Question: Module 1 Project Contribution Overview What better way to internalize key statistical concepts than to actually use them with your own data?! For this project
Module Project Contribution
Overview
What better way to internalize key statistical concepts than to actually use them with your own data?!
For this project contribution you will define, collect, organize, visualize, and analyze a single set of data using the concepts and skills learned in this course. This will be an application of the DCOVA framework.
A contribution to the project portfolio will be required for each module. An example project piece dembinstrating the requirements for these contributions for each module are explained in each module. In this first module, you will collect some data of your choice and begin organizing and analyzing that data.
Resources
M Project example contribution
Microsoft support materials "Load the Analysis ToolPak in Excel"
Microsoft support materials "Analyze Data in Excel"
Pearson support materials on "StatCrunch"
Instructions
This project is scaffolded; in other words, you will build your project piecebypiece throughout the semester, from module to module. The Module project contribution will be your project, fully complete in final form.
For Module you will accomplish the following tasks.
Come up with a single one question or problem that you are interested in at least for the purposes of this project Recent questions that projects have been built on were: How much money did you spend on groceries last month? How many pairs of shoes do you own? How many pets have you owned in your lifetime? etc.
Collect data points needed for this project from answers to your one question.
This data needs to be of a quantitative variable numbers
You do NOT need to make this a big deal. Just talk to coworkers or customers at work with your supervisors permission if needed solicit responses from Facebook friends, research data on the internet, etc.
Finally, clearly define the purpose of your project and details of your collection of data, then calculate key descriptive statistics using a statistics appification Excel or StatCrunch
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