Programming Homework Help

This is the first part of a larger capstone project. I found a dataset that may work for the overall capstone but please let me know if you don’t think this dataset will work for the project. I have also included the final capstone project requirements at the bottom of this post so you know if this dataset will work. We need to be able to create a few hypotheses and null hypotheses then try to prove or disprove them. Descriptive analytics and predictive analytics should be performed using SAS. I am open to using a different dataset if you don’t think the one i attached will work.

Here is the requirement for the first question:

In this assignment, you will describe the public dataset and data analytics tools used to analyze your dataset in your Capstone Project. Examples of tools are found in the tools document. Tool instructions can be found in the Course Information section.

The report should include:

• a description about the dataset that you chose;
• identifying two to three tools or techniques used to analyze your dataset;
• describing the type of variables (binary, interval);
• a visual model of your data (i.e., data dictionary);
• an explanation of the potential of the data within your dataset and what it means for the organization; and
• defining future plans to analyze the data within the dataset.

—–Final Project – ***This information is in the text below is just so you know what we are working towards.- It is not to be answered for this question. I plan to give you weekly questions to progress the project.—–For your Capstone Project, you will select a public dataset and identify two or three tools to analyze the data for an organization in the United States. The purpose is to show the organization how these tools can be used to analyze data in a project. You submitted your project write-up in Module 5 and a rough draft in Module 6. You will incorporate all feedback from your instructor and submit your Final Report, including a presentation with speaker notes.

Your Final Report should include:

• information about the organization (history, services and products, location, employee size, and revenue) and why you chose it;
• an explanation about what dataset you selected and why you chose this data;
• identifying your research null and alternative hypotheses;
• identifying the tools and techniques you used to analyze the data;
• addressing security, privacy, and ethical concerns when handling and analyzing the data;
• explaining your data analysis outcomes and whether you could support your null or alternative hypothesis; (if you did not find support for your alternative hypothesis, what conclusions can you draw about your data?);
• programming code, and screenshots of data analysis outcomes;
• uploading your project (code and documents, for example) to your GitHub account and include the link in your project write-up; and
• the write-up components submitted in Module 5.