must include:
-problem statement
-objectives
-potential benefits of research
-potential errors when examining relation between independent and dependent variable
-Methodology break-down:

Part 1

Step one: Disprove the Type 1 error!

-According to the literature (cite specific sources) is Type one error not possible?

-what is the literature that supports all parts of the hypothesis

Step two: Statistical Significance

-what is the level of significance?

-What are the errors?

-What are the built in errors?

-What level of error will you allow with the study (set error margin)?

-Analyze the errors from the data

Step three: Sampling

-Qualitative (25 samples) or Quantitative (300+ samples) or Mix Methods (combination of both)

-What is your idea sample size?

– Rationalize your sample size

– Where do you want to collect data from?

– Provide a plan B or secondary source collection

– Approximate data sets with real numbers and data sets (20%-30% of people will respond to a request for data so make sure your database reflects the sample size)

– if plan uses incentives make a plan on where the funds will come from because you can not use personal finances

– if using already existing data say “The study used “x” number of participants for their data and from that we will use __% from their dataset.”

Step four: What statistical software are you using?

Step five: How to check for accuracy?

-if the data collected is incomplete, will you keep it or exclude it? And why?

– what is your strategy for missing data?

Step six: Descriptive Statistics

-idea of what kind of people you will be working with, what is their demographic details?

– does this population exist in the database that we are proposing?