In this project, you will demonstrate your mastery of the following competency: Apply statistical techniques to address research problems Perform hypothesis testing to address an authentic problem Overview In this project, you will apply inference methods for means to test your hypotheses about the housing sales market for a region of the United States. You will use appropriate sampling and statistical methods. Scenario You have been hired by your regional real estate company to determine if your region’s housing prices and housing square footage are significantly different from those of the national market. The regional sales director has three questions that they want to see addressed in the report: Are housing prices in your regional market higher than the national market average? Is the square footage for homes in your region different than the average square footage for homes in the national market? For your region, what is the range of values for the 95% confidence interval of square footage for homes in your market? You are given a real estate data set that has houses listed for every county in the United States. In addition, you have been given national statistics and graphs that show the national averages for housing prices and square footage. Your job is to analyze the data, complete the statistical analyses, and provide a report to the regional sales director. You will do so by completing the Project Two Template located in the What to Submit area below. Directions Introduction Purpose: What was the purpose of your analysis, and what is your approach? Define a random sample and two hypotheses (means) to analyze. Sample: Define your sample. Take a random sample of 100 observations for your region. Describe what is included in your sample (i.e., states, region, years or months). Questions and type of test: For your selected sample, define two hypothesis questions and the appropriate type of test hypothesis for each. Address the following for each hypothesis: Describe the population parameter for the variable you are analyzing. Describe your hypothesis in your own words. Describe the inference test you will use. Identify the test statistic. Level of confidence: Discuss how you will use estimation and conference intervals to help you solve the problem. 1-Tail Test Hypothesis: Define your hypothesis. Define the population parameter. Write null (Ho) and alternative (Ha) hypotheses. Specify your significance level. Data analysis: Analyze the data and confirm assumptions have not been violated to complete this hypothesis test. Summarize your sample data using appropriate graphical displays and summary statistics. Provide at least one histogram of your sample data. In a table, provide summary statistics including sample size, mean, median, and standard deviation. Summarize your sample data, describing the center, spread, and shape in comparison to the national information. Check the conditions. Determine if the normal condition has been met. Determine if there are any other conditions that you should check and whether they have been met. Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs. Calculate the hypothesis statistics. Determine the appropriate test statistic (t). Calculate the probability (p value). Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis. Relate the p value and significance level. Make the correct decision (reject or fail to reject). Provide a conclusion in the context of your hypothesis. 2-Tail Test Hypotheses: Define your hypothesis. Define the population parameter. Write null and alternative hypotheses. State your significance level. Data analysis: Analyze the data and confirm assumptions have not been violated to complete this hypothesis test. Summarize your sample data using appropriate graphical displays and summary statistics. Provide at least one histogram of your sample data. In a table, provide summary statistics including sample size, mean, median, and standard deviation. Summarize your sample data, describing the center, spread, and shape in comparison to the national information. Check the assumptions. Determine if the normal condition has been met. Determine if there are any other conditions that should be checked on and whether they have been met. Hypothesis test calculations: Complete hypothesis test calculations, providing the appropriate statistics and graphs. Calculate the hypothesis statistics. Determine the appropriate test statistic (t). Determine the probability (p value). Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis. Relate the p value and significance level. Make the correct decision (reject or fail to reject). Provide a conclusion in the context of your hypothesis. Comparison of the test results: See Question 3 from the Scenario section. Calculate a 95% confidence interval. Show or describe your method of calculation. Interpret a 95% confidence interval. Final Conclusions Summarize your findings: Refer back to the Introduction section above and summarize your findings of the sample you selected. Discuss: Discuss whether you were surprised by the findings. Why or why not? What to Submit To complete this project, you must submit the following: Project Two Template: Use this template to structure your report, and submit the finished version as a Word document. Supporting Materials The following resources may help support your work on the project: Data Set: House Listing Price by Region Use this data for input in your project report. Document: National Statistics and Graphs Use this data for input in your project report. Use these tutorials for support with the Excel functions you will use in the project: Tutorial: Random Sampling in Excel Tutorial: Scatterplots in Excel Tutorial: Descriptive Statistics in Excel Tutorial: Creating Histograms in Excel

 F97= 83,621,143,489,848,422,977 F98= 135,301,852,344,706,746,049 Given these two Fibonacci numbers, find F100.

CompetencyGiven a real-life application, develop a hypothesis test for a population parameter and its interpretation.InstructionsScenario (information repeated for deliverable 01, 03, and 04)A major client of your company is interested in the salary distributions of jobs in the state of Minnesota that range from $30,000 to $200,000 per year. As a Business Analyst, your boss asks you to research and analyze the salary distributions. You are given a spreadsheet that contains the following information:A listing of the jobs by titleThe salary (in dollars) for each jobIn prior engagements, you have already explained to your client about the basic statistics and discussed the importance of constructing confidence intervals for the population mean. Your client says that he remembers a little bit about hypothesis testing, but he is a little fuzzy. He asks you to give him the full explanation of all steps in a hypothesis testing and wants your conclusion about a claim that the average salary for all jobs in the state of Minnesota is less than $74,500 and a second claim that the average salary for all jobs in the state of Minnesota is greater than $70,500.Background information on the DataThe data set in the spreadsheet consists of 364 records that you will be analyzing from the Bureau of Labor Statistics. The data set contains a listing of several jobs titles with yearly salaries ranging from approximately $30,000 to $200,000 for the state of Minnesota.What to SubmitYour boss wants you to submit the spreadsheet with the completed calculations, answers, and analysis.Grading RubricFFCBA01234Not SubmittedNo PassCompetenceProficiencyMasteryNot SubmittedDid not correctly solve a majority of the problems or at least one problem left blank.Correctly solved a majority of the problems.Correctly solved almost all the problems.All problems are solved correctly.Not SubmittedVery few steps are provided to explain how to solve the problem OR the steps provided have several errors.Fairly complete and detailed steps are provided to explain how to solve the problem OR the steps provided have some errors.Mostly complete and detailed steps are provided to explain how to solve the problem.Complete and detailed steps are provided to explain how to solve the problem.Not SubmittedExplanations generally lack a basic understanding of the statistical concepts or lack of proper terminology.Explanations demonstrate a basic understanding of most of the statistical concepts and terminology, but some explanations may be incomplete or incorrect.Explanations demonstrate a proficient understanding of most of the statistical concepts and terminology, but with small errors.Explanations demonstrate a mastery of understanding of the statistical concepts and terminology.Not SubmittedThe majority of variables, equations, and expressions are not properly formatted.The majority of variables, equations, and expressions are properly formatted.Almost all variables, equations, and expressions are properly formatted.All variables, equations, and expressions are properly formatted.