Attached was the midterm project now i need the final project done 

Requirements:

• No more than 2 to 3 pages
• Present the findings using the skillset acquired (topics covered) in class.
• Also include the dataset with the analysis (could be excel or any statistical package). You should provide details of the analysis in an Appendix.

How are the 40 points given: 10 for each Module you choose to apply. (For example, you choose regression to test an association or predict an outcome, you get 10 points for that analysis)

Data Analytics is a subject that can be best appreciated only when applied to a dataset you are familiar with. The aim of this project is to achieve that. Do not view this project as a hurdle in the course, rather a bridge to connect the topics you learnt to your work or subject domain. There are five main modules in this course:

• Module 1 : Normal Distribution (Percentile, distribution of means, and chance of occurrence if we assume normal distribution)
• Module 2 : Confidence Interval Estimation (Including Sample Size determination)
• Module 3 : Inferences from data (Hypothesis testing, i.e., confirming or checking if a claim made about the data. In this module, we dealt with only one sample)
• Module 4 : More Inferences from data (Multiple samples)
• Module 5 : Regression analysis (Both simple and multiple, apart from basic ANOVA)

1. Bring your own data from work (you can remove any private or confidential information, for example: if you are bringing any sales or cost data of an item/product or service – the name can be masked)
2. Use data from your previous work or company you have access to (again you can remove any private/confidential information)
3. Use data from public domain – In today’s world, there is no dearth of structured data. Here are some places where you can get data from:
   • Any data source you have access to like the Hawkes Learning Resources
     • Datasets (1) (Links to an external site.) from Hawkes
     • Datasets (2) (Links to an external site.) from Hawkes – Look at the additional datasets, not the chapter datasets
   • U.S. Bureau of Labor Statics (Links to an external site.)
   • U.S. Government’s open data (Links to an external site.)
   • Center for Medicare and Medicaid services (Links to an external site.)
   • Kaggle datasets (Links to an external site.)
   • WHO Data repository (Links to an external site.)
   • World Bank Data (Links to an external site.)
   • Google Public data explorer (Links to an external site.)
     • Amazing visualization or graphics
     • But remember, we need the data to do analysis, if you look at the bottom of any figure – Google would provide the source name, and you can retrieve data from there.
   • Any sports data (from the appropriate website, getting data in structured format for several years might be challenge, but a few minutes or an hour – you can do it)
     • For example – Cricket data could be obtained from espncricinfo (Links to an external site.).

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