's T-distribution.To illustrate his analysis, Gosset used the results of seeding 11 different plots of land with two different types of seed: regular and kiln-dried. He wanted to determine if drying seeds before planting increased plant yield. Since different plots of soil may be naturally more fertile, this confounding variable was eliminated by using the matched pairs design and planting both types of seed in all 11 plots.The resulting data (corn yield in pounds per acre) are as follows. Plot Regular seed Kiln-dried Seed 1 1903 2009 2 1935 1915 3 1910 2011 4 2496 2463 5 2108 2180 6 1961 1925 7 2060 2122 8 1444 1482 9 1612 1542 10 1316 1443 11 1511 1535 We use these data to test the hypothesis that kiln-dried seed yields more corn than regular seed.Because of the nature of the experimental design (matched pairs), we are testing the difference in yield. Plot Regular seed Kiln-dried Seed Difference 1 1903 2009 –106 2 1935 1915 20 3 1910 2011 –101 4 2496 2463 33 5 2108 2180 –72 6 1961 1925 36 7 2060 2122 –62 8 1444 1482 –38 9 1612 1542 70 10 1316 1443 –127 11 1511 1535 –24 Note that the differences were calculated: regular − kiln-dried.VariablesRegular seed: regular seeds that were traditionally used for planting kiln-dried: seed that were kiln-dried before plantingDataDownload the seed (Links to an external site.) data file, and then upload the file into StatCrunch.PromptState the hypotheses and define the parameter.Checking conditions: Since Gosset invented the T-distribution, we will assume that his sample meets the conditions and proceed with the T-test. Regardless, answer these questions to demonstrate your understanding of the conditions for use of the T-model. But first you will need to review the dotplots for the data (opens in a new tab). Which graph is used to check conditions? Why?What do we look for in the graph to verify that conditions are met?What else do we need to know about the sample of seeds before using the T-test? Use StatCrunch to find the T-score and the P-value. Hint: as you work through the StatCrunch directions, keep in mind that we want to calculate the differences as regular − kiln-dried . So you will choose Regular seed for Sample 1 and kiln-dried seed for Sample 2. (directions) Copy and paste the information in the StatCrunch output window into your initial post.State a conclusion based on the context of this scenario.EXAMPLE TO RIGHT ANSWER1. Ho: μ=0Ha: μ>0The average difference is -33.732. a) We use the graph of the differences because that is what we are analyzing.b) We look to see if the graph is normally distributed, not skewed, and doesn't have outliers.c) We don't know if the data is randomly selected.3.Paired T hypothesis test: μD = μ1 - μ2 : Mean of the difference between Regular seed and Kiln-dried seed H0 : μD = 0 HA : μD > 0 Hypothesis test results: Difference Mean Std. Err. DF T-Stat P-value Regular seed - Kiln-dried seed -33.727273 19.951346 10 -1.6904761 0.9391 Differences stored in column, Differences.4. Based on the P-value of 0.9391, we do not have enough evidence to reject the null hypothesis. There is no statistically significant evidence to show that kiln-dried seeds yield more than regular seeds.