CompetencyIn this project, you will demonstrate your mastery of the following competency:Perform regression analysis to address an authentic problemScenarioYou are a data analyst for a basketball team and have access to a large set of historical data that you can use to analyze performance patterns. The coach of the team and your management have requested that you come up with regression models that predict the number of wins in a regular game based on the performance metrics that are included in the data set. These regression models will help make key decisions to improve the performance of the team. You will use the Python programming language to perform the statistical analyses and then prepare a report of your findings to present for the team’s management. Since the managers are not data analysts, you will need to interpret your findings and describe their practical implications.Note: This data set has been “cleaned” for the purposes of this assignment.ReferenceFiveThirtyEight. (April 26, 2019). FiveThirtyEight NBA Elo dataset. Kaggle. Retrieved from https://www.kaggle.com/fivethirtyeight/fivethirtye...DirectionsFor this project, you will submit the Python script you used to make your calculations and a summary report explaining your findings.Python Script: Python script complete! See attached pictures!Summary Report: Once you have completed all the steps in your Python script, you will create a summary report to present your findings. Use the provided template to create your report. You must complete each of the following sections:Introduction: Set the context for your scenario and the analyses you will be performing.Scatterplots and Correlation: Discuss relationships between variables using scatterplots and correlation coefficients.Simple Linear Regression: Create a simple linear regression model to predict the response variable.Multiple Regression: Create a multiple regression model to predict the response variable.Conclusion: Summarize your findings and explain their practical implications.What to SubmitTo complete this project, you must submit the following:Summary Report Zip File Word DocumentUse the provided template to create your summary report. The template contains guiding questions to help you complete each section. Be sure to remove these questions before submitting your report. Your summary report should be submitted as a 3- to 5-page Microsoft Word document. It should include an APA-style cover page and APA citations for any sources used. Use double spacing, 12-point Times New Roman font, and one-inch margins.Supporting MaterialsThe following resource(s) may help support your work on the project:Shapiro Library: APA Style GuideThis guide will help you format your cover page and references according to APA style. You are not required to use external resources for this project. However, if you do use any resources, you must cite them in APA format.

This project is about finding the best forecasting model for 6 known stocks. The first part is to find the 6 stocks that we need to build a model on. Second is to try to build an index that can be used for predicting the chosen stocks. Finally is to write a 5 pages report that explains the process that you did. I will upload the book of the class and the assignment description so that it can make more sense. You need to be an expert in the forecasting concepts and the use of Minitab Software to solve this problem.

Discussion Board # 5 Last DB DISCUSSION BOARD DUE: NOVEMBER 9, 2020 AT 2PM CENTRAL TIME.Overview: In module 2 we focused on using statistics to make assumptions about the entire population. What allowed us to make that connection was the:Central Limit Theorem - if you can't explain it in under 10 words you probably don't get it! So in this DB be sure you have it down before you move on. Submit: You may choose however you would like to submit your analysis- only request is that the work be converted to PDF, and you show your work. Failure to do so will result in loss of points. You are more than welcome to work all problems out by hand & feel free to add a catchy title for fun, also as a signal (data) to me that you know what you are doing. Data you will need: Class Survey Data (Can be found in Files link to left or Modules tab)Create a table - with column headers population, sample, & concepts. Then for each row put one important fact that you 'predict' will be on the exam & underneath each column heading (sample & population) give examples/symbols/etc. In the concepts column briefly explain 'why' you think it will be on the exam. Be sure to only include relevant examples, (Links to an external site.) therefore, there is no max or min on how many you need to include. As long as they are relevant (Links to an external site.)you are fine! This will "feel' strange because I'm ask you to use your critical thinking skills, which isn't hard but it is different. Do your best, I trust you but of course I'll be sure to give you copious amounts of feedback until you get it right. You can compare & contrast, analyze, etc. Only thing to avoid is copy & pasting definitions. Using class data create a 95% Confidence Interval on the average number of hours a student is taking at HCCDraw a normal distribution curve & mark the mean, upper limit & lower limitIs it possible to find someone on campus who is not w/in the upper & lower limits, if so, why would this happen & how often would it occur?Looking at your answer above in #4 is that a fact?Review the class data file - given an example when this would be the population, given an example when this would be a sample.Perform a statistical test -Do Men & Women take the same # of Hours? Include all 6 steps outlined by bookState Hypothesis StatementsSignificance Level - lets use 5% Determine test statistic - (depends on independence, are they normally distributed, etc-go back to your earlier analysis)Decision Rule -lets use 2 tail (this is much easier to learn at first)State your decision (did you use critical value & t statistic or P?Interpret the results - Is gender significant, why or why not (include diagram)Feedback post: 100% of your grade will be based on this. You must peer review 2 posts and provide constructive feedback on their work to receive full credit.)Word of caution: Most students will not link the concept of sampling to earlier chapters on bivariate data. Students will also confuse samples, with populations - best way to keep these straight is to understand that the terms are not permanent. It depends on context. Was survey we used a good sample? Are they independent, normally distributed, is standard deviation known (this will help you determine 'which' tests you can use).