Explore BrainMass

# Problem with statistical method type

Not what you're looking for? Search our solutions OR ask your own Custom question.

This content was COPIED from BrainMass.com - View the original, and get the already-completed solution here!

What statistical method is used to accept or reject the null hypothesis in determining if outsourcing is always beneficial? Please explain your reasons for choosing the selected method in detail and cite references (if any).

Also, explain the variables for which data will be collected. For each variable, identify the level of measurement that would be used.

https://brainmass.com/statistics/analysis-of-variance/problem-with-statistical-method-type-63368

#### Solution Preview

As an applied statistician and a faculty member in a graduate school of business let's see if we can shed a little light on your problem. First of all, however, I want you to do something for me... now and in the future. What I want you to do is put all your fears about statistics aside as there is nothing haunting or foreboding about statistical processes in any profession. Statistical processes are nothing more than extensions of the addition, subtraction, multiplication and division processes we all learned in high school. Statistics is simply a different expression of these for processes.

Now... a couple other important issues that needs to be addressed before getting into the "meat" of your assignment. Be patient! This wont hurt but it will help you to know what to do in the future as well as garner an appreciation of what research is all about. Did you ever ask yourself why prudent investigators set hypotheses and why the null hypothesis in necessary? Well...it goes like this:

Statistical processes are absolutely useless until something has been identified, a question asked, and a hypothesis stated. Here is an example. We all know what 1 + 1 equals... Yep, it equals 2. BUT what does it mean? The equation means nothing until you identify, with accuracy, the components of the equation or, in research, identify the investigative variables. That is, 1 what + 1 what equals 2 what? Well, 1 apple + 1 apple = 2 apples. But, 1 apple + 1 orange = what? Nothing but a fruit salad that has no common element. Therefore, identification of what you want to measure or gage is crucial to good research.