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?